Automated detection of c-Fos-expressing neurons using inhomogeneous background subtraction in fluorescent images
Neurobiology of Learning and Memory,
Год журнала:
2025,
Номер
218, С. 108035 - 108035
Опубликована: Фев. 20, 2025
Язык: Английский
Single-cell transcriptional dynamics in a living vertebrate
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 5, 2024
The
ability
to
quantify
transcriptional
dynamics
in
individual
cells
via
live
imaging
has
revolutionized
our
understanding
of
gene
regulation.
However,
such
measurements
are
lacking
the
context
vertebrate
embryos.
We
addressed
this
deficit
by
applying
MS2-MCP
mRNA
labeling
quantification
transcription
zebrafish,
a
model
vertebrate.
developed
platform
transgenic
organisms,
light
sheet
fluorescence
microscopy,
and
optimized
image
analysis
that
enables
visualization
MS2
reporters.
used
these
tools
obtain
first
single-cell,
real-time
segmentation
clock.
Our
challenge
traditional
view
smooth
clock
oscillations
instead
suggest
discrete
bursts
organized
space
time.
Together,
results
highlight
how
measuring
single-cell
activity
can
reveal
unexpected
features
regulation
data
fuel
dialogue
between
theory
experiment.
Язык: Английский
Automated cell detection for immediate early gene-expressing neurons using inhomogeneous background subtraction in fluorescent images
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 8, 2024
Abstract
Although
many
methods
for
automated
fluorescent-labeled
cell
detection
have
been
proposed,
not
all
of
them
assume
a
highly
inhomogeneous
background
arising
from
complex
biological
structures.
Here,
we
propose
an
algorithm
that
accounts
and
subtracts
the
by
avoiding
high-intensity
pixels
in
blur
filtering
calculation.
Cells
were
detected
intensity
thresholding
background-subtracted
image,
algorithm’s
performance
was
tested
on
NeuN-
c-Fos-stained
images
mouse
prefrontal
cortex
hippocampal
dentate
gyrus.
In
addition,
applications
c-Fos
positive
counting
quantification
expression
level
double-labeled
cells
demonstrated.
Our
method
after
assumption
(ADABA)
offers
advantage
high-throughput
unbiased
analysis
regions
with
structures
produce
background.
Highlights
-
We
proposed
to
subtract
pattern.
(79/85)
automatically
image.
(71/85)
The
results
corresponded
manual
detection.
(73/85)
Detection
IEG
overlapping
neural
marker
(85/85)
Язык: Английский