Environmental Science Nano,
Год журнала:
2024,
Номер
11(9), С. 3744 - 3760
Опубликована: Янв. 1, 2024
Methanol
probe
chemisorption
quantifies
the
number
of
reactive
sites
at
surface
engineered
nanomaterials,
enabling
normalization
per
site
in
reactivity
and
toxicity
tests,
rather
than
mass
or
physical
area.
Subsequent
temperature-programmed
reaction
(TPSR)
chemisorbed
methanol
identifies
nature
(acidic,
basic,
redox
combination
thereof)
their
reactivity.
Complementary
to
assay,
a
dithiothreitol
(DTT)
oxidation
is
used
evaluate
capacity.
These
acellular
approaches
quantify
number,
nature,
constitute
new
approach
methodology
(NAM)
for
site-specific
classification
nanomaterials.
As
proof
concept,
CuO,
CeO2,
ZnO,
Fe3O4,
CuFe2O4,
Co3O4
two
TiO2
nanomaterials
were
probed.
A
harmonized
descriptor
ENMs
was
obtained:
DTT
rate
site,
oxidative
turnover
frequency
(OxTOF).
CuO
CuFe2O4
exhibit
largest
density
possess
highest
oxidizing
ability
series,
as
estimated
by
reaction,
followed
CeO2
NM-211
then
titania
(DT-51
NM-101)
Fe3O4.
depletion
ZnO
NM-110
associated
with
dissolved
zinc
ions
particles;
however,
basic
characteristics
particles
evidenced
TPSR.
assays
allow
ranking
eight
into
three
categories
statistically
different
potentials:
are
most
reactive;
ceria
exhibits
moderate
reactivity;
iron
oxide
titanias
low
potential.
The Journal of Physical Chemistry Letters,
Год журнала:
2024,
Номер
15(22), С. 5804 - 5813
Опубликована: Май 23, 2024
Nanozymes
are
unique
materials
with
many
valuable
properties
for
applications
in
biomedicine,
biosensing,
environmental
monitoring,
and
beyond.
In
this
work,
we
developed
a
machine
learning
(ML)
approach
to
search
new
nanozymes
deployed
web
platform,
DiZyme,
featuring
state-of-the-art
database
of
containing
1210
experimental
samples,
catalytic
activity
prediction,
DiZyme
Assistant
interface
powered
by
large
language
model
(LLM).
For
the
first
time,
enable
prediction
multiple
activities
training
an
ensemble
algorithm
achieving
R2
=
0.75
Michaelis–Menten
constant
0.77
maximum
velocity
on
unseen
test
data.
We
envision
accurate
(peroxidase,
oxidase,
catalase)
promoting
novel
wide
range
surface-modified
inorganic
nanozymes.
The
based
ChatGPT
provides
users
supporting
information
such
as
synthesis
procedures,
measurement
protocols,
etc.
(dizyme.aicidlab.itmo.ru)
is
now
openly
available
worldwide.
Frontiers in Immunology,
Год журнала:
2023,
Номер
14
Опубликована: Сен. 19, 2023
Prostate
cancer
(PCa)
is
a
prevalent
malignancy
with
increasing
incidence
in
middle-aged
and
older
men.
Despite
various
treatment
options,
advanced
metastatic
PCa
remains
challenging
poor
prognosis
limited
effective
therapies.
Nanomedicine,
its
targeted
drug
delivery
capabilities,
has
emerged
as
promising
approach
to
enhance
efficacy
reduce
adverse
effects.
Prostate-specific
membrane
antigen
(PSMA)
stands
one
of
the
most
distinctive
highly
selective
biomarkers
for
PCa,
exhibiting
robust
expression
cells.
In
this
review,
we
explore
applications
PSMA-targeted
nanomedicines
management.
Our
primary
objective
bridge
gap
between
cutting-edge
nanomedicine
research
clinical
practice,
making
it
accessible
medical
community.
We
discuss
mainstream
strategies
including
chemotherapy,
radiotherapy,
immunotherapy,
context
nanomedicines.
