Abstract
Glioma
is
the
most
common
malignant
tumor
in
central
nervous
system,
and
its
unique
pathogenesis
often
leads
to
poor
treatment
outcomes
prognosis.
In
2021,
World
Health
Organization
(WHO)
divided
gliomas
into
five
categories
based
on
their
histological
characteristics
molecular
changes.
Non-coding
RNA
a
type
of
that
does
not
encode
proteins
but
can
exert
biological
functions
at
level,
long
non-coding
(lncRNA)
with
length
exceeding
200
nt.
It
controlled
by
various
transcription
factors
plays
an
indispensable
role
regulatory
processes
cells.
Numerous
studies
have
confirmed
dysregulation
lncRNA
critical
pathogenesis,
progression,
malignancy
gliomas.
Therefore,
this
article
reviews
proliferation,
apoptosis,
invasion,
migration,
angiogenesis,
immune
regulation,
glycolysis,
stemness,
drug
resistance
changes
caused
gliomas,
summarizes
potential
clinical
significance
Frontiers in Medicine,
Год журнала:
2025,
Номер
12
Опубликована: Янв. 22, 2025
Parkinson’s
disease
is
a
progressive
neurodegenerative
that
destroys
substantia
nigra
dopaminergic
neurons,
causing
tremors,
bradykinesia,
rigidity,
and
postural
instability.
Current
treatment
approaches
primarily
focus
on
symptom
management,
employing
pharmacological,
non-pharmacological,
surgical
methods.
However,
these
treatments
often
result
in
fluctuating
symptoms,
side
effects,
progression.
Here,
the
authors
have
reviewed
emerging
field
of
nanomedicine
as
promising
path
for
treatment,
emphasizing
its
potential
to
overcome
limitations
traditional
therapies.
Nanomedicine
utilizes
nanoparticles
targeted
drug
delivery,
leveraging
their
small
size
high
surface
area
volume
ratio
cross
blood-brain
barrier
deliver
therapeutic
agents
directly
affected
brain
regions.
Various
nanoparticles,
including
lipid-based,
polymeric,
metallic,
carbon-based,
shown
treatment.
Additionally,
nanocarrier
systems
like
liposomes,
nanogels,
dendrimers,
solid
lipid
offer
controlled
sustained
release
agents,
enhancing
bioavailability
reducing
effects.
This
review
provides
insights
into
pathophysiology
disease,
highlighting
mechanisms
neurodegeneration,
role
alpha-synuclein,
disruption
pathways.
It
further
discusses
application
gene
therapy
conjunction
with
interventions.
CNS Neuroscience & Therapeutics,
Год журнала:
2023,
Номер
30(4)
Опубликована: Окт. 18, 2023
Abstract
Aims
The
dysregulation
of
TGF‐β
signaling
is
a
crucial
pathophysiological
process
in
tumorigenesis
and
progression.
LncRNAs
have
diverse
biological
functions
are
significant
participants
the
regulation
tumor
pathways.
However,
clinical
value
lncRNAs
related
to
glioma
currently
unclear.
Methods
Data
on
glioma's
RNA‐seq
transcriptome,
somatic
mutation,
DNA
methylation
data,
clinicopathological
information
were
derived
from
CGGA
TCGA
databases.
A
prognostic
lncRNA
signature
was
constructed
by
Cox
LASSO
regression
analyses.
TIMER2.0
database
utilized
deduce
immune
infiltration
characteristics.
“ELMER
v.2”
used
reconstruct
TF‐methylation‐gene
regulatory
network.
Immunotherapy
chemotherapy
response
predictions
implemented
TIDE
algorithm
GDSC
database,
respectively.
In
vitro
vivo
experiments
conducted
verify
results
clarify
mechanism
lncRNA.
Results
glioma,
signaling‐related
15‐lncRNA
constructed,
including
AC010173.1,
HOXA‐AS2,
AC074286.1,
AL592424.1,
DRAIC,
HOXC13‐AS,
AC007938.1,
AC010729.1,
AC013472.3,
AC093895.1,
AC131097.4,
AL606970.4,
HOXC‐AS1,
AGAP2‐AS1,
AC002456.1.
This
proved
be
reliable
tool,
with
high
risk
indicating
an
unfavorable
prognosis
being
linked
malignant
genomic
mutation
traits.
Risk
levels
associated
different
landscapes,
where
indicative
macrophage
infiltration.
addition,
also
suggested
better
immunotherapy
response.
cg05987823
important
site
progression,
AP‐1
transcription
factor
family
participated
expression.
AGAP2‐AS1
knockdown
inhibited
proliferation,
migration,
invasion
cells,
as
well
growth
downregulating
expression
NF‐κB
ERK
1/2
pathway.
Conclusions
established
which
can
for
judgment,
status
inference,
prediction.
plays
role
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Янв. 25, 2025
Diabetes
is
a
growing
health
concern
in
developing
countries,
causing
considerable
mortality
rates.
While
machine
learning
(ML)
approaches
have
been
widely
used
to
improve
early
detection
and
treatment,
several
studies
shown
low
classification
accuracies
due
overfitting,
underfitting,
data
noise.
This
research
employs
parallel
sequential
ensemble
ML
paired
with
feature
selection
techniques
boost
accuracy.
The
Pima
India
Data
from
the
UCI
Repository
served
as
dataset.
preprocessing
included
cleaning
dataset
by
replacing
missing
values
column
means
selecting
highly
correlated
features
using
forward
backward
methods.
was
split
into
two
parts:
training
(70%),
testing
(30%).
Python
for
Jupyter
Notebook,
there
were
design
phases.
first
phase
utilized
J48,
Classification
Regression
Tree
(CART),
Decision
Stump
(DS)
create
random
forest
model.
second
employed
same
algorithms
alongside
methods—XG
Boost,
AdaBoostM1,
Gradient
Boosting—using
an
average
voting
algorithm
binary
classification.
Evaluation
revealed
that
XG
Boosting
achieved
of
100%,
performance
metrics
including
F1
score,
MCC,
Precision,
Recall,
AUC-ROC,
AUC-PR
all
equal
1.00,
indicating
reliable
predictions
diabetes
presence.
Researchers
practitioners
can
leverage
predictive
model
developed
this
work
make
quick
mellitus,
which
could
save
many
lives.
