Utilizing machine learning to analyze trunk movement patterns in women with postpartum low back pain
Scientific Reports,
Год журнала:
2024,
Номер
14(1)
Опубликована: Авг. 12, 2024
Abstract
This
paper
presents
an
analysis
of
trunk
movement
in
women
with
postnatal
low
back
pain
using
machine
learning
techniques.
The
study
aims
to
identify
the
most
important
features
related
and
develop
accurate
models
for
predicting
pain.
Machine
approaches
showed
promise
analyzing
biomechanical
factors
(LBP).
applied
regression
classification
algorithms
proposed
dataset
from
100
postpartum
women,
50
LBP
without.
Optimized
optuna
Regressor
achieved
best
performance
a
mean
squared
error
(MSE)
0.000273,
absolute
(MAE)
0.0039,
R2
score
0.9968.
In
classification,
Basic
CNN
Random
Forest
Classifier
both
attained
near-perfect
accuracy
1.0,
area
under
receiver
operating
characteristic
curve
(AUC)
precision
recall
F1-score
outperforming
other
models.
Key
predictive
included
(correlation
-0.732
flexion
range
motion),
motion
measures
(flexion
extension
correlation
0.662),
average
movements
0.957
flexion).
Feature
selection
consistently
identified
pain,
flexion,
extension,
lateral
as
influential
across
methods.
While
limited
this
initial
constrained
by
generalizability,
offered
quantitative
insight.
Models
accurately
regressed
(MSE
<
0.01,
>
0.95)
classified
(accuracy
0.94)
biomechanics
distinguishing
LBP.
Incorporating
additional
demographic,
clinical,
patient-reported
may
enhance
individualized
risk
prediction
treatment
personalization.
preliminary
application
advanced
analytics
supported
learning's
potential
utility
determination
outcome
improvement.
provides
valuable
insights
into
use
techniques
can
potentially
inform
development
more
effective
treatments.
Trial
registration
:
trial
was
designed
observational
cross-section
study.
approved
Ethical
Committee
Deraya
University,
Faculty
Pharmacy,
(No:
10/2023).
According
ethical
standards
Declaration
Helsinki.
complies
principles
human
research.
Each
patient
signed
written
consent
form
after
being
given
thorough
description
trial.
conducted
at
outpatient
clinic
February
2023
till
June
30,
2023.
Язык: Английский
Exploring Inflammatory Changes in the Peripheral Blood of Type 2 Diabetes Mellitus in China
Journal of Inflammation Research,
Год журнала:
2025,
Номер
Volume 18, С. 1679 - 1688
Опубликована: Фев. 1, 2025
Objective:
Type
2
diabetes
mellitus
(T2DM)
is
a
serious,
chronic
metabolic
disease
globally
and
its
pathogenesis
not
completely
understood
yet.
This
study
aimed
to
thoroughly
investigate
the
fluctuation
of
inflammatory
markers
in
peripheral
blood
patients
with
T2DM,
which
are
rarely
reported.
Methods:
Peripheral
samples
from
T2DM
healthy
individuals,
as
well
their
clinical
information,
were
collected
at
Second
Affiliated
Hospital
Soochow
University.
Flow
cytometry
was
used
analyse
immune
cells
cytokines
blood.
CCK-8
assay
performed
detect
viability
THP-1
cell
after
treatment
5
m&Mgr;
or
50
glucose.
cytometry,
Western
Blotting
qPCR
apoptosis
monocytes
cells.
Results:
The
numbers
white
cells,
lymphocytes,
neutrophils
substantially
increased
elevated
IL-6
levels.
There
significant
decrease
due
caused
by
sustained
high
glucose
stimulation.
Hyperglycemia
reduced
monocyte
altered
subgroups
increasing
number
intermediate
non-classical
monocytes.
Conclusion:
In
summary,
our
work
reveals
that
do
have
variations
inflammation
biomarkers,
especially
Keywords:
mellitus,
inflammation,
Язык: Английский
Exploring the Antidiabetic Potential of Salvia officinalis Using Network Pharmacology, Molecular Docking and ADME/Drug-Likeness Predictions
Plants,
Год журнала:
2024,
Номер
13(20), С. 2892 - 2892
Опубликована: Окт. 16, 2024
A
combination
of
network
pharmacology,
molecular
docking
and
ADME/drug-likeness
predictions
was
employed
to
explore
the
potential
Язык: Английский
Deciphering the Gut–Liver Axis: A Comprehensive Scientific Review of Non-Alcoholic Fatty Liver Disease
Livers,
Год журнала:
2024,
Номер
4(3), С. 435 - 454
Опубликована: Сен. 12, 2024
Non-alcoholic
fatty
liver
disease
(NAFLD)
has
emerged
as
a
significant
global
health
issue.
The
condition
is
closely
linked
to
metabolic
dysfunctions
such
obesity
and
type
2
diabetes.
gut–liver
axis,
bidirectional
communication
pathway
between
the
gut,
plays
crucial
role
in
pathogenesis
of
NAFLD.
This
review
delves
into
mechanisms
underlying
exploring
influence
gut
microbiota,
intestinal
permeability,
inflammatory
pathways.
also
explores
potential
therapeutic
strategies
centered
on
modulating
microbiota
fecal
transplantation;
phage
therapy;
use
specific
probiotics,
prebiotics,
postbiotics
managing
By
understanding
these
interactions,
we
can
better
comprehend
development
advancement
NAFLD
identify
targets.
Язык: Английский