Nitrogen Fertilization Coupled with Zinc Foliar Applications Modulate the Production, Quality, and Stress Response of Sideritis cypria Plants Grown Hydroponically Under Excess Copper Concentrations
Plants,
Год журнала:
2025,
Номер
14(5), С. 691 - 691
Опубликована: Фев. 24, 2025
The
demand
for
medicinal
and
aromatic
plants
(MAPs)
has
grown
significantly
in
recent
years,
due
to
their
therapeutic
value.
Among
these,
Sideritis
cypria
Post
is
a
promising
yet
under-evaluated
species.
Existing
research
assessing
the
effects
of
nitrogen
(N)
fertilization,
zinc
(Zn)
foliar
applications,
toxic
copper
(Cu)
concentrations
often
overlooks
MAPs
such
as
S.
cypria.
Additionally,
interactions
among
these
parameters,
well
combined
roles
plant
physiology
secondary
metabolite
biosynthesis,
have
be
fully
elucidated.
In
this
study,
hydroponically
were
cultivated
using
nutrient
solutions
(NSs)
with
different
N
(75,
150,
300
mg
L−1)
Cu
(5
100
μM)
levels,
spraying
(0
1.74
mM
Zn),
evaluate
growth,
mineral
uptake,
metabolites
production
stress
response.
levels
at
75
150
L−1
resulted
increased
dry
matter
content,
whereas
fresh
biomass
was
preserved.
Foliar
Zn
applications
enhanced
chlorophylls
antioxidants,
contingent
upon
NS.
Increased
accumulation
observed
via
increase
NS,
while
its
uptake
moderate
levels.
Excess
stimulated
accumulation,
reduction
low
high
lipid
peroxidation
(MDA)
decreased
both
MDA
hydrogen
peroxide,
Low-to-moderate
NS
can
applied
under
excess
without
compromising
yield,
quality,
safety
plants,
modulate
response
metabolites.
These
results
may
utilized
optimizing
management
strategies
cultivation
MAPs,
contributing
conservation
efforts
by
supporting
endemic
species
like
cypria,
considering
potential
benefits
Cu-contaminated
conditions.
Язык: Английский
Binding Affinity Prediction and Pesticide Screening against Phytophthora sojae Using a Heterogeneous Interaction Graph Attention Network–Based Model
Journal of Chemical Information and Modeling,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 26, 2025
Phytophthora
root
and
stem
rot
in
soybeans
results
substantial
economic
losses
worldwide.
In
this
study,
a
machine
learning
model
based
on
heterogeneous
interaction
graph
attention
network
was
constructed.
The
PDBbind
data
set,
comprising
13,285
complexes
with
experimental
pKa
or
pKi
values,
utilized
to
train
evaluate
the
model,
which
subsequently
employed
screen
candidate
compounds
against
chitin
synthase
of
sojae
(PsChs1)
Traditional
Chinese
Medicine
Systems
Pharmacology
database,
14,249
compounds.
High-scoring
were
docked
PsChs1
protein
using
Discovery
Studio,
their
energies
evaluated.
Molecular
dynamic
simulations
spanning
50
ns
performed
GROMACS
explore
stability
complexes,
trajectory
analysis
conducted
root-mean-square
deviations,
hydrogen
bonds,
radius
gyration,
MMPBSA
binding
free
energy,
modes
analyzed.
MOL011832
MOL011833
identified
as
potential
pesticides,
both
present
herb
Schizonepeta
through
database
retrieval.
inhibitory
effects
an
ethanol
extract
P.
explored
confirmed
biological
experiments.
Overall,
study
proves
feasibility
high
efficiency
pesticide
discovery
neural
network–based
models.
Язык: Английский