Revisiting the advance of age-dependent α-synuclein propagation and aggregation
Ageing and Neurodegenerative Diseases,
Год журнала:
2025,
Номер
5(1)
Опубликована: Фев. 22, 2025
Aging
is
a
major
risk
factor
for
different
neurodegenerative
diseases
(NDDs),
including
Parkinson’s
disease
(PD).
In
PD,
one
of
the
key
neuropathological
features
cytoplasmic
protein
aggregation,
named
Lewy
bodies
(LBs)
in
cell
body,
and
neurites
(LNs)
neuronal
processes
terminals.
The
α-synuclein
(α-syn)
has
been
found
to
be
component
LBs
LNs,
considered
play
central
role
their
formation.
α-Syn
also
increases
healthy
aging
conditions.
Evidence
shown
that
promotes
α-syn
pathological
aggregation
propagation
and,
therefore,
may
induce
aggravate
PD
pathogenesis.
Here,
we
aim
highlight
recent
advances
age-related
prion-like
discuss
subsequent
consequences
functions.
Язык: Английский
Role and Potential of Artificial Intelligence in Biomarker Discovery and Development of Treatment Strategies for Amyotrophic Lateral Sclerosis
International Journal of Molecular Sciences,
Год журнала:
2025,
Номер
26(9), С. 4346 - 4346
Опубликована: Май 2, 2025
Neurodegenerative
diseases,
including
amyotrophic
lateral
sclerosis
(ALS),
present
significant
challenges
owing
to
their
complex
pathologies
and
a
lack
of
curative
treatments.
Early
detection
reliable
biomarkers
are
critical
but
remain
elusive.
Artificial
intelligence
(AI)
has
emerged
as
transformative
tool,
enabling
advancements
in
biomarker
discovery,
diagnostic
accuracy,
therapeutic
development.
From
optimizing
clinical-trial
designs
leveraging
omics
neuroimaging
data,
AI
facilitates
understanding
disease
treatment
innovation.
Notably,
technologies
such
AlphaFold
deep
learning
models
have
revolutionized
proteomics
neuroimaging,
offering
unprecedented
insights
into
ALS
pathophysiology.
This
review
highlights
the
intersection
ALS,
exploring
current
state
progress
future
prospects.
Язык: Английский
Multiplexed Data-Independent Acquisition (mDIA) to Profile Extracellular Vesicle Proteomes
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2025,
Номер
unknown
Опубликована: Май 15, 2025
Extracellular
vesicles
(EVs)
have
gained
increasing
attention
with
their
intriguing
biological
functions
and
molecular
cargoes
serving
as
potential
biomarkers
for
various
diseases,
including
cancers.
A
relatively
lower
abundance
of
EV
proteins
compared
to
cellular
counterparts
necessitates
sensitive
accurate
quantitative
proteomic
strategies.
Multiplexed
proteomics
combined
data-independent
acquisition
(mDIA)
has
shown
promise
improving
sensitivity
quantification
over
traditional
DDA
label-free
methods.
Despite
this,
mDIA
pipelines
that
utilize
types
spectral
libraries
search
software
suites
not
been
thoroughly
evaluated
proteome
samples.
In
this
study,
we
aim
establish
a
robust
pipeline
based
on
dimethyl
labeling
EVs.
EVs
were
isolated
using
the
extracellular
vesicle
total
recovery
purification
(EVtrap)
technique
processed
directly
through
an
on-bead
one-pot
sample
preparation
workflow
obtain
digested
peptides.
We
different
pipelines,
library-free
library-based
DIA
timsTOF
HT
platform.
Results
showed
DIA,
project-specific
generated
from
StageTip-based
fractionation,
outperformed
other
in
protein
identification
quantification.
demonstrated
first
time
landscape
changes
caused
by
IDH1
mutation
inhibitor
treatment
intrahepatic
cholangiocarcinoma,
highlighting
utility
EV-based
biomarker
discovery.
Язык: Английский