2022 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO),
Journal Year:
2023,
Volume and Issue:
unknown, P. 439 - 442
Published: July 31, 2023
Herein,
the
surface-modified
M/layered
double
hydroxides
(LDHs)
were
demonstrated
capable
of
analyzing
small
metabolites
by
laser
desorption/ionization
mass
spectrometry
(LDI
MS).
We
first
synthesized
M/LDHs
with
a
designed
host-guest
structure
via
one-pot
ultrasound
method.
Based
on
high
signal
response
and
low
background
interference
at
range
(<
1000
Da),
have
good
performance
in
metabolite
detection
using
LDI
MS.
Therefore,
assay
M/LDH-enhanced
MS
has
broad
prospects
applications
for
screening,
biochemical
analysis,
disease
diagnosis,
etc.
ACS Nano,
Journal Year:
2023,
Volume and Issue:
17(20), P. 19779 - 19792
Published: Oct. 11, 2023
Timely
screening
of
neuromyelitis
optica
spectrum
disorder
(NMOSD)
and
differential
diagnosis
from
myelin
oligodendrocyte
glycoprotein
associated
(MOGAD)
are
the
keys
to
improving
quality
life
patients.
Metabolic
disturbance
occurs
with
development
NMOSD.
Still,
advanced
tools
required
probe
metabolic
phenotype
Here,
we
developed
a
fast
nanoparticle-enhanced
laser
desorption/ionization
mass
spectrometry
assay
for
multiplexing
fingerprints
(MFs)
trace
plasma
cerebrospinal
fluid
(CSF)
samples
in
30
s.
Machine
learning
MFs
achieved
timely
NMOSD
healthy
donors
an
area
under
receiver
operator
characteristic
curve
(AUROC)
0.998,
it
comprehensively
revealed
dysregulated
neurotransmitter
energy
metabolisms.
Combining
comprehensive
both
CSF,
constructed
integrated
panel
versus
MOGAD
AUROC
0.923.
This
approach
demonstrated
performance
superior
that
human
experts
classifying
two
diseases,
especially
antibody
assay-limited
regions.
Together,
this
provides
nanomaterial-based
tool
identifying
vulnerable
populations
below
threshold
aquaporin-4
positivity.
ACS Nano,
Journal Year:
2024,
Volume and Issue:
18(3), P. 2409 - 2420
Published: Jan. 8, 2024
Serum
united
urine
metabolic
analysis
comprehensively
reveals
the
disease
status
for
kidney
diseases
in
particular.
Thus,
precise
and
convenient
acquisition
of
molecular
information
from
biofluids
is
vitally
important
clinical
diagnosis
biomarker
discovery.
Laser
desorption/ionization
mass
spectrometry
(LDI-MS)
presents
various
advantages
analysis;
however,
there
remain
challenges
ionization
efficiency
MS
signal
reproducibility.
Herein,
we
constructed
a
self-assembled
hyperbranched
black
gold
nanoarray
(HyBrAuNA)
assisted
LDI-MS
platform
to
profile
serum
fingerprints
(S-UMFs)
early
stage
renal
cell
carcinoma
(RCC).
The
closely
packed
HyBrAuNA
afforded
strong
electromagnetic
field
enhancement
high
photothermal
conversion
efficacy,
enabling
effective
low
abundant
metabolites
S-UMF
collection.
With
uniform
nanoarray,
presented
excellent
reproducibility
ensure
accuracy
S-UMFs
obtained
seconds.
When
it
was
combined
with
automated
machine
learning
S-UMFs,
RCC
patients
were
discriminated
healthy
controls
an
area
under
curve
(AUC)
>
0.99.
Furthermore,
screened
out
panel
9
(4
5
urine)
related
pathways
toward
tumor.
In
view
its
high-throughput,
fast
analytical
speed,
sample
consumption,
our
possesses
potential
profiling
pathogenic
mechanism
exploration.
Advanced Materials,
Journal Year:
2024,
Volume and Issue:
36(18)
Published: Jan. 19, 2024
Abstract
Effective
detection
of
bio‐molecules
relies
on
the
precise
design
and
preparation
materials,
particularly
in
laser
desorption/ionization
mass
spectrometry
(LDI‐MS).
