Micromachines,
Год журнала:
2025,
Номер
16(3), С. 243 - 243
Опубликована: Фев. 20, 2025
Polymerase
chain
reaction
(PCR)
chips
are
advanced,
microfluidic
platforms
that
have
revolutionized
biomarker
discovery
and
validation
because
of
their
high
sensitivity,
specificity,
throughput
levels.
These
miniaturize
traditional
PCR
processes
for
the
speed
precision
nucleic
acid
detection
relevant
to
advancing
drug
development.
Biomarkers,
which
useful
in
helping
explain
disease
mechanisms,
patient
stratification,
therapeutic
monitoring,
hard
identify
validate
due
complexity
biological
systems
limitations
techniques.
The
challenges
respond
include
high-throughput
capabilities
coupled
with
real-time
quantitative
analysis,
enabling
researchers
novel
biomarkers
greater
accuracy
reproducibility.
More
recent
design
improvements
further
expanded
functionality
also
digital
multiplex
technologies.
Digital
ideal
quantifying
rare
biomarkers,
is
essential
oncology
infectious
research.
In
contrast,
enable
simultaneous
analysis
multiple
targets,
therefore
simplifying
validation.
Furthermore,
single-cell
made
it
possible
detect
at
unprecedented
resolution,
hence
revealing
heterogeneity
within
cell
populations.
transforming
development,
target
identification,
efficacy
assessment.
They
play
a
major
role
development
companion
diagnostics
and,
therefore,
pave
way
personalized
medicine,
ensuring
right
receives
treatment.
While
this
tremendously
promising
technology
has
exhibited
many
regarding
its
scalability,
integration
other
omics
technologies,
conformity
regulatory
requirements,
still
prevail.
Future
breakthroughs
chip
manufacturing,
artificial
intelligence,
multi-omics
applications
will
expand
capabilities.
not
only
be
important
acceleration
but
raising
bar
improving
outcomes
hence,
global
health
care
as
these
technologies
continue
mature.
Nature Communications,
Год журнала:
2024,
Номер
15(1)
Опубликована: Июль 16, 2024
DNA
methylation
(DNAm)
is
one
of
the
most
reliable
biomarkers
aging
across
mammalian
tissues.
While
age-dependent
global
loss
DNAm
has
been
well
characterized,
gain
less
characterized.
Studies
have
demonstrated
that
CpGs
which
with
age
are
enriched
in
Polycomb
Repressive
Complex
2
(PRC2)
targets.
However,
whole-genome
examination
all
PRC2
targets
as
determination
pan-tissue
or
tissue-specific
nature
these
associations
lacking.
Here,
we
show
low-methylated
regions
(LMRs)
highly
bound
by
embryonic
stem
cells
(PRC2
LMRs)
examined
somatic
mitotic
cells.
We
estimated
this
epigenetic
change
represents
around
90%
genome-wide.
Therefore,
propose
"PRC2-AgeIndex,"
defined
average
LMRs,
a
universal
biomarker
cellular
can
distinguish
effect
different
anti-aging
interventions.
Abstract
While
observational
studies
and
small
pilot
trials
suggest
that
vitamin
D,
omega-3
exercise
may
slow
biological
aging,
larger
clinical
testing
these
treatments
individually
or
in
combination
are
lacking.
Here,
we
report
the
results
of
a
post
hoc
analysis
among
777
participants
DO-HEALTH
trial
on
effect
D
(2,000
IU
per
day)
and/or
(1
g
home
program
four
next-generation
DNA
methylation
(DNAm)
measures
aging
(PhenoAge,
GrimAge,
GrimAge2
DunedinPACE)
over
3
years.
Omega-3
alone
slowed
DNAm
clocks
PhenoAge,
DunedinPACE,
all
three
had
additive
benefits
PhenoAge.
Overall,
from
baseline
to
year
3,
standardized
effects
ranged
0.16
0.32
units
(2.9–3.8
months).
In
summary,
our
indicates
protective
treatment
slowing
years
across
several
clocks,
with
an
omega-3,
based
Abstract
Beyond
mere
prognostication,
optimal
biomarkers
of
aging
provide
insights
into
qualitative
and
quantitative
features
biological
might,
therefore,
offer
useful
information
for
the
testing
and,
ultimately,
clinical
use
gerotherapeutics.
