Aptasensor‐based point‐of‐care detection of cardiac troponin biomarkers for diagnosis of acute myocardial infarction
The Kaohsiung Journal of Medical Sciences,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 3, 2025
Abstract
Acute
myocardial
infarction
(AMI)
represents
a
critical
health
challenge
characterized
by
significant
reduction
in
blood
flow
to
the
heart,
leading
high
rates
of
mortality
and
morbidity.
Cardiac
troponins,
specifically
cardiac
troponin
I
T,
are
essential
proteins
involved
muscle
contraction
serve
as
vital
biomarkers
for
diagnosis
AMI.
Aptasensors
utilize
synthetic
aptamers
or
peptides
with
affinity
specific
offer
promising
approach
integration
into
portable,
user‐friendly
point‐of‐care
(POC)
applications.
This
review
explores
recent
advances
POC
aptasensor‐based
platforms
rapid
detection
biomarkers.
Furthermore,
this
addresses
current
challenges
potential
future
directions
development
aptasensor.
Also,
it
highlights
their
improve
timely
accurate
clinical
emergency
settings.
Language: Английский
Mitochondrial mt12361A>G increased risk of metabolic dysfunction-associated steatotic liver disease among non-diabetes
World Journal of Gastroenterology,
Journal Year:
2025,
Volume and Issue:
31(10)
Published: Feb. 26, 2025
BACKGROUND
Insulin
resistance,
lipotoxicity,
and
mitochondrial
dysfunction
contribute
to
the
pathogenesis
of
metabolic
dysfunction-associated
steatotic
liver
disease
(MASLD).
Mitochondrial
impairs
oxidative
phosphorylation
increases
reactive
oxygen
species
production,
leading
steatohepatitis
hepatic
fibrosis.
Artificial
intelligence
(AI)
is
a
potent
tool
for
diagnosis
risk
stratification.
AIM
To
investigate
DNA
polymorphisms
in
susceptibility
MASLD
establish
an
AI
model
screening.
METHODS
Multiplex
polymerase
chain
reaction
was
performed
comprehensively
genotype
82
variants
screening
dataset
(n
=
264).
The
significant
single
nucleotide
polymorphism
validated
independent
cohort
1046)
using
Taqman®
allelic
discrimination
assay.
Random
forest,
eXtreme
gradient
boosting,
Naive
Bayes,
logistic
regression
algorithms
were
employed
construct
MASLD.
RESULTS
In
dataset,
only
mt12361A>G
significantly
associated
with
showed
borderline
significance
patients
2-3
cardiometabolic
traits
compared
controls
validation
(P
0.055).
Multivariate
analysis
confirmed
that
factor
[odds
ratio
(OR)
2.54,
95%
confidence
interval
(CI):
1.19-5.43,
P
0.016].
genetic
effect
non-diabetic
group
but
not
diabetic
group.
mt12361G
carriers
had
2.8-fold
higher
than
A
(OR
2.80,
95%CI:
1.22-6.41,
0.015).
By
integrating
clinical
features
mt12361A>G,
random
forest
outperformed
other
detecting
[training
area
under
receiver
operating
characteristic
curve
(AUROC)
1.000,
AUROC
0.876].
CONCLUSION
variant
increased
severity
patients.
supports
management
primary
care
settings.
Language: Английский
The current status and future directions of artificial intelligence in the prediction, diagnosis, and treatment of liver diseases
Digital Health,
Journal Year:
2025,
Volume and Issue:
11
Published: April 1, 2025
Early
detection,
accurate
diagnosis,
and
effective
treatment
of
liver
diseases
are
paramount
importance
for
improving
patient
survival
rates.
However,
traditional
methods
frequently
influenced
by
subjective
factors
technical
limitations.
With
the
rapid
progress
artificial
intelligence
(AI)
technology,
its
applications
in
medical
field,
particularly
prediction,
diseases,
have
drawn
increasing
attention.
This
article
offers
a
comprehensive
review
current
AI
hepatology.
It
elaborates
on
how
is
utilized
to
predict
progression
diagnose
various
conditions,
assist
formulating
personalized
plans.
The
emphasizes
key
advancements,
including
application
machine
learning
deep
algorithms.
Simultaneously,
it
addresses
challenges
limitations
within
this
domain.
Moreover,
pinpoints
future
research
directions.
underscores
necessity
large-scale
datasets,
robust
algorithms,
ethical
considerations
clinical
practice,
which
crucial
facilitating
integration
technology
enhancing
diagnostic
therapeutic
capabilities
diseases.
Language: Английский