Targeted and spatial metabolomics unveil how brassinolide enhances polyphenol and proline metabolism in cold-stressed jujube fruit
Chenyu Niu,
No information about this author
Ting Guo,
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Wenhui Xu
No information about this author
et al.
Postharvest Biology and Technology,
Journal Year:
2025,
Volume and Issue:
222, P. 113386 - 113386
Published: Jan. 7, 2025
Language: Английский
Overview: Spatial Metabolomics Review Series
Seminars in Nephrology,
Journal Year:
2025,
Volume and Issue:
unknown, P. 151576 - 151576
Published: April 1, 2025
Language: Английский
Challenges in Spatial Metabolomics and Proteomics for Functional Tissue Unit and Single-Cell Resolution
Kevin Zemaitis,
No information about this author
Ljiljana Paša‐Tolić
No information about this author
Seminars in Nephrology,
Journal Year:
2025,
Volume and Issue:
unknown, P. 151583 - 151583
Published: April 1, 2025
Language: Английский
Untargeted metabolomics HRMS data processing using regions of interest and multivariate curve resolution approaches to unveil health-to-disease transition
Microchemical Journal,
Journal Year:
2025,
Volume and Issue:
unknown, P. 113737 - 113737
Published: April 1, 2025
Language: Английский
Emerging Biomarkers and Advanced Diagnostics in Chronic Kidney Disease: Early Detection Through Multi-Omics and AI
Diagnostics,
Journal Year:
2025,
Volume and Issue:
15(10), P. 1225 - 1225
Published: May 13, 2025
Chronic
kidney
disease
(CKD)
remains
a
significant
global
health
burden,
often
diagnosed
at
advanced
stages
due
to
the
limitations
of
traditional
biomarkers
such
as
serum
creatinine
and
estimated
glomerular
filtration
rate
(eGFR).
This
review
aims
critically
evaluate
recent
advancements
in
novel
biomarkers,
multi-omics
technologies,
artificial
intelligence
(AI)-driven
diagnostic
strategies,
specifically
addressing
existing
gaps
early
CKD
detection
personalized
patient
management.
We
explore
key
diagnostics,
focusing
on
emerging
biomarkers—including
neutrophil
gelatinase-associated
lipocalin
(NGAL),
injury
molecule-1
(KIM-1),
soluble
urokinase
plasminogen
activator
receptor
(suPAR),
cystatin
C—and
their
clinical
applications.
Additionally,
approaches
integrating
genomics,
proteomics,
metabolomics,
transcriptomics
are
reshaping
classification
prognosis.
Artificial
predictive
models
further
enhance
accuracy,
enabling
real-time
risk
assessment
treatment
optimization.
Despite
these
innovations,
challenges
remain
biomarker
standardization,
large-scale
validation,
integration
into
practice.
Future
research
should
focus
refining
multi-biomarker
panels,
improving
assay
facilitating
adoption
precision-driven
diagnostics.
By
leveraging
advancements,
diagnostics
can
transition
toward
earlier
intervention,
individualized
therapy,
improved
outcomes.
Language: Английский
Decoding Kidney Pathophysiology: Omics-Driven Approaches in Precision Medicine
Journal of Personalized Medicine,
Journal Year:
2024,
Volume and Issue:
14(12), P. 1157 - 1157
Published: Dec. 19, 2024
Chronic
kidney
disease
(CKD)
is
a
major
worldwide
health
concern
because
of
its
progressive
nature
and
complex
biology.
Traditional
diagnostic
therapeutic
approaches
usually
fail
to
account
for
heterogeneity,
resulting
in
low
efficacy.
Precision
medicine
offers
novel
approach
studying
by
combining
omics
technologies
such
as
genomics,
transcriptomics,
proteomics,
metabolomics,
epigenomics.
By
identifying
discrete
subtypes,
molecular
biomarkers,
targets,
these
pave
the
way
personalized
treatment
approaches.
Multi-omics
integration
has
enhanced
our
understanding
CKD
revealing
intricate
linkages
pathways
that
contribute
resistance
progression.
While
pharmacogenomics
insights
into
expected
responses
treatments,
single-cell
spatial
transcriptomics
can
be
utilized
investigate
biological
heterogeneity.
Despite
significant
development,
challenges
persist,
including
data
concerns,
high
costs,
ethical
quandaries.
Standardized
protocols,
collaborative
data-sharing
frameworks,
advanced
computational
tools
machine
learning
causal
inference
models
are
required
address
challenges.
With
advancement
technology,
nephrology
may
benefit
from
improved
accuracy,
risk
assessment,
care.
overcoming
barriers,
precision
potential
develop
techniques
improving
patient
outcomes
treatment.
Language: Английский
Omics Studies in CKD: Diagnostic Opportunities and Therapeutic Potential
PROTEOMICS,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Nov. 11, 2024
Omics
technologies
have
significantly
advanced
the
prediction
and
therapeutic
approaches
for
chronic
kidney
disease
(CKD)
by
providing
comprehensive
molecular
insights.
This
is
a
review
of
current
state
future
prospects
integrating
biomarkers
into
clinical
practice
CKD,
aiming
to
improve
patient
outcomes
targeted
interventions.
In
fact,
integration
genomic,
transcriptomic,
proteomic,
metabolomic
data
has
enhanced
our
understanding
CKD
pathogenesis
identified
novel
an
early
diagnosis
treatment.
Advanced
computational
methods
artificial
intelligence
(AI)
further
refined
multi-omics
analysis,
leading
more
accurate
models
progression
responses.
These
developments
highlight
potential
care
with
precise
individualized
treatment
plan
.
Language: Английский