Biosensors,
Год журнала:
2024,
Номер
14(6), С. 295 - 295
Опубликована: Июнь 5, 2024
Development
and
optimisation
of
bioelectronic
monitoring
techniques
like
microelectrode
array-based
field
potential
measurement
impedance
spectroscopy
for
the
functional,
label-free
non-invasive
in
vitro
neuronal
networks
is
widely
investigated
biosensors.
Thus,
these
were
individually
used
to
demonstrate
capabilities
of,
e.g.,
detecting
compound-induced
toxicity
culture
models.
In
contrast,
extended
application
investigating
effects
central
nervous
system
infecting
viruses
are
rarely
described.
this
context,
we
wanted
analyse
effect
herpesviruses
on
functional
networks.
Therefore,
developed
a
unique
hybrid
platform
that
allows
performing
same
microelectrode.
first
step,
model
based
primary
hippocampal
cells
from
neonatal
rats
was
established
with
reproducible
stable
synchronised
electrophysiological
network
activity
after
21
days
cultivation
arrays.
For
proof
concept,
pseudorabies
virus
PrV
Kaplan-ΔgG-GFP
applied
monitored
by
72
h
multiparametric
mode.
Analysis
several
parameters
revealed
concentration-dependent
degeneration
within
24–48
h,
significant
early
change
activity,
subsequently
leading
loss
synchronicity.
conclusion,
successfully
quantitative
pathologic
herpesvirus
active
ECS Sensors Plus,
Год журнала:
2024,
Номер
3(1), С. 011601 - 011601
Опубликована: Март 1, 2024
There
is
a
plethora
of
electrochemical
biosensors
developed
for
ultrasensitive
detection
clinically
relevant
biomarkers.
However,
many
these
systems
lose
their
performance
in
heterogeneous
clinical
samples
and
are
too
complex
to
be
operated
by
end
users
at
the
point-of-care
(POC),
prohibiting
commercial
success.
Integration
with
sample
processing
technology
addresses
both
challenges;
however,
it
adds
manufacturing
complexity
overall
cost
systems.
Herein,
we
review
different
components
biosensor
avenues
creating
fully
integrated
In
context
integration,
focus
on
discussing
trade-offs
between
sensing
performance,
cost,
scalable
guide
readers
toward
designing
new
commercialization
potential.
Journal of Clinical Medicine,
Год журнала:
2025,
Номер
14(2), С. 550 - 550
Опубликована: Янв. 16, 2025
The
convergence
of
Artificial
Intelligence
(AI)
and
neuroscience
is
redefining
our
understanding
the
brain,
unlocking
new
possibilities
in
research,
diagnosis,
therapy.
This
review
explores
how
AI’s
cutting-edge
algorithms—ranging
from
deep
learning
to
neuromorphic
computing—are
revolutionizing
by
enabling
analysis
complex
neural
datasets,
neuroimaging
electrophysiology
genomic
profiling.
These
advancements
are
transforming
early
detection
neurological
disorders,
enhancing
brain–computer
interfaces,
driving
personalized
medicine,
paving
way
for
more
precise
adaptive
treatments.
Beyond
applications,
itself
has
inspired
AI
innovations,
with
architectures
brain-like
processes
shaping
advances
algorithms
explainable
models.
bidirectional
exchange
fueled
breakthroughs
such
as
dynamic
connectivity
mapping,
real-time
decoding,
closed-loop
systems
that
adaptively
respond
states.
However,
challenges
persist,
including
issues
data
integration,
ethical
considerations,
“black-box”
nature
many
systems,
underscoring
need
transparent,
equitable,
interdisciplinary
approaches.
By
synthesizing
latest
identifying
future
opportunities,
this
charts
a
path
forward
integration
neuroscience.
From
harnessing
multimodal
cognitive
augmentation,
fusion
these
fields
not
just
brain
science,
it
reimagining
human
potential.
partnership
promises
where
mysteries
unlocked,
offering
unprecedented
healthcare,
technology,
beyond.
Individual
choices
shape
life
course
trajectories
of
brain
structure
and
function
beyond
genes
environment.
We
hypothesized
that
individual
task
engagement
in
response
to
a
learning
program
results
individualized
biographies
connectomics.
Genetically
identical
female
mice
living
one
large
shared
enclosure
freely
engaged
self-paced,
automatically
administered
monitored
tasks.
discovered
growing
increasingly
stable
interindividual
differences
trajectories.
Adult
hippocampal
neurogenesis
connectivity
as
assessed
by
high-density
multielectrode
array
positively
correlated
with
the
variation
exploration
efficiency.
