Unveiling the chemical complexity of food-risk components: A comprehensive data resource guide in 2024
Dachuan Zhang,
No information about this author
Dongliang Liu,
No information about this author
Jiayi Jing
No information about this author
et al.
Trends in Food Science & Technology,
Journal Year:
2024,
Volume and Issue:
148, P. 104513 - 104513
Published: April 26, 2024
With
the
influence
of
climate
change,
environmental
pollution,
industrial
development,
and
new
agricultural
practices,
increasing
amounts
chemical
substances
with
potential
risks—both
anthropogenic
biogenic—enter
food
supply
chain
ultimately
affect
human
health,
entailing
challenges
to
safety
security.
Although
some
food-risk
components
(FRCs)
have
been
accessed
regulated,
toxicity
exposure
level
numerous
detected
in
remain
unknown,
leaving
questions
on
their
effect
safety.
Therefore,
multiple
databases
emerging
FRCs
constructed
aid
risk
assessment,
regulation,
communication;
however,
focus
areas,
data
content,
quality,
accessibility
not
systematically
summarized,
which
hinders
development
applications
data-driven
methods
field.
The
major
objective
this
review
is
comprehensively
introduce
representative
FRC
different
along
presentation,
quality
availability,
successful
applications.
Over
past
decades,
over
50
released
widely
used
hazard
identification,
prediction,
contributing
significantly
scientific
research,
policymaking,
education.
However,
our
analysis
unveils
persistent
such
as
delayed
updates,
concerns,
reproducibility
issues,
suboptimal
inadequate
coverage
underdeveloped
regions.
To
address
these
shortcomings,
we
propose
an
initiative
aimed
at
enhancing
future
FRC-related
resources,
prioritizing
principles
findability,
accessibility,
interoperability,
reusability.
Additionally,
highlight
strategies,
e.g.,
natural
language
processing,
cheminformatics,
suspect
non-targeted
analysis,
genome
mining,
for
detection
outside
existing
databases.
By
embracing
initiatives
lay
groundwork
a
robust
framework
facilitating
enhanced
assessment
informed
decision-making
face
evolving
challenges.
Language: Английский
Knowledge graph and its application in the study of neurological and mental disorders
Frontiers in Psychiatry,
Journal Year:
2025,
Volume and Issue:
16
Published: March 18, 2025
Neurological
disorders
(e.g.,
Alzheimer's
disease
and
Parkinson's
disease)
mental
depression
anxiety),
pose
huge
challenges
to
global
public
health.
The
pathogenesis
of
these
diseases
can
usually
be
attributed
many
factors,
such
as
genetic,
environmental
socioeconomic
status,
which
make
the
diagnosis
treatment
difficult.
As
research
on
advances,
so
does
body
medical
data.
accumulation
data
provides
unique
opportunities
for
basic
clinical
study
diseases,
but
vast
diverse
nature
also
it
difficult
physicians
researchers
precisely
extract
information
utilize
in
their
work.
A
powerful
tool
necessary
knowledge
from
large
amounts
is
graph
(KG).
KG,
an
organized
form
information,
has
great
potential
neurological
when
paired
with
big
deep
learning
technologies.
In
this
study,
we
reviewed
application
KGs
common
recent
years.
We
discussed
current
state
graphs,
highlighting
obstacles
constraints
that
still
need
overcome.
Language: Английский
Symphonies of metabolomics
Published: Jan. 1, 2024
WikiPathways
(wikipathways.org)captures
the
collective
knowledge
represented
in
biological
pathways.By
providing
a
database
curated,
machine
readable
way,
omics
data
analysis
and
visualization
is
enabled.WikiPathways
other
pathway
databases
are
used
to
analyze
experimental
by
research
groups
many
fields.Due
open
collaborative
nature
of
platform,
our
content
keeps
growing
getting
more
accurate,
making
reliable
rich
database.Previously,
however,
focus
was
primarily
on
genes
proteins,
leaving
metabolites
with
only
limited
annotation.Recent
curation
efforts
focused
improving
annotation
metabolism
metabolic
pathways
associating
unmapped
identifiers
detailed
interaction
knowledge.Here,
we
report
outcomes
continued
growth
efforts,
such
as
doubling
number
annotated
metabolite
nodes
WikiPathways.Furthermore,
introduce
an
OpenAPI
documentation
web
services
FAIR
(Findable,
Accessible,
Interoperable
Reusable)
resources
increase
interoperability
encoded
these
data.New
search
options,
monthly
downloads,
links
databases,
new
portals
make
effortlessly
accessible
individual
researchers
communities.
Language: Английский