Langmuir,
Journal Year:
2024,
Volume and Issue:
40(47), P. 25051 - 25060
Published: Nov. 12, 2024
The
fast,
and
highly
sensitive
estimation
of
cardiac
troponin
T
(cTnT)
is
crucial
for
the
early
identification
acute
myocardial
infarction
(AMI).
electrochemical
immunoassay-based
(EIB)
sensors
are
promising
this
purpose,
as
they
offer
precise
measurements
can
be
directly
assessed
in
intricate
matrices,
including
blood.
To
increase
sensitivity,
EIB
use
nanomaterials
or
amplification
processes,
which
laborious
to
develop.
With
this,
we
develop
an
immunosensor
detection
(cTnT).
sensing
platform
composed
functionalized
triangular
carbon
quantum
dots
stabilized
gold
nanoparticles
integrated
with
boron
nitride
nanosheets
(caf-TCQDs@AuNPs
on
HO-BNNS).
Ferrocene
carboxylic
acid
(Fc-COOH)
serves
signal
label.
composite
was
developed
examined
using
several
techniques
such
X-ray
diffraction
(XRD),
photoelectron
spectroscopy
(XPS),
transmission
electron
microscopy
(TEM),
cyclic
voltammetry,
chronocoulometry.
caf-TCQDs@AuNPs
supported
HO-BNNS,
have
a
large
surface
area
excellent
electrical
conductivity,
serve
effective
immobilization
anti-cTnT
monoclonal
antibodies
via
carbodiimide
coupling.
Fc-COOH,
functioning
label
through
oxidation
process,
HO-BNNS
establish
cTnT.
demonstrated
performance
determination
cTnT
under
optimal
conditions,
exhibiting
linearity
range
spanning
from
0.0001
100
ng
mL
Nature Communications,
Journal Year:
2023,
Volume and Issue:
14(1)
Published: Jan. 11, 2023
Nanozymes
with
superoxide
dismutase
(SOD)-like
activity
have
attracted
increasing
interest
due
to
their
ability
scavenge
anion,
the
origin
of
most
reactive
oxygen
species
in
vivo.
However,
SOD
nanozymes
reported
thus
far
yet
approach
natural
enzymes.
Here,
we
report
a
carbon
dot
(C-dot)
nanozyme
catalytic
over
10,000
U/mg,
comparable
that
Through
selected
chemical
modifications
and
theoretical
calculations,
show
SOD-like
C-dots
relies
on
hydroxyl
carboxyl
groups
for
binding
anions
carbonyl
conjugated
π-system
electron
transfer.
Moreover,
C-dot
exhibit
intrinsic
targeting
oxidation-damaged
cells
effectively
protect
neuron
ischemic
stroke
male
mice
model.
Together,
our
study
sheds
light
structure-activity
relationship
nanozymes,
demonstrates
potential
treating
oxidation
stress
related
diseases.
International Journal of Nanomedicine,
Journal Year:
2025,
Volume and Issue:
Volume 20, P. 2427 - 2443
Published: Feb. 1, 2025
The
increasing
global
prevalence
of
cardiovascular
diseases
highlights
the
urgent
need
for
innovative
diagnostic
and
therapeutic
strategies.
Aptamers,
small
single-stranded
nucleic
acid
molecules
with
exceptional
specificity
affinity
target
biomolecules,
have
emerged
as
promising
tools
precise
diagnostics
targeted
therapies.
Their
selective
binding
capabilities
provide
valuable
insights
into
molecular
mechanisms
underlying
conditions.
When
integrated
nanosystems,
aptamers
enhance
delivery,
bioavailability,
stability
agents,
addressing
challenges
solubility
degradation.
This
integration
enables
more
drug
advanced
imaging
techniques,
improved
interventions,
ultimately
improving
management
diseases.
Recent
advancements
in
aptamer
selection
methodologies,
coupled
their
unique
three-dimensional
structures,
significantly
expanded
application
potential
health.
By
combining
novel
approaches
to
disease
diagnosis
treatment
are
emerging,
enhanced
efficacy,
safety,
precision.
review
explores
recent
progress
development
aptamer-based
nanosystems
Medicine,
Journal Year:
2024,
Volume and Issue:
103(15), P. e37793 - e37793
Published: April 12, 2024
Acute
myocardial
infarction
(AMI),
the
most
severe
cardiovascular
event
in
clinical
settings,
imposes
a
significant
burden
with
its
annual
increase
morbidity
and
mortality
rates.