During
some
tasks,
divergence
transiently
collapsed,
highlighting
sustained
significance
context
for
individualization.
Thus,
equal
environments
do
not
result
because
confronts
individuals
lead
divergent
paths.
Biosensors and Bioelectronics,
Год журнала:
2024,
Номер
252, С. 116120 - 116120
Опубликована: Фев. 14, 2024
In
recent
decades,
significant
progress
has
been
made
in
the
treatment
of
heart
diseases,
particularly
field
personalized
medicine.
Despite
development
genetic
tests,
phenotyping
and
risk
stratification
are
performed
based
on
clinical
findings
invasive
vivo
techniques,
such
as
stimulation
conduction
mapping
techniques
programmed
ventricular
pacing.
Consequently,
label-free
non-invasive
vitro
functional
analysis
systems
urgently
needed
for
more
accurate
effective
stratification,
model-based
therapy
planning,
safety
profile
evaluation
drugs.
To
overcome
these
limitations,
a
novel
multilayer
high-density
microelectrode
array
(HD-MEA),
with
an
optimized
configuration
512
sensing
4
pacing
electrodes
sensor
area
100
mm2,
was
developed
bioelectronic
detection
re-entry
arrhythmia
patterns.
Together
co-developed
front-end,
we
monitored
parallel
cardiac
electrophysiology
potential
monitoring
mechanical
contraction
using
impedance
spectroscopy
at
same
microelectrode.
proof
principle
experiments,
human
induced
pluripotent
stem
cell-derived
cardiomyocytes
were
cultured
HD-MEAs
used
to
demonstrate
sensitive
quantification
strength
modulation
by
cardioactive
drugs
blebbistatin
(IC50
=
4.2
μM),
omecamtiv
levosimendan.
Strikingly,
arrhythmia-typical
rotor
patterns
(re-entry)
can
be
electrical
sequences
detected
high
spatial
resolution.
Therefore,
provide
system
promising
reference
point
diagnostic
approaches
assays
patient-specific
hiPS-derived
cardiomyocytes.
Journal of Visualized Experiments,
Год журнала:
2024,
Номер
205
Опубликована: Март 8, 2024
Large-scale
neuronal
networks
and
their
complex
distributed
microcircuits
are
essential
to
generate
perception,
cognition,
behavior
that
emerge
from
patterns
of
spatiotemporal
activity.
These
dynamic
emerging
functional
groups
interconnected
ensembles
facilitate
precise
computations
for
processing
coding
multiscale
neural
information,
thereby
driving
higher
brain
functions.
To
probe
the
computational
principles
dynamics
underlying
this
complexity
investigate
impact
biological
processes
in
health
disease,
large-scale
simultaneous
recordings
have
become
instrumental.
Here,
a
high-density
microelectrode
array
(HD-MEA)
is
employed
study
two
modalities
-
hippocampal
olfactory
bulb
circuits
ex-vivo
mouse
slices
in-vitro
cell
cultures
human
induced
pluripotent
stem
cells
(iPSCs).
The
HD-MEA
platform,
with
4096
microelectrodes,
enables
non-invasive,
multi-site,
label-free
extracellular
firing
thousands
simultaneously
at
high
resolution.
This
approach
allows
characterization
several
electrophysiological
network-wide
features,
including
single/-multi-unit
spiking
activity
local
field
potential
oscillations.
scrutinize
these
multidimensional
data,
we
developed
tools
incorporating
machine
learning
algorithms,
automatic
event
detection
classification,
graph
theory,
other
advanced
analyses.
By
supplementing
pipelines
provide
methodology
studying
large,
multiscale,
multimodal
assemblies
networks.
can
potentially
advance
our
understanding
functions
cognitive
disease.
Commitment
open
science
insights
into
could
enhance
brain-inspired
modeling,
neuromorphic
computing,
algorithms.
Furthermore,
mechanisms
impaired
microcircuit
lead
identification
specific
biomarkers,
paving
way
more
accurate
diagnostic
targeted
therapies
neurological
disorders.
Frontiers in Bioengineering and Biotechnology,
Год журнала:
2024,
Номер
12
Опубликована: Сен. 4, 2024
Large-scale
multimodal
neural
recordings
on
high-density
biosensing
microelectrode
arrays
(HD-MEAs)
offer
unprecedented
insights
into
the
dynamic
interactions
and
connectivity
across
various
brain
networks.
However,
fidelity
of
these
is
frequently
compromised
by
pervasive
noise,
which
obscures
meaningful
information
complicates
data
analysis.
