Nutrients,
Journal Year:
2024,
Volume and Issue:
17(1), P. 42 - 42
Published: Dec. 27, 2024
Biomarkers
constitute
a
valuable
tool
to
diagnose
both
the
incidence
and
prevalence
of
chronic
diseases
may
help
inform
design
effectiveness
precision
nutrition
interventions.
Cardiovascular
disease
(CVD)
continues
be
foremost
cause
death
all
over
world.
While
reasons
that
lead
increased
risk
for
CVD
are
multifactorial,
dyslipidemias,
plasma
concentrations
specific
lipoproteins,
dynamic
measures
lipoprotein
function
strong
biomarkers
predict
document
coronary
heart
incidence.
The
aim
this
review
is
provide
comprehensive
evaluation
emerging
approaches
can
utilized
characterize
profiles
as
predictive
tools
assessing
risk,
including
assessment
traditional
clinical
lipid
panels,
efflux
capacity
inflammatory
antioxidant
activity,
omics-based
characterization
composition
regulators
metabolism.
In
addition,
we
discuss
demographic,
genetic,
metagenomic,
lifestyle
determinants
profiles—such
age,
sex,
gene
variants
single-nucleotide
polymorphisms,
gut
microbiome
profiles,
dietary
patterns,
physical
inactivity,
obesity
status,
smoking
alcohol
intake,
stress—which
likely
essential
factors
explain
interindividual
responses
recommendations
mitigate
risk.
Biomedicines,
Journal Year:
2024,
Volume and Issue:
12(10), P. 2389 - 2389
Published: Oct. 18, 2024
Osteoporosis
(OP)
is
a
prevalent
skeletal
disorder
characterized
by
decreased
bone
mineral
density
(BMD)
and
increased
fracture
risk.
The
advancements
in
omics
technologies—genomics,
transcriptomics,
proteomics,
metabolomics—have
provided
significant
insights
into
the
molecular
mechanisms
driving
OP.
These
technologies
offer
critical
perspectives
on
genetic
predispositions,
gene
expression
regulation,
protein
signatures,
metabolic
alterations,
enabling
identification
of
novel
biomarkers
for
diagnosis
therapeutic
targets.
This
review
underscores
potential
these
multi-omics
approaches
to
bridge
gap
between
basic
research
clinical
applications,
paving
way
precision
medicine
OP
management.
By
integrating
technologies,
researchers
can
contribute
improved
diagnostics,
preventative
strategies,
treatments
patients
suffering
from
related
conditions.
Cancer Letters,
Journal Year:
2024,
Volume and Issue:
unknown, P. 217350 - 217350
Published: Nov. 1, 2024
Pancreatic
cancer
remains
one
of
the
most
challenging
malignancies
to
treat
due
its
late-stage
diagnosis,
aggressive
progression,
and
high
resistance
existing
therapies.
This
review
examines
latest
advancements
in
early
detection,
therapeutic
strategies,
with
a
focus
on
emerging
biomarkers,
tumor
microenvironment
(TME)
modulation,
integration
artificial
intelligence
(AI)
data
analysis.
We
highlight
promising
including
microRNAs
(miRNAs)
circulating
DNA
(ctDNA),
that
offer
enhanced
sensitivity
specificity
for
early-stage
diagnosis
when
combined
multi-omics
panels.
A
detailed
analysis
TME
reveals
how
components
such
as
cancer-associated
fibroblasts
(CAFs),
immune
cells,
extracellular
matrix
(ECM)
contribute
therapy
by
creating
immunosuppressive
barriers.
also
discuss
interventions
target
these
components,
aiming
improve
drug
delivery
overcome
evasion.
Furthermore,
AI-driven
analyses
are
explored
their
potential
interpret
complex
data,
enabling
personalized
treatment
strategies
real-time
monitoring
response.
conclude
identifying
key
areas
future
research,
clinical
validation
regulatory
frameworks
AI
applications,
equitable
access
innovative
comprehensive
approach
underscores
need
integrated,
outcomes
pancreatic
cancer.
Toxics,
Journal Year:
2024,
Volume and Issue:
12(11), P. 822 - 822
Published: Nov. 16, 2024
It
is
imperative
to
comprehend
the
mechanisms
that
underlie
drug
toxicity
in
order
enhance
efficacy
and
safety
of
novel
therapeutic
agents.
The
capacity
identify
molecular
pathways
contribute
drug-induced
has
been
significantly
enhanced
by
recent
developments
omics
technologies,
such
as
transcriptomics,
proteomics,
metabolomics.
This
enabled
early
identification
potential
adverse
effects.
These
insights
are
further
computational
tools,
including
quantitative
structure-activity
relationship
(QSAR)
analyses
machine
learning
models,
which
accurately
predict
endpoints.
Additionally,
technologies
physiologically
based
pharmacokinetic
(PBPK)
modeling
micro-physiological
systems
(MPS)
provide
more
precise
preclinical-to-clinical
translation,
thereby
improving
assessments.
review
emphasizes
synergy
between
sophisticated
screening
silico
modeling,
data,
emphasizing
their
roles
reducing
late-stage
development
failures.
Challenges
persist
integration
a
variety
data
types
interpretation
intricate
biological
interactions,
despite
progress
made.
standardized
methodologies
predictive
toxicology
contingent
upon
ongoing
collaboration
researchers,
clinicians,
regulatory
bodies.
ensures
pharmaceuticals
effective
safer.
Nutrients,
Journal Year:
2024,
Volume and Issue:
17(1), P. 42 - 42
Published: Dec. 27, 2024
Biomarkers
constitute
a
valuable
tool
to
diagnose
both
the
incidence
and
prevalence
of
chronic
diseases
may
help
inform
design
effectiveness
precision
nutrition
interventions.
Cardiovascular
disease
(CVD)
continues
be
foremost
cause
death
all
over
world.
While
reasons
that
lead
increased
risk
for
CVD
are
multifactorial,
dyslipidemias,
plasma
concentrations
specific
lipoproteins,
dynamic
measures
lipoprotein
function
strong
biomarkers
predict
document
coronary
heart
incidence.
The
aim
this
review
is
provide
comprehensive
evaluation
emerging
approaches
can
utilized
characterize
profiles
as
predictive
tools
assessing
risk,
including
assessment
traditional
clinical
lipid
panels,
efflux
capacity
inflammatory
antioxidant
activity,
omics-based
characterization
composition
regulators
metabolism.
In
addition,
we
discuss
demographic,
genetic,
metagenomic,
lifestyle
determinants
profiles—such
age,
sex,
gene
variants
single-nucleotide
polymorphisms,
gut
microbiome
profiles,
dietary
patterns,
physical
inactivity,
obesity
status,
smoking
alcohol
intake,
stress—which
likely
essential
factors
explain
interindividual
responses
recommendations
mitigate
risk.