Additionally,
elucidate
novel
concepts
such
photodynamic
photothermal
therapies,
along
nano-theragnostics.
present
content
clear
manner,
appealing
general
physicians,
those
backgrounds
biochemistry
bioengineering.
The
review
emphasizes
potential
benefits
enhancing
efficiency
improving
patient
outcomes.
While
use
nano-drug
demonstrated
results,
further
investigation
required
comprehend
precise
mechanisms
action,
pharmacotoxicity,
long-term
By
meticulous
optimization
combination
PSMA
ligands,
horizon
nanomedicine-based
therapy
could
bring
renewed
hope
patients
PCa.
Abstract
Nanoparticles
(NPs)
have
been
employed
as
drug
delivery
systems
(DDSs)
for
several
decades,
primarily
passive
carriers,
with
limited
selectivity.
However,
recent
publications
shed
light
on
the
emerging
phenomenon
of
NPs
exhibiting
selective
cytotoxicity
against
cancer
cell
lines,
attributable
to
distinct
metabolic
disparities
between
healthy
and
pathological
cells.
This
study
revisits
concept
cytotoxicity,
first
time
proposes
a
high‐throughput
in
silico
screening
approach
massive
targeted
discovery
selectively
cytotoxic
inorganic
NPs.
In
step,
this
work
trains
gradient
boosting
regression
model
predict
viability
NP‐treated
lines.
The
achieves
mean
cross‐validation
(CV)
Q2
=
0.80
root
square
error
(RMSE)
13.6.
second
develops
machine
learning
(ML)
reinforced
genetic
algorithm
(GA),
capable
>14
900
candidates/min,
identify
best‐performing
As
proof‐of‐concept,
DDS
candidates
treatment
liver
are
screened
HepG2
hepatocytes
lines
resulting
Ag
toxicity
score
42%.
opens
door
clinical
translation
NPs,
expanding
their
therapeutic
application
wider
range
chemical
space
living
organisms
such
bacteria
fungi.
MRS Communications,
Год журнала:
2024,
Номер
14(5), С. 752 - 770
Опубликована: Июль 1, 2024
Abstract
Artificial
intelligence
and
machine
learning
(ML)
continue
to
see
increasing
interest
in
science
engineering
every
year.
Polymer
is
no
different,
though
implementation
of
data-driven
algorithms
this
subfield
has
unique
challenges
barring
widespread
application
these
techniques
the
study
polymer
systems.
In
Prospective,
we
discuss
several
critical
ML
science,
including
structure
representation,
high-throughput
limitations,
limited
data
availability.
Promising
studies
targeting
resolution
issues
are
explored,
contemporary
research
demonstrating
potential
despite
existing
obstacles
discussed.
Finally,
present
an
outlook
for
moving
forward.
Graphical
Frontiers in Oncology,
Год журнала:
2025,
Номер
15
Опубликована: Фев. 7, 2025
Iron-based
nanomaterials
(INMs),
due
to
their
particular
magnetic
property,
excellent
biocompatibility,
and
functionality,
have
been
developed
into
powerful
tools
in
both
tumor
diagnosis
therapy.
We
give
an
overview
here
on
how
INMs
such
as
iron
oxide
nanoparticles,
element-doped
nanocomposites,
iron-based
organic
frameworks
(MOFs)
display
versatility
for
imaging
therapy
improvement.
In
terms
of
imaging,
improve
the
sensitivity
accuracy
techniques
resonance
(MRI)
photoacoustic
(PAI)
support
development
multimodal
platforms.
Regarding
treatment,
play
a
key
role
advanced
strategies
immunotherapy,
hyperthermia,
synergistic
combination
therapy,
which
effectively
overcome
tumor-induced
drug
resistance
reduce
systemic
toxicity.
The
integration
with
artificial
intelligence
(AI)
radiomics
further
expands
its
capabilities
precise
identification,
treatment
optimization,
amplifies
monitoring.
now
link
materials
science
computing
clinical
innovations
enable
next-generation
cancer
diagnostics
therapeutics.