However,
it
is
noteworthy
that
due
to
AMI
developed
countries
has
experienced
decline,
largely
attributable
advancements
medical
interventions
such
as
percutaneous
coronary
intervention.
This
trend
highlights
importance
of
accurate
diagnosis
effective
treatment
preserve
myocardium
at
risk
improve
patient
outcomes.
Conventional
biomarkers
myoglobin,
creatine
kinase
isoenzymes,
troponin
have
been
instrumental
AMI.
recent
years
witnessed
emergence
new
demonstrating
potential
further
enhance
accuracy
diagnosis.
literature
review
focuses
on
biomarker
research
context
Mathematics,
Journal Year:
2024,
Volume and Issue:
12(17), P. 2693 - 2693
Published: Aug. 29, 2024
Electrocardiography
(ECG)
plays
a
pivotal
role
in
monitoring
cardiac
health,
yet
the
manual
analysis
of
ECG
signals
is
challenging
due
to
complex
task
identifying
and
categorizing
various
waveforms
morphologies
within
data.
Additionally,
datasets
often
suffer
from
significant
class
imbalance
issue,
which
can
lead
inaccuracies
detecting
minority
samples.
To
address
these
challenges
enhance
effectiveness
efficiency
arrhythmia
detection
imbalanced
datasets,
this
study
proposes
novel
approach.
This
research
leverages
MIT-BIH
dataset,
encompassing
total
109,446
beats
distributed
across
five
classes
following
Association
for
Advancement
Medical
Instrumentation
(AAMI)
standard.
Given
dataset’s
inherent
imbalance,
1D
generative
adversarial
network
(GAN)
model
introduced,
incorporating
Bi-LSTM
synthetically
generate
two
signal
classes,
represent
mere
0.73%
fusion
(F)
2.54%
supraventricular
(S)
The
generated
are
rigorously
evaluated
similarity
real
data
using
three
key
metrics:
mean
squared
error
(MSE),
structural
index
(SSIM),
Pearson
correlation
coefficient
(r).
In
addition
addressing
work
presents
deep
learning
models
tailored
classification:
SkipCNN
(a
convolutional
neural
with
skip
connections),
SkipCNN+LSTM,
SkipCNN+LSTM+Attention
mechanisms.
further
accuracy,
test
dataset
assessed
an
ensemble
model,
consistently
outperforms
individual
models.
performance
evaluation
employs
standard
metrics
such
as
precision,
recall,
F1-score,
along
their
average,
macro
weighted
average
counterparts.
Notably,
SkipCNN+LSTM
emerges
most
promising,
achieving
remarkable
F1-scores
99.3%,
were
elevated
impressive
99.60%
through
techniques.
Consequently,
innovative
combination
balancing
techniques,
GAN-SkipNet
not
only
resolves
posed
by
but
also
provides
robust
reliable
solution
detection.
stands
poised
clinical
applications,
offering
potential
be
deployed
hospitals
real-time
detection,
thereby
benefiting
patients
healthcare
practitioners
alike.
Algorithms,
Journal Year:
2024,
Volume and Issue:
17(8), P. 364 - 364
Published: Aug. 19, 2024
Heart
diseases
such
as
cardiovascular
and
myocardial
infarction
are
the
foremost
reasons
of
death
in
world.
The
timely,
accurate,
effective
prediction
heart
is
crucial
for
saving
lives.
Electrocardiography
(ECG)
a
primary
non-invasive
method
to
identify
cardiac
abnormalities.
However,
manual
interpretation
ECG
recordings
disease
diagnosis
time-consuming
inaccurate
process.
For
accurate
efficient
detection
from
12-lead
dataset,
we
have
proposed
hybrid
residual/inception-based
deeper
model
(HRIDM).
In
this
study,
utilized
datasets
various
sources,
which
multi-institutional
large
datasets.
trained
on
data
over
10,000
patients.
We
compared
with
several
state-of-the-art
(SOTA)
models,
LeNet-5,
AlexNet,
VGG-16,
ResNet-50,
Inception,
LSTM,
same
training
test
To
show
effectiveness
computational
efficiency
model,
only
20
epochs
without
GPU
support
achieved
an
accuracy
50.87%
dataset
27
categories
found
that
our
outperformed
previous
studies
participated
official
PhysioNet/CinC
Challenge
2020
fourth
place
41
ranking
teams.
result
study
indicates
implying
new
predicting
using
ECGs.