Journal of Inflammation Research,
Journal Year:
2024,
Volume and Issue:
Volume 17, P. 10141 - 10161
Published: Dec. 1, 2024
Purpose:
Osteoarthritis
(OA)
is
the
most
common
degenerative
joint
disease.
However,
its
etiology
remains
largely
unknown.
Zinc
Finger
Protein
652
(ZNF652)
a
transcription
factor
implicated
in
various
biological
processes.
Nevertheless,
role
OA
has
not
been
elucidated.
Methods:
The
search
term
"osteoarthritis"
was
utilized
to
procure
transcriptome
data
relating
patients
and
healthy
people
from
Gene
Expression
Omnibus
(GEO)
database.
Then
screening
process
initiated
identify
differentially
expressed
genes
(DEGs).
DEGs
were
discerned
using
three
distinct
machine
learning
methods.
accuracy
of
these
diagnosing
evaluated
Receiver
Operating
Characteristic
(ROC)
Curve.
A
competitive
endogenous
RNA
(ceRNA)
visualization
network
established
delve
into
potential
regulatory
targets.
ZNF652
expression
confirmed
cartilage
rats
quantitative
reverse
polymerase
chain
reaction
(qRT-PCR)
Western
blotting
(WB)
analyzed
an
independent
t
-test.
Results:
identified
as
DEG
exhibited
highest
diagnostic
value
for
according
ROC
analysis.
GO
KEGG
enrichment
analyses
suggest
that
plays
vital
development
through
processes
including
nitric
oxide
anabolism,
macrophage
proliferation,
immune
response,
PI3K/Akt
MAPK
signaling
pathways.
increased
validated
qRT-PCR
(1.193
±
0.005
vs
1.000
0.005,
p
<
0.001)
WB
(0.981
0.055
0.856
0.026,
=
0.012)
Conclusion:
found
be
related
pathogenesis
can
potentially
serve
therapeutic
target
OA.
underlying
mechanism
pathways,
cells
their
functions
findings
need
clinical
trials
molecular
requires
further
study.
Keywords:
osteoarthritis,
zinc
finger
protein
652,
algorithms,
cell
Frontiers in Medicine,
Journal Year:
2024,
Volume and Issue:
11
Published: Oct. 9, 2024
Objectives
Low-dose
aspirin
is
widely
used
as
a
preventive
medication
for
cardiovascular
diseases.
However,
there
controversy
regarding
the
impact
of
low-dose
on
articular
cartilage.
The
aim
this
study
to
explore
association
between
intake
and
osteoarthritis
(OA).
Methods
We
conducted
cross-sectional
based
United
States
population
data
from
National
Health
Nutrition
Examination
Survey
(NHANES)
2011–2018.
investigation
diagnosis
OA
was
self-reporting
in
questionnaires.
Multivariate
regression
models
assess
relationship
OA.
In
addition,
subgroup
interaction
analysis
were
performed
robustness
results.
Results
A
total
12,215
participants
included
study.
logistic
showed
that
use
had
significantly
increased
odds
(OR
=
1.14;
95%
CI:
1.01–1.28;
p
0.035).
significant
consistent
with
still
observed
each
stratified
by
gender,
age,
presence
comorbidities
including
diabetes,
coronary
heart
disease,
hypertension,
stroke.
results
illustrated
stable
all
subgroups
no
interaction.
Conclusion
Our
confirmed
may
increase
risk
Attention
should
be
paid
possibility
joint
degenerative
changes
patients
who
take
chronically.
further
studies
are
needed
possible
mechanisms
behind
association.
Advanced Healthcare Materials,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Nov. 28, 2024
Abstract
Musculoskeletal
diseases
have
emerged
as
the
leading
cause
of
disability
worldwide,
with
their
prevalence
increasing
annually.
In
light
this
escalating
health
challenge,
organoids,
an
emerging
technology
in
tissue
engineering,
offer
promising
solutions
for
disease
modeling,
drug
screening,
regeneration,
and
repair
processes.
The
successful
development
musculoskeletal
organoids
represents
a
significant
breakthrough,
providing
novel
platform
studying
facilitating
discovery
new
treatments.
Moreover,
serve
valuable
complements
to
traditional
2D
culture
methods
animal
models,
offering
rich
insights
into
biology.
This
review
provides
overview
organoid
technology,
outlining
construction
processes
various
highlighting
similarities
differences.
Furthermore,
challenges
associated
systems
are
discussed
future
perspectives
offered.
Journal of Inflammation Research,
Journal Year:
2024,
Volume and Issue:
Volume 17, P. 10141 - 10161
Published: Dec. 1, 2024
Purpose:
Osteoarthritis
(OA)
is
the
most
common
degenerative
joint
disease.
However,
its
etiology
remains
largely
unknown.
Zinc
Finger
Protein
652
(ZNF652)
a
transcription
factor
implicated
in
various
biological
processes.
Nevertheless,
role
OA
has
not
been
elucidated.
Methods:
The
search
term
"osteoarthritis"
was
utilized
to
procure
transcriptome
data
relating
patients
and
healthy
people
from
Gene
Expression
Omnibus
(GEO)
database.
Then
screening
process
initiated
identify
differentially
expressed
genes
(DEGs).
DEGs
were
discerned
using
three
distinct
machine
learning
methods.
accuracy
of
these
diagnosing
evaluated
Receiver
Operating
Characteristic
(ROC)
Curve.
A
competitive
endogenous
RNA
(ceRNA)
visualization
network
established
delve
into
potential
regulatory
targets.
ZNF652
expression
confirmed
cartilage
rats
quantitative
reverse
polymerase
chain
reaction
(qRT-PCR)
Western
blotting
(WB)
analyzed
an
independent
t
-test.
Results:
identified
as
DEG
exhibited
highest
diagnostic
value
for
according
ROC
analysis.
GO
KEGG
enrichment
analyses
suggest
that
plays
vital
development
through
processes
including
nitric
oxide
anabolism,
macrophage
proliferation,
immune
response,
PI3K/Akt
MAPK
signaling
pathways.
increased
validated
qRT-PCR
(1.193
±
0.005
vs
1.000
0.005,
p
<
0.001)
WB
(0.981
0.055
0.856
0.026,
=
0.012)
Conclusion:
found
be
related
pathogenesis
can
potentially
serve
therapeutic
target
OA.
underlying
mechanism
pathways,
cells
their
functions
findings
need
clinical
trials
molecular
requires
further
study.
Keywords:
osteoarthritis,
zinc
finger
protein
652,
algorithms,
cell