To
address
this
challenge,
we
introduce
DENOISING,
a
versatile
data-derived
computational
engine
engineered
to
adjust
thresholds
adaptively
based
large-scale
extracellular
signal
characteristics
noise
levels.
This
facilitates
separation
components
without
reliance
specific
transformations.
Uniquely
capable
handling
diverse
array
types
(electrical,
mechanical,
environmental)
multidimensional
signals,
including
stationary
non-stationary
oscillatory
local
field
potential
(LFP)
spiking
activity,
DENOISING
presents
an
adaptable
solution
applicable
different
recording
modalities
Applying
from
mice
hippocampal
olfactory
bulb
networks
yielded
enhanced
signal-to-noise
ratio
(SNR)
LFP
spike
firing
patterns
compared
those
computed
raw
data.
Comparative
analysis
with
existing
state-of-the-art
denoising
methods,
employing
SNR
root
mean
square
(RMS),
underscores
DENOISING's
performance
in
improving
quality
reliability.
Through
experimental
approaches,
validate
that
improves
clarity
interpretation
effectively
mitigating
independent
spatiotemporally
structured
datasets,
thus
unlocking
new
dimensions
understanding
functional
dynamics.
Large-scale
neuronal
networks
and
their
complex
distributed
microcircuits
are
essential
to
generate
perception,
cognition,
behavior
that
emerge
from
patterns
of
spatiotemporal
activity.
These
dynamic
emerging
functional
groups
interconnected
ensembles
facilitate
precise
computations
for
processing
coding
multiscale
neural
information,
thereby
driving
higher
brain
functions.
To
probe
the
computational
principles
dynamics
underlying
this
complexity
investigate
impact
biological
processes
in
health
disease,
large-scale
simultaneous
recordings
have
become
instrumental.
Here,
a
high-density
microelectrode
array
(HD-MEA)
is
employed
study
two
modalities
-
hippocampal
olfactory
bulb
circuits
ex-vivo
mouse
slices
in-vitro
cell
cultures
human
induced
pluripotent
stem
cells
(iPSCs).
The
HD-MEA
platform,
with
4096
microelectrodes,
enables
non-invasive,
multi-site,
label-free
extracellular
firing
thousands
simultaneously
at
high
resolution.
This
approach
allows
characterization
several
electrophysiological
network-wide
features,
including
single/-multi-unit
spiking
activity
local
field
potential
oscillations.
scrutinize
these
multidimensional
data,
we
developed
tools
incorporating
machine
learning
algorithms,
automatic
event
detection
classification,
graph
theory,
other
advanced
analyses.
By
supplementing
pipelines
provide
methodology
studying
large,
multiscale,
multimodal
assemblies
networks.
can
potentially
advance
our
understanding
functions
cognitive
disease.
Commitment
open
science
insights
into
could
enhance
brain-inspired
modeling,
neuromorphic
computing,
algorithms.
Furthermore,
mechanisms
impaired
microcircuit
lead
identification
specific
biomarkers,
paving
way
more
accurate
diagnostic
targeted
therapies
neurological
disorders.
Frontiers in Bioengineering and Biotechnology,
Год журнала:
2024,
Номер
12
Опубликована: Май 13, 2024
With
cancer
as
one
of
the
leading
causes
death
worldwide,
there
is
a
need
for
development
accurate,
cost-effective,
easy-to-use,
and
fast
drug-testing
assays.
While
NCI
60
cell-line
screening
gold
standard
based
on
colorimetric
assay,
monitoring
cells
electrically
constitutes
label-free
non-invasive
tool
to
assess
cytotoxic
effects
chemotherapeutic
treatment
cells.
For
decades,
impedance-based
cellular
assays
extensively
investigated
various
cell
characteristics
affected
by
drug
but
lack
spatiotemporal
resolution.
progress
in
microelectrode
fabrication,
high-density
Complementary
Metal
Oxide
Semiconductor
(CMOS)-based
arrays
(MEAs)
with
subcellular
resolution
time-continuous
recording
capability
emerged
potent
alternative.
In
this
article,
we
present
new
adhesion
noise
(CAN)-based
electrical
imaging
technique
expand
CMOS
MEA
cell-biology
applications:
CAN
spectroscopy
enables
quantification
single-cell
spatial
The
agent
5-Fluorouracil
exerts
effect
colorectal
(CRC)
hampering
proliferation
lowering
viability.
proof-of-concept,
found
sufficient
accuracy
reproducibility
compared
commercially
available
biological
assay.
This
label-free,
non-invasive,
complements
standardized
methods
significant
advances
over
established
approaches.