Application of Machine Learning in LC-MS-Based Non-Targeted Analysis
TrAC Trends in Analytical Chemistry,
Год журнала:
2025,
Номер
unknown, С. 118243 - 118243
Опубликована: Март 1, