Frontiers in Molecular Neuroscience,
Journal Year:
2021,
Volume and Issue:
14
Published: Feb. 25, 2021
One
of
the
major
unsolved
mysteries
biological
science
concerns
question
where
and
in
what
form
information
is
stored
brain.
I
propose
that
memory
brain
a
mechanically
encoded
binary
format
written
into
conformations
proteins
found
cell-extracellular
matrix
(ECM)
adhesions
organise
each
every
synapse.
The
MeshCODE
framework
outlined
here
represents
unifying
theory
data
storage
animals,
providing
read-write
both
dynamic
persistent
format.
Mechanosensitive
contain
force-dependent
switches
can
store
persistently,
which
be
or
updated
using
small
changes
mechanical
force.
These
mechanosensitive
proteins,
such
as
talin,
scaffold
synapse,
creating
meshwork
together
code,
so-called
MeshCODE.
Large
signalling
complexes
assemble
on
these
scaffolds
function
switch
patterns
would
stabilise
coordinate
synaptic
regulators
to
dynamically
tune
activity.
Synaptic
transmission
action
potential
spike
trains
operate
cytoskeletal
machinery
write
update
MeshCODEs,
thereby
propagating
this
coding
throughout
organism.
Based
established
biophysical
principles,
basis
for
provide
physical
location
brain,
with
patterns,
information-storing
molecules
scaffolds,
them,
representing
engrams.
Furthermore,
conversion
sensory
temporal
inputs
constitute
an
addressable
system,
supporting
view
mind
organic
supercomputer.
Nature Communications,
Journal Year:
2021,
Volume and Issue:
12(1)
Published: April 15, 2021
Abstract
Deep
Learning
(DL)
methods
are
powerful
analytical
tools
for
microscopy
and
can
outperform
conventional
image
processing
pipelines.
Despite
the
enthusiasm
innovations
fuelled
by
DL
technology,
need
to
access
compatible
resources
train
networks
leads
an
accessibility
barrier
that
novice
users
often
find
difficult
overcome.
Here,
we
present
ZeroCostDL4Mic,
entry-level
platform
simplifying
leveraging
free,
cloud-based
computational
of
Google
Colab.
ZeroCostDL4Mic
allows
researchers
with
no
coding
expertise
apply
key
perform
tasks
including
segmentation
(using
U-Net
StarDist),
object
detection
YOLOv2),
denoising
CARE
Noise2Void),
super-resolution
Deep-STORM),
image-to-image
translation
Label-free
prediction
-
fnet,
pix2pix
CycleGAN).
Importantly,
provide
suitable
quantitative
each
network
evaluate
model
performance,
allowing
optimisation.
We
demonstrate
application
study
multiple
biological
processes.
Nature Communications,
Journal Year:
2023,
Volume and Issue:
14(1)
Published: Nov. 30, 2023
Expansion
microscopy
(ExM)
is
a
highly
effective
technique
for
super-resolution
fluorescence
that
enables
imaging
of
biological
samples
beyond
the
diffraction
limit
with
conventional
microscopes.
Despite
development
several
enhanced
protocols,
ExM
has
not
yet
demonstrated
ability
to
achieve
precision
nanoscopy
techniques
such
as
Single
Molecule
Localization
Microscopy
(SMLM).
Here,
address
this
limitation,
we
have
developed
an
iterative
ultrastructure
expansion
(iU-ExM)
approach
achieves
SMLM-level
resolution.
With
iU-ExM,
it
now
possible
visualize
molecular
architecture
gold-standard
samples,
eight-fold
symmetry
nuclear
pores
or
organization
conoid
in
Apicomplexa.
its
wide-ranging
applications,
from
isolated
organelles
cells
and
tissue,
iU-ExM
opens
new
avenues
scientists
studying
structures
functions.
Trends in biotechnology,
Journal Year:
2021,
Volume and Issue:
40(6), P. 647 - 676
Published: Dec. 28, 2021
Tumors
are
unique
and
complex
ecosystems,
in
which
heterogeneous
cell
subpopulations
with
variable
molecular
profiles,
aggressiveness,
proliferation
potential
coexist
interact.
Understanding
how
heterogeneity
influences
tumor
progression
has
important
clinical
implications
for
improving
diagnosis,
prognosis,
treatment
response
prediction.
Several
recent
innovations
data
acquisition
methods
computational
metrics
have
enabled
the
quantification
of
spatiotemporal
across
different
scales
organization.
Here,
we
summarize
most
promising
efforts
from
a
common
experimental
perspective,
discussing
their
advantages,
shortcomings,
challenges.
With
personalized
medicine
entering
new
era
unprecedented
opportunities,
our
vision
is
that
future
workflows
integrating
modalities,
scales,
dimensions
to
capture
intricate
aspects
ecosystem
open
avenues
improved
patient
care.
Cell Adhesion & Migration,
Journal Year:
2022,
Volume and Issue:
16(1), P. 25 - 64
Published: May 1, 2022
Cell
motility
is
essential
for
life
and
development.
Unfortunately,
cell
migration
also
linked
to
several
pathological
processes,
such
as
cancer
metastasis.
Cells'
ability
migrate
relies
on
many
actors.
Cells
change
their
migratory
strategy
based
phenotype
the
properties
of
surrounding
microenvironment.
is,
therefore,
an
extremely
complex
phenomenon.
Researchers
have
investigated
more
than
a
century.
Recent
discoveries
uncovered
some
mysteries
associated
with
mechanisms
involved
in
migration,
intracellular
signaling
mechanics.
These
findings
involve
different
players,
including
transmembrane
receptors,
adhesive
complexes,
cytoskeletal
components
,
nucleus,
extracellular
matrix.
This
review
aims
give
global
overview
our
current
understanding
migration.
Nature Communications,
Journal Year:
2022,
Volume and Issue:
13(1)
Published: Dec. 2, 2022
Abstract
The
resolution
of
fluorescence
microscopy
images
is
limited
by
the
physical
properties
light.
In
last
decade,
numerous
super-resolution
(SRM)
approaches
have
been
proposed
to
deal
with
such
hindrance.
Here
we
present
Mean-Shift
Super
Resolution
(MSSR),
a
new
SRM
algorithm
based
on
Mean
Shift
theory,
which
extends
spatial
single
beyond
diffraction
limit
MSSR
works
low
and
high
fluorophore
densities,
not
architecture
optical
setup
applicable
as
well
temporal
series.
theoretical
resolution,
optimized
real-world
imaging
conditions
analysis
image
stacks,
has
measured
be
40
nm.
Furthermore,
denoising
capabilities
that
outperform
other
approaches.
Along
its
wide
accessibility,
powerful,
flexible,
generic
tool
for
multidimensional
live
cell
applications.
Nature Methods,
Journal Year:
2023,
Volume and Issue:
20(12), P. 1949 - 1956
Published: Nov. 13, 2023
Abstract
Live-cell
super-resolution
microscopy
enables
the
imaging
of
biological
structure
dynamics
below
diffraction
limit.
Here
we
present
enhanced
radial
fluctuations
(eSRRF),
substantially
improving
image
fidelity
and
resolution
compared
to
original
SRRF
method.
eSRRF
incorporates
automated
parameter
optimization
based
on
data
itself,
giving
insight
into
trade-off
between
fidelity.
We
demonstrate
across
a
range
modalities
systems.
Notably,
extend
three
dimensions
by
combining
it
with
multifocus
microscopy.
This
realizes
live-cell
volumetric
an
acquisition
speed
~1
volume
per
second.
provides
accessible
approach,
maximizing
information
extraction
varied
experimental
conditions
while
minimizing
artifacts.
Its
optimal
prediction
strategy
is
generalizable,
moving
toward
unbiased
optimized
analyses
in