Despite
significant
advancements
substrate
performance
single‐structured
substrates
remains
suboptimal
for
LDI‐MS
analysis
complex
systems.
Herein,
designer
Au@SiO
2
@ZrO
core‐shell
are
developed
LDI‐MS‐based
early
diagnosis
prognosis
pancreatic
cancer
(PC).
Through
controlling
Au
core
size
ZrO
shell
crystallization,
signal
amplification
metabolites
up
to
3
orders
is
not
only
achieved,
but
also
synergistic
mechanism
LDI
process
revealed.
The
optimized
enables
a
direct
record
serum
metabolic
fingerprints
(SMFs)
by
LDI‐MS.
Subsequently,
SMFs
employed
distinguish
PC
(stage
I/II)
from
controls,
with
an
accuracy
92%.
Moreover,
prognostic
prediction
scoring
system
established
enhanced
efficacy
predicting
survival
compared
CA19‐9
(p
<
0.05).
This
work
contributes
material‐based
prognosis.
Advanced Materials,
Journal Year:
2024,
Volume and Issue:
36(21)
Published: Jan. 24, 2024
Abstract
It
is
challenging
to
detect
and
differentiate
multiple
diseases
with
high
complexity/similarity
from
the
same
organ.
Metabolic
analysis
based
on
nanomatrix‐assisted
laser
desorption/ionization
mass
spectrometry
(NMALDI‐MS)
a
promising
platform
for
disease
diagnosis,
while
enhanced
property
of
its
core
nanomatrix
materials
has
plenty
room
improvement.
Herein,
multidimensional
interactive
cascade
nanochip
composed
iron
oxide
nanoparticles
(FeNPs)/MXene/gold
(AuNPs),
IMG,
reported
serum
metabolic
profiling
achieve
high‐throughput
detection
liver
diseases.
MXene
serves
as
multi‐binding
site
an
electron‐hole
source
ionization
during
NMALDI‐MS
analysis.
Introduction
AuNPs
surface
plasmon
resonance
(SPR)
properties
facilitates
charge
accumulation
rapid
energy
conversion.
FeNPs
are
integrated
into
MXene/Au
nanocomposite
sharply
reduce
thermal
conductivity
negligible
heat
loss
strong
thermally‐driven
desorption,
construct
multi‐interaction
proton
transport
pathway
ionization.
Analysis
these
fingerprint
signals
detected
IMG
through
neural
network
model
results
in
differentiation
via
single
pass
revelation
potential
biomarkers.
The
method
can
rapidly
accurately
screen
various
diseases,
thus
allowing
timely
treatment
ACS Nano,
Journal Year:
2024,
Volume and Issue:
18(34), P. 23625 - 23636
Published: Aug. 16, 2024
Accurate
diagnosis
and
classification
of
kidney
cancer
are
crucial
for
high-quality
healthcare
services.
However,
the
current
diagnostic
platforms
remain
challenges
in
rapid
accurate
analysis
large-scale
clinical
biosamples.
Herein,
we
fabricated
a
bifunctional
smart
nanoplatform
based
on
tannic
acid-modified
gold
nanoflowers
(TA@AuNFs),
integrating
nanozyme
catalysis
colorimetric
sensing
self-assembled
nanoarray-assisted
LDI-MS
analysis.
The
TA@AuNFs
presented
peroxidase
(POD)-
glucose
oxidase-like
activity
owing
to
abundant
galloyl
residues
surface
AuNFs.
Combined
with
assay,
TA@AuNF-based
was
used
directly
detect
serum
tumor
diagnosis.
On
other
hand,
could
self-assemble
into
closely
packed
homogeneous
two-dimensional
(2D)
nanoarrays
at
liquid-liquid
interfaces
by
using
Fe
Advanced Science,
Journal Year:
2024,
Volume and Issue:
11(12)
Published: Jan. 15, 2024
Abstract
Detecting
exosomal
markers
using
laser
desorption/ionization
time‐of‐flight
mass
spectrometry
(LDI‐TOF
MS)
is
a
novel
approach
for
examining
liquid
biopsies
of
non‐small
cell
lung
cancer
(NSCLC)
samples.
However,
LDI‐TOF
MS
limited
by
low
sensitivity
and
poor
reproducibility
when
analyzing
intact
proteins
directly.
In
this
report,
gold
nanoparticles/cellulose
nanocrystals
(AuNPs/CNC)
introduced
as
the
matrix
direct
analysis
in
NSCLC
serum
exosomes.
AuNPs/CNC
with
“dual
dispersion”
effects
dispersed
stabilized
AuNPs
improved
ion
inhibition
caused
protein
aggregation.
These
features
increased
signal‐to‐noise
ratio
[M+H]
+
peaks
two
orders
magnitude
lowered
detection
limit
to
0.01
mg
mL
–1
.
The
coefficient
variation
or
without
measured
10.2%
32.5%,
respectively.
excellent
yielded
linear
relationship
(
y
=
15.41
x
–
7.983,
R
2
0.989)
over
concentration
range
20
Finally,
AuNPs/CNC‐assisted
provides
clinically
relevant
fingerprint
information
serum,
characteristic
S100
calcium‐binding
A10,
Urokinase
plasminogen
activator
surface
receptor,
Plasma
protease
C1
inhibitor,
Tyrosine‐protein
kinase
Fgr
Mannose‐binding
lectin
associated
serine
represented
predictive
biomarkers
risk.
Journal of Nanobiotechnology,
Journal Year:
2023,
Volume and Issue:
21(1)
Published: March 24, 2023
Non-small
cell
lung
cancer
(NSCLC)
is
the
most
common
pathological
type
of
LC
and
ranks
as
leading
cause
deaths.
Circulating
exosomes
have
emerged
a
valuable
biomarker
for
diagnosis
NSCLC,
while
performance
current
electrochemical
assays
exosome
detection
constrained
by
unsatisfactory
sensitivity
specificity.
Here
we
integrated
ratiometric
biosensor
with
an
OR
logic
gate
to
form
assay
surface
protein
profiling
from
clinical
serum
samples.
By
using
specific
aptamers
recognition
clinically
validated
biomarkers
(EpCAM
CEA),
enabled
ultrasensitive
trace
levels
NSCLC-derived
in
complex
samples
(15.1
particles
μL-1
within
linear
range
102-108
μL-1).
The
outperformed
analysis
six
accurate
diagnosis,
staging,
prognosis
displaying
diagnostic
93.3%
even
at
early
stage
(Stage
I).
provides
advanced
tool
quantification
facilitates
exosome-based
liquid
biopsies
management
clinics.
Advanced Science,
Journal Year:
2024,
Volume and Issue:
unknown
Published: July 8, 2024
Renal
cell
carcinoma
(RCC)
is
a
substantial
pathology
of
the
urinary
system
with
growing
prevalence
rate.
However,
current
clinical
methods
have
limitations
for
managing
RCC
due
to
heterogeneity
manifestations
disease.
Metabolic
analyses
are
regarded
as
preferred
noninvasive
approach
in
clinics,
which
can
substantially
benefit
characterization
RCC.
This
study
constructs
nanoparticle-enhanced
laser
desorption
ionization
mass
spectrometry
(NELDI
MS)
analyze
metabolic
fingerprints
renal
tumors
(n
=
456)
and
healthy
controls
200).
The
classification
models
yielded
areas
under
curves
(AUC)
0.938
(95%
confidence
interval
(CI),
0.884-0.967)
distinguishing
from
controls,
0.850
differentiating
malignant
benign
CI,
0.821-0.915),
0.925-0.932
classifying
subtypes
0.821-0.915).
For
early
stage
subtypes,
averaged
diagnostic
sensitivity
90.5%
specificity
91.3%
test
set
achieved.
biomarkers
identified
potential
indicator
subtype
diagnosis
(p
<
0.05).
To
validate
prognostic
performance,
predictive
model
participants
achieve
prediction
disease
0.003)
constructed.
provides
promising
prospect
applying
analytical
tools
characterization.
