A systematic review of potentially toxic elements (PTEs) in river sediments from China: evaluation of associated non-dietary health risks
Environmental Monitoring and Assessment,
Год журнала:
2025,
Номер
197(3)
Опубликована: Фев. 11, 2025
Язык: Английский
Enhancing MRI diagnosis of myocarditis using deep learning and generative adversarial networks
Applied Mathematics and Nonlinear Sciences,
Год журнала:
2025,
Номер
10(1)
Опубликована: Янв. 1, 2025
Abstract
In
this
paper,
in
order
to
enhance
the
MRI
diagnosis
of
myocarditis,
a
generative
adversarial
network
(GAN)-based
diagnostic
model
for
myocarditis
is
constructed
paper.
The
images
provided
by
hospital
were
used
as
data
source
study,
and
image
format
was
transformed
into
NII
file
saving
using
Python
tool,
which
uniformly
cropped
480×768
pixels,
stored
form
datasets,
divided
dataset
A
(the
MRI-weighted
dataset)
B
myocarditis).
ResNet-34
U-Net
generator
discriminator,
respectively,
address
problem
difficulty
training
GAN
networks,
BN
layer
added
between
convolutional
activation
function
construction
finally
completed.
Determine
loss
function,
select
quantitative
evaluation
indexes
(MAE,
RMSE,
PSNR,
SSIM
PCC),
set
control
(CNN,
RNN,
LSTM,
GRU),
validate
analyze
discriminator
after
400
iterations
training,
value
both
almost
0.
paper’s
genus
pig
are
higher
than
other
four
models.
summary,
has
facilitating
effect
on
myocarditis.
Язык: Английский
Optimized Feature Selection and Deep Neural Networks to Improve Heart Disease Prediction
Deleted Journal,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 16, 2025
Heart
disease
remains
a
significant
health
threat
due
to
its
high
mortality
rate
and
increasing
prevalence.
Early
prediction
using
basic
physical
markers
from
routine
exams
is
crucial
for
timely
diagnosis
intervention.
However,
manual
analysis
of
large
datasets
can
be
labor-intensive
error-prone.
Our
goal
rapidly
reliably
anticipate
cardiac
variety
body
signs.
This
research
presents
unique
model
heart
prediction.
We
provide
system
predicting
that
blends
the
deep
convolutional
neural
network
with
feature
selection
technique
based
on
LinearSVC.
integrated
method
selects
subset
characteristics
are
strongly
linked
disease.
feed
these
features
into
conventual
we
constructed.
Also
improve
speed
predictor
avoid
gradient
varnishing
or
explosion,
network's
hyperparameters
were
tuned
random
search
algorithm.
The
proposed
was
evaluated
UCI
MIT
datasets.
number
indicators,
such
as
accuracy,
recall,
precision,
F1
score.
results
demonstrate
our
attains
accuracy
rates
98.16%,
98.2%,
95.38%,
97.84%
in
dataset,
an
average
MCC
score
90%.
These
affirm
efficacy
reliability
predict
Язык: Английский
The concentration and prevalence of aflatoxins and ochratoxin A in imported rice ( Oryza sativa ) samples from Iranian market: a probabilistic dietary risk assessment
Masoud Memar,
Zahra Esfandiari,
Mehrdad Ahmadi
и другие.
International Journal of Environmental & Analytical Chemistry,
Год журнала:
2024,
Номер
unknown, С. 1 - 18
Опубликована: Ноя. 13, 2024
This
investigation
aimed
to
measure
the
concentrations
of
total
aflatoxin
(AFT),
B1
(AFB1),
and
ochratoxin
A
(OTA)
in
imported
rice
samples
Iran
conduct
a
probabilistic
health
risk
assessment
for
consumers.
Three
thousand
seven
hundred
fifty-one
were
randomly
collected
from
March
2022
April
2024.
The
AFT,
AFB1,
OTA
analysed
using
high-performance
liquid
chromatography
with
flame
ionisation
detector
(HPLC-FID)
an
ultraviolet
(HPLC-UV).
ranking
mycotoxins
based
on
mean
concentration
was
as
follows:
AFT
(3.996
±
6.925
µg/kg)
>
AFB1
(2.648
5.746
(0.088
0.847
µg/kg).
prevalence
these
found
be
present
897
out
3,710
(24.18%),
657
(17.52%),
40
(1.07%).
Significant
correlations
observed
between
(C:
0.96,
p-value
<
0.001),
0.28,
0.15,
0.001).
95th
percentile
Margin
Exposure
(MOE)
adult
child
consumers
0.930
0.270,
respectively,
while
Hazard
Quotient
(HQ)
adults
children
0.030
0.100,
respectively.
estimated
cancer
percentages
22.220
43.500
children.
Overall,
consuming
containing
does
not
pose
significant
non-carcinogenic
consumers'
health.
However,
carcinogenic
is
higher
than
other
countries.
Therefore,
it
recommended
that
more
effective
continuous
monitoring
programmes
implemented
ensure
quality
rice.
Язык: Английский
Prevalence of Vancomycin-Resistant Van A and Van B Genes in ESKAPE Gram-Positive Bacteria Isolated from Hospitalized Patients in Mashhad, Iran
Research in Biotechnology and Environmental Science,
Год журнала:
2024,
Номер
3(4), С. 59 - 65
Опубликована: Дек. 12, 2024
Introduction:
The
ESKAPE
group,
comprising
Escherichia
coli,
Staphylococcus
aureus,
Klebsiella
pneumoniae,
Acinetobacter
baumannii,
Pseudomonas
aeruginosa,
and
Enterococcus
faecium,
is
known
for
its
role
in
hospital-acquired
infections
growing
resistance
to
antimicrobial
agents.
This
complicates
treatment
options,
particularly
with
last-resort
antibiotics,
such
as
vancomycin.
study
aims
determine
the
prevalence
of
vancomycin-resistant
genes
(Van
A
Van
B)
aureus
species
isolated
by
polymerase
chain
reaction
(PCR)
method
from
hospitalized
patients
Mashhad,
Iran.
Materials
Methods:
total
1000
clinical
samples
were
collected
over
six
months
four
hospitals
included
blood,
urine,
wound
swabs,
respiratory
secretions.
isolates
identified
through
standard
microbiological
tests.
Vancomycin
susceptibility
was
assessed
using
E-test
method.
presence
determined
PCR
Results:
Out
a
98
bacterial
isolates,
77
21
species.
Among
15
faecium
6
faecalis.
detected
7
total,
these
harboring
gene
1
carrying
B
gene.
Conclusion:
reveals
40%
1.3%
prevalences
vancomycin
respectively.
These
findings
underscore
critical
need
vigilant
antibiotic
stewardship
implementation
appropriate
strategies
effectively
manage
caused
resistant
pathogens.
Язык: Английский