Journal of Pure and Applied Microbiology,
Год журнала:
2024,
Номер
18(2), С. 797 - 807
Опубликована: Май 27, 2024
Tremendous
increase
in
anthropogenic
activities
and
natural
disasters
have
created
long
term
negative
impacts
to
the
crop
productivity
as
well
on
our
ecosystem.
In
debate
regarding
ongoing
ecosystem
fluctuations,
there
is
a
need
explore
an
efficient,
cost-effective,
target-oriented
less
manpower-based
technologies
for
sustainable
development.
Microbial
engineering
provides
better
solution
growth
of
healthy
environment
higher
agricultural
over
existing
methods
resolved
challenges
worldwide
related
development
agriculture
greener
ecosystems.
recent
years,
researchers
are
working
different
advanced
microbial
strategies
such
gene
editing,
CRISPR/Cas9,
RNAi
enhance
potential
microorganisms
towards
plant
degradation
pollutants.
The
present
review
focused
applications
genetically
engineered
inoculants
Artificial
intelligence
(AI)
is
revolutionizing
plant
sciences
by
enabling
precise
species
identification,
early
disease
diagnosis,
crop
yield
prediction,
and
precision
agriculture
optimization.
AI
uses
machine
learning
image
recognition
to
aid
ecological
research
biodiversity
conservation.
It
plays
a
crucial
role
in
breeding
accelerating
the
development
of
resilient,
high-yielding
crops
with
desirable
traits.
models
using
climate
soil
data
contribute
sustainable
food
security.
In
phenotyping,
automates
measurement
analysis
characteristics,
enhancing
our
understanding
growth.
Ongoing
aims
improve
models’
robustness
interpretability
while
addressing
privacy
algorithmic
biases.
Interdisciplinary
collaboration
essential
fully
harness
AI’s
potential
for
sustainable,
food-secure
future.
Advancing
therapeutic
progress
is
centered
on
developing
drug
delivery
systems
(DDS)
that
control
molecule
release,
ensuring
precise
targeting
and
optimal
concentrations.
Targeted
DDS
enhances
treatment
efficacy
minimizes
off-target
effects,
but
struggles
with
degradation.
Over
the
last
three
decades,
nanopharmaceuticals
have
evolved
from
laboratory
concepts
into
clinical
products,
highlighting
profound
impact
of
nanotechnology
in
medicine.
Despite
advancements,
effective
therapeutics
remains
challenging
because
biological
barriers.
Nanocarriers
offer
a
solution
small
size,
high
surface-to-volume
ratios,
customizable
properties.
These
address
physiological
challenges,
such
as
shear
stress,
protein
adsorption,
quick
clearance.
They
allow
targeted
to
specific
tissues,
improve
outcomes,
reduce
adverse
effects.
exhibit
controlled
decreased
degradation,
enhanced
efficacy.
Their
size
facilitates
cell
membrane
penetration
intracellular
delivery.
Surface
modifications
increase
affinity
for
types,
allowing
This
study
also
elucidates
potential
integration
artificial
intelligence
nanoscience
innovate
future
nanocarrier
systems.
This
study
investigates
the
transformative
potential
of
mushroom-derived
biomaterials
within
biomedical
engineering,
presenting
them
as
sustainable
and
eco-friendly
alternatives
to
conventional
materials.
By
examining
distinct
characteristics
chemical
compositions
various
mushroom
species,
we
highlight
their
suitability
for
creating
innovative
biomaterials.
The
paper
focuses
on
key
components,
such
polysaccharides,
fungal
mycelium,
chitin/chitosan,
demonstrating
applications
in
tissue
antimicrobial
treatments,
drug
delivery
systems.
biodegradability
cultivation
mushrooms
underscore
environmental
advantages,
aligning
with
global
sustainability
goals.
Through
detailed
case
studies,
illustrate
successful
these
medical
devices,
construction,
packaging,
showcasing
versatility
effectiveness.
also
addresses
current
challenges
proposes
future
research
directions,
emphasizing
need
interdisciplinary
collaboration
ensure
safety,
biocompatibility,
ethical
use
mushroom-based
Our
provides
a
comprehensive
roadmap
harnessing
materials,
paving
way
significant
advancements
devices
contributing
more
future.
We
have
demonstrated
that
are
promising
frontier
material
science,
revolutionize
field
contribute
environment.
Journal of Composites Science,
Год журнала:
2025,
Номер
9(1), С. 16 - 16
Опубликована: Янв. 2, 2025
The
development
of
models
the
physicochemical
and
biochemical
behavior
nanomaterials
is
useful
for
improving
evaluation
management
this
material.
Quasi-SMILES
technology
makes
it
possible
to
quite
successfully
cope
with
kind
modeling
task,
accounting
various
experimental
conditions,
where
use
other
approaches
difficult
or
even
impossible.
Here,
we
describe
results
using
quasi-SMILES
model
toxicity
mixtures
titanium
nano
oxide
inorganic
substances
towards
Daphnia
magna.
approach
based
on
stochastic
process
optimization
correlation
weights
different
codes
used
in
quasi-SMILES.
was
carried
out
special
statistical
criteria
predictive
potential.
It
shown
that
built
have
best
Cervical
cancer
remains
the
top
killer
of
women
at
a
young
age
in
world,
85%
cases
are
detected
low-income
countries.
Preventive
measures
and
therapeutic
response
enhanced
if
potential
hazards
identified
early.
This
research
belongs
to
this
field
by
introducing
an
end-to-end
prediction
model
based
on
individual
medical
records
early
screening
data
thus
emphasizing
discovery
meaningful
predictors.
In
order
overcome
issues
with
feature
selection
class
imbalances,
our
study
creates
ensemble
framework
that
blends
Random
Forest
Logistic
Regression
techniques.
addition
achieving
astounding
accuracy
99.75%,
guarantees
transparency
its
decision-making
processes
utilizing
sophisticated
machine
learning
algorithms
conjunction
interpretability
tools
like
SHAP
LIME,
which
is
essential
for
applications
healthcare.
The
creation
extensive
method
combines
several
classifiers,
advanced
techniques
locating
important
predictive
factors,
help
healthcare
professionals
better
understand
complex
predictions
some
research's
main
investments.
By
offering
accurate
comprehensible
risk
assessments,
novel
has
revolutionize
clinical
enhance
cervical
cavity
identification.
promotes
development
more
proactive
individualized
methods
fusing
cutting-edge
computational
technology
diagnostics,
improving
health
outcomes
everywhere.
Advanced Biology,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 12, 2025
Abstract
Plants
are
vital
to
ecosystems
and
human
survival,
possessing
intricate
internal
inter‐plant
signaling
networks
that
allow
them
adapt
quickly
changing
environments
maintain
ecological
balance.
The
integration
of
engineered
nanomaterials
(ENMs)
with
plant
systems
has
led
the
emergence
nanobionics,
a
field
holds
potential
enhance
capabilities
significantly.
This
may
result
in
improved
photosynthesis,
increased
nutrient
uptake,
accelerated
growth
development.
treated
ENMs
can
be
stress
mitigators,
pollutant
detectors,
environmental
sensors,
even
light
emitters.
review
explores
recent
advancements
focusing
on
nanoparticle
(NP)
synthesis,
adhesion,
transport,
fate,
application
enhancing
physiological
functioning,
mitigation,
health
monitoring,
energy
production,
sensing,
overall
productivity.
Potential
research
directions
challenges
nanobionics
highlighted,
how
material
optimization
innovation
propelling
smart
agriculture,
pollution
remediation,
energy/biomass
production
discussed.
Advanced Functional Materials,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 11, 2025
Abstract
Machine
learning
(ML)
is
increasingly
adopted
to
explore
the
dependence
of
properties
on
descriptors
especially
for
materials
with
complicated
structure–activity
relationships.
However,
most
current
ML
modeling
strategies
typically
depend
a
single
combination
descriptors,
which
leads
inaccurate
and
unilateral
inferences.
Here,
divide‐and‐conquer
method
proposed
machine
(descriptors‐DCML)
in
rough
set
theory
(RST)
integrated
domain
knowledge
select
multiple
optimal
sets
combinations
thus
diverse
rule
extraction
are
provided
dig
out
mechanisms
latent
data.
Its
potential
utility
applications
using
sodium
ion
energy
barrier
prediction
NASICION‐type
solid‐state
electrolyte
compounds
multifaceted
influencing
factors
as
an
example
demonstrated.
A
total
85
samples
45
derived
from
72
published
literature
serve
data
foundation
modeling.
Not
only
does
descriptors‐DCML
exhibit
accuracy
93.8%
but
also
extract
9
relations
mapping
essential
Na
5
ones
conform
existing
understanding
rest
waiting
validation.
This
work
paves
way
reducing
complexity
analyzing
relationships
enhancing
interpretability
models.
Journal of Functional Biomaterials,
Год журнала:
2025,
Номер
16(5), С. 158 - 158
Опубликована: Апрель 28, 2025
This
article
explores
the
transformative
advances
in
soft
machines,
where
biology,
materials
science,
and
engineering
have
converged.
We
discuss
remarkable
adaptability
versatility
of
whose
designs
draw
inspiration
from
nature’s
elegant
solutions.
From
intricate
movements
octopus
tentacles
to
resilience
an
elephant’s
trunk,
nature
provides
a
wealth
for
designing
robots
capable
navigating
complex
environments
with
grace
efficiency.
Central
this
advancement
is
ongoing
research
into
bioinspired
materials,
which
serve
as
building
blocks
creating
machines
lifelike
behaviors
adaptive
capabilities.
By
fostering
collaboration
innovation,
we
can
unlock
new
possibilities
shaping
future
seamlessly
integrate
interact
natural
world,
offering
solutions
humanity’s
most
pressing
challenges.