ACS Sensors,
Journal Year:
2024,
Volume and Issue:
9(11), P. 5999 - 6010
Published: Oct. 18, 2024
Label-free
surface-enhanced
Raman
spectroscopy
(SERS)
is
capable
of
capturing
rich
compositional
information
from
complex
biosamples
by
providing
vibrational
spectra
that
are
crucial
for
biosample
identification.
However,
increasing
complexity
and
subtle
variations
in
biological
media
can
diminish
the
discrimination
accuracy
traditional
SERS
excited
a
single
laser
wavelength.
Herein,
we
introduce
multiwavelength
approach
combined
with
machine
learning
(ML)-based
classification
to
improve
human
urine
specimens
bladder
cancer
(BCa)
diagnosis.
This
strategy
leverages
excitation-wavelength-dependent
spectral
profiles
matrices,
which
mainly
attributed
wavelength-related
changes
individual
analytes
differences
variation
ratios
intensity
across
different
wavelengths
among
various
analytes.
By
fingerprints
under
multiple
excitation
wavelengths,
acquire
more
comprehensive
unique
chemical
on
samples.
Further
experimental
examinations
clinical
specimens,
supported
ML
algorithms,
demonstrate
effectiveness
this
diagnostic
BCa
staging
its
invasion
numbers
wavelengths.
The
holds
promise
as
convenient,
cost-effective,
broadly
applicable
technique
precise
identification
matrices
diagnosis
diseases
based
body
fluids.
The
year
2024
marks
the
50th
anniversary
of
discovery
surface-enhanced
Raman
spectroscopy
(SERS).
Over
recent
years,
SERS
has
experienced
rapid
development
and
became
a
critical
tool
in
biomedicine
with
its
unparalleled
sensitivity
molecular
specificity.
This
review
summarizes
advancements
challenges
substrates,
nanotags,
instrumentation,
spectral
analysis
for
biomedical
applications.
We
highlight
key
developments
colloidal
solid
an
emphasis
on
surface
chemistry,
hotspot
design,
3D
hydrogel
plasmonic
architectures.
Additionally,
we
introduce
innovations
including
those
interior
gaps,
orthogonal
reporters,
near-infrared-II-responsive
properties,
along
biomimetic
coatings.
Emerging
technologies
such
as
optical
tweezers,
nanopores,
wearable
sensors
have
expanded
capabilities
single-cell
single-molecule
analysis.
Advances
analysis,
signal
digitalization,
denoising,
deep
learning
algorithms,
improved
quantification
complex
biological
data.
Finally,
this
discusses
applications
nucleic
acid
detection,
protein
characterization,
metabolite
monitoring,
vivo
spectroscopy,
emphasizing
potential
liquid
biopsy,
metabolic
phenotyping,
extracellular
vesicle
diagnostics.
concludes
perspective
clinical
translation
SERS,
addressing
commercialization
potentials
tissue
sensing
imaging.
Chemical Society Reviews,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 23, 2024
This
review
comprehensively
presents
the
fifty-year
journey
of
surface-enhanced
Raman
spectroscopy
(SERS),
covering
its
discovery,
pivotal
phases,
innovative
methods,
and
key
inspirations
from
pioneers
trailblazers.
Nanoscale,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 1, 2025
The
integration
of
a
2D
WS
2
monolayer
into
plasmonic
nanogap
leads
to
synergistic
enhancement,
achieving
an
unprecedented
Raman
enhancement
factor
10
14
–10
15
and
ultrasensitive
single-molecule
SERS
detection
(10
−16
M).
Theranostics,
Journal Year:
2024,
Volume and Issue:
14(15), P. 6071 - 6087
Published: Jan. 1, 2024
Stroke
induces
metabolic
changes
in
the
body,
and
metabolites
have
become
potential
biomarkers
for
stroke.
However,
specific
involved
stroke
mechanisms
underlying
brain
injury
during
remain
unclear.
Biosensors,
Journal Year:
2024,
Volume and Issue:
14(8), P. 372 - 372
Published: July 31, 2024
The
incidence
of
thyroid
cancer
is
increasing
worldwide.
Fine-needle
aspiration
(FNA)
cytology
widely
applied
with
the
use
extracted
biological
cell
samples,
but
current
FNA
labor-intensive,
time-consuming,
and
can
lead
to
risk
false-negative
results.
Surface-enhanced
Raman
spectroscopy
(SERS)
combined
machine
learning
algorithms
holds
promise
for
diagnosis.
In
this
study,
we
develop
a
label-free
SERS
liquid
biopsy
method
rapid
accurate
diagnosis
by
using
washout
fluids.
These
supernatants
are
mixed
silver
nanoparticle
colloids,
dispersed
in
quartz
capillary
measurements
discriminate
between
healthy
malignant
samples.
We
collect
spectra
36
samples
(18
18
benign)
compare
four
classification
models:
Principal
Component
Analysis-Linear
Discriminant
Analysis
(PCA-LDA),
Random
Forest
(RF),
Support
Vector
Machine
(SVM),
Convolutional
Neural
Network
(CNN).
results
show
that
CNN
algorithm
most
precise,
high
accuracy
88.1%,
sensitivity
87.8%,
area
under
receiver
operating
characteristic
curve
0.953.
Our
approach
simple,
convenient,
cost-effective.
This
study
indicates
assisted
deep
models
great
early
detection
screening
cancer.
Advanced Science,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Sept. 4, 2024
Abstract
Metabolic
dysregulation
is
a
key
driver
of
cellular
senescence,
contributing
to
the
progression
systemic
aging.
The
heterogeneity
senescent
cells
and
their
metabolic
shifts
are
complex
unexplored.
A
microfluidic
SlipChip
integrated
with
surface‐enhanced
Raman
spectroscopy
(SERS),
termed
SlipChip‐SERS,
developed
for
single‐cell
metabolism
analysis.
This
SlipChip‐SERS
enables
compartmentalization
single
cells,
parallel
delivery
saponin
nanoparticles
release
intracellular
metabolites
realize
SERS
detection
simple
slipping
operations.
Analysis
different
cancer
cell
lines
using
demonstrated
its
capability
sensitive
multiplexed
profiling
individual
cells.
When
applied
human
primary
fibroblasts
ages,
it
identified
12
differential
metabolites,
spermine
validated
as
potent
inducer
senescence.
Prolonged
exposure
can
induce
classic
senescence
phenotype,
such
increased
senescence‐associated
β‐glactosidase
activity,
elevated
expression
senescence‐related
genes
reduced
LMNB1
levels.
Additionally,
senescence‐inducing
capacity
in
HUVECs
WRL‐68
confirmed,
exogenous
treatment
accumulation
H
2
O
.
Overall,
novel
system
analysis,
revealing
potential
across
multiple
types,
which
may
offer
new
strategies
addressing
ageing
ageing‐related
diseases.
