Biochemical Society Transactions,
Journal Year:
2024,
Volume and Issue:
52(6), P. 2579 - 2592
Published: Dec. 10, 2024
Cells
exert
forces
on
each
other
and
their
environment,
shaping
the
tissue.
The
resulting
mechanical
stresses
can
be
determined
experimentally
or
estimated
computationally
using
stress
inference
methods.
Over
years,
has
become
a
non-invasive,
low-cost
computational
method
for
estimating
relative
intercellular
intracellular
pressures
of
tissues.
This
mini-review
introduces
compares
static
dynamic
modalities
inference,
considering
advantages
limitations.
To
date,
most
software
focused
which
requires
only
single
microscopy
image
as
input.
Although
applicable
in
quasi-equilibrium
states,
this
approach
neglects
influence
that
cell
rearrangements
might
have
inference.
In
contrast,
relies
time
series
images
to
estimate
pressures.
Here,
we
discuss
both
terms
physical,
mathematical,
foundations
then
outline
what
believe
are
promising
avenues
silico
states
Smart Materials in Medicine,
Journal Year:
2024,
Volume and Issue:
5(2), P. 256 - 260
Published: March 26, 2024
Over
the
past
decades,
increasing
evidence
has
indicated
that
multiple
mechanical
signals
with
different
magnitude
and
pattern,
including
fluid
flow-derived
shear
stress,
topology
of
extracellular
matrix
(ECM),
substrate
stiffness,
tension
or
compression,
are
now
emerging
as
important
orchestrators
immune
response
under
physiological
pathophysiological
conditions.
Correspondingly,
extrinsic
may
confer
unique
mechanophenotypes
on
cells,
which
coupled
their
immunophenotypes,
determines
ultimate
type
response.
Therefore,
concept
mechano-immunological
checkpoints
is
proposed,
concerns
featured
typical
making
it
possible
to
elucidate
treat
immune-associated
disease
from
viewpoint.
Physical Review Letters,
Journal Year:
2024,
Volume and Issue:
133(10)
Published: Sept. 3, 2024
We
present
a
data-driven
pipeline
for
model
building
that
combines
interpretable
machine
learning,
hydrodynamic
theories,
and
microscopic
models.
The
goal
is
to
uncover
the
underlying
processes
governing
nonlinear
dynamics
experiments.
exemplify
our
method
with
data
from
microfluidic
experiments
where
crystals
of
streaming
droplets
support
propagation
waves
absent
in
passive
crystals.
By
combining
physics-inspired
neural
networks,
known
as
operators,
symbolic
regression
tools,
we
infer
solution,
well
mathematical
form,
dynamical
system
accurately
models
experimental
data.
Finally,
interpret
this
continuum
fundamental
physics
principles.
Informed
by
coarse
grain
interacting
discover
nonreciprocal
interactions
stabilize
promote
wave
propagation.
Database,
Journal Year:
2024,
Volume and Issue:
2024
Published: Jan. 1, 2024
Mechanical
aspects
of
tissues
and
cells
critically
influence
a
myriad
biological
processes
can
substantially
alter
the
course
diverse
diseases.
The
emergence
methodologies
adapted
from
physical
science
now
permits
precise
quantification
cellular
forces
mechanical
properties
cells.
Despite
rising
interest
in
tissue
mechanics
across
fields
like
biology,
bioengineering
medicine,
there
remains
noticeable
absence
comprehensive
readily
accessible
repository
this
pertinent
information.
To
fill
gap,
we
present
MechanoBase,
database,
curating
57
480
records
5634
PubMed
articles.
archived
MechanoBase
encompass
range
forces,
such
as
modulus
tractions,
which
have
been
measured
utilizing
various
technical
approaches.
These
measurements
span
hundreds
biosamples
more
than
400
species
studied
under
conditions.
Aiming
for
broad
applicability,
design
with
user-friendly
search,
browsing
data
download
features,
making
it
versatile
tool
exploring
biomechanical
attributes
contexts.
Moreover,
add
complementary
resources,
including
principles
popular
techniques,
concepts
mechanobiology
terms
tissue-level
expression
related
genes,
offering
scientists
unprecedented
access
to
wealth
knowledge
field
research.
Database
URL:
https://zhanglab-web.tongji.edu.cn/mechanobase/
https://compbio-zhanglab.org/mechanobase/.
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2024,
Volume and Issue:
unknown
Published: March 17, 2024
Abstract
The
metabolic
activity
of
soil
microbiomes
plays
a
central
role
in
carbon
and
nitrogen
cycling.
Given
the
changing
climate,
it
is
important
to
understand
how
metabolism
natural
communities
responds
environmental
change.
However,
ecological,
spatial,
chemical
complexity
soils
makes
understanding
mechanisms
governing
response
these
perturbations
challenging.
Here,
we
overcome
this
by
using
dynamic
measurements
microcosms
modeling
reveal
regimes
where
few
key
govern
We
sample
along
pH
gradient,
construct
>1500
perturb
pH,
quantify
dynamics
respiratory
nitrate
utilization,
process
cycle.
Despite
microbiome,
minimal
mathematical
model
with
two
variables,
quantity
active
biomass
community
availability
growth-limiting
nutrient,
quantifies
observed
utilization
across
perturbations.
Across
perturbations,
changes
variables
give
rise
three
functional
each
qualitatively
distinct
over
time:
regime
acidic
induce
cell
death
that
limits
activity,
nutrientlimiting
uptake
performed
dominant
taxa
utilize
nutrients
released
from
matrix,
resurgent
growth
basic
conditions,
excess
enable
initially
rare
taxa.
underlying
mechanism
predicted
our
interpretable
tested
via
amendment
experiments,
nutrient
measurements,
sequencing.
Further,
data
suggest
long-term
history
variation
wild
influences
transitions
between
regimes.
Therefore,
quantitative
existence
qualitative
capture
responding
Biophysical Reviews,
Journal Year:
2024,
Volume and Issue:
16(5), P. 625 - 637
Published: Oct. 1, 2024
Abstract
A
key
developmental
stage
in
mammalian
folliculogenesis
is
the
formation
of
a
fluid-filled
lumen
(antrum)
prior
to
ovulation.
While
it
has
long
been
speculated
that
follicular
fluid
essential
for
oocyte
maturation
and
ovulation,
little
known
about
morphogenesis
mechanisms
driving
antrum
potentially
due
challenges
imaging
tissue
dynamics
large
tissues.
Misregulation
such
processes
leads
anovulation,
hallmark
infertility
ageing
diseases
as
polycystic
ovary
syndrome
(PCOS).
In
this
review,
we
discuss
recent
advances
deep
techniques,
machine
learning
theoretical
approaches
have
applied
study
development
diseases.
We
propose
an
integrative
approach
combining
these
techniques
understanding
physics
hydraulics
follicle
ovarian
functions.
PRX Life,
Journal Year:
2024,
Volume and Issue:
2(4)
Published: Nov. 7, 2024
Multicellular
self-assembly
into
functional
structures
is
a
dynamic
process
that
critical
in
the
development
of
biological
and
diseases,
including
embryo
development,
organ
formation,
tumor
invasion,
other
processes.
Being
able
to
infer
collective
cell
migratory
dynamics
from
their
static
configuration
valuable
for
both
understanding
predicting
these
complex
behaviors.
However,
identification
structural
features
can
indicate
multicellular
motion
has
been
difficult,
existing
metrics
largely
rely
on
physical
instincts.
Here
we
show
that,
through
use
graph
neural
network,
collectives
be
inferred
snapshot
positions,
experimental
synthetic
datasets.
Published
by
American
Physical
Society
2024