We
aimed
to
develop
a
proteomic
clock
(PAC)
all‐cause
mortality
risk
as
proxy
age.
Data
were
from
UK
Biobank
Pharma
Proteomics
Project,
including
53,021
participants
aged
between
39
70
years
2923
plasma
proteins
assessed
using
Olink
Explore
3072
assay®.
10.9%
died
during
mean
follow‐up
13.3
years,
with
age
at
death
70.1
years.
The
Spearman
correlation
PAC
chronological
was
0.77.
showed
robust
age‐adjusted
associations
predictions
onset
various
diseases
in
general
disease‐free
participants.
associated
deviation
enriched
several
processes
related
hallmarks
aging.
Our
results
expand
previous
findings
by
showing
that
acceleration,
based
on
PAC,
strongly
predicts
incident
disease
outcomes.
Particularly,
it
facilitates
evaluation
multiple
conditions
population,
thereby,
contributing
prevention
initial
diseases,
which
vary
among
individuals
may
subsequently
lead
additional
comorbidities.
Abstract
Aging
is
a
complex
biological
process
influenced
by
various
factors,
including
genetic
and
environmental
influences.
In
this
study,
we
present
BayesAge
2.0,
an
upgraded
version
of
our
maximum
likelihood
algorithm
designed
for
predicting
transcriptomic
age
(tAge)
from
RNA-seq
data.
Building
on
the
original
framework,
which
was
developed
epigenetic
prediction,
2.0
integrates
Poisson
distribution
to
model
count-based
gene
expression
data
employs
LOWESS
smoothing
capture
nonlinear
gene-age
relationships.
provides
significant
improvements
over
traditional
linear
models,
such
as
Elastic
Net
regression.
Specifically,
it
addresses
issues
bias
in
predictions,
with
minimal
age-associated
observed
residuals.
Its
computational
efficiency
further
distinguishes
reference
construction
cross-validation
are
completed
more
quickly
compared
regression,
requires
extensive
hyperparameter
tuning.
Overall,
represents
step
forward
tAge
offering
robust,
accurate,
efficient
tool
aging
research
biomarker
development.
With
the
global
population
aging
at
an
unprecedented
rate,
there
is
a
need
to
extend
healthy
productive
life
span.
This
review
examines
how
Deep
Learning
(DL)
and
Generative
Artificial
Intelligence
(GenAI)
are
used
in
biomarker
discovery,
deep
clock
development,
geroprotector
identification
generation
of
dual-purpose
therapeutics
targeting
disease.
The
paper
explores
emergence
multimodal,
multitasking
research
systems
highlighting
promising
future
directions
for
GenAI
human
animal
research,
as
well
clinical
application
longevity
medicine.
Previous
research
on
sleep
and
aging
largely
has
failed
to
illustrate
the
optimal
dose-response
curve
of
this
relationship.
We
aimed
analyze
associations
between
duration
measures
predicted
age.
In
total,
241,713
participants
from
UK
Biobank
were
included.
Habitual
was
collected
baseline
questionnaire.
Four
indicators,
homeostatic
dysregulation
(HD),
phenoAge
(PA),
Klemera-Doubal
method
(KDM),
allostatic
load
(AL),
chosen
assess
Multivariate
linear
regression
models
utilized.
The
association
age
followed
a
U-shape
(All
p
for
nonlinear
<0.05).
Compared
with
individuals
who
7
h/day,
multivariable-adjusted
beta
≤5
≥9
h/day
0.05
(95%
CI
0.03,
0.07)
0.03
0.02,
0.05)
HD,
0.08
0.01,
0.14)
0.36
0.31,
0.41)
PA,
0.21
0.12,
0.30)
0.30
0.23,
0.37)
KDM.
Significant
independent
joint
effects
cystatin
C
(CysC)
gamma
glutamyltransferase
(GGT)
metrics
future
found.
Similar
results
observed
when
conducting
stratification
analyses.
Short
long
associated
accelerated
mediated
by
CysC
GGT.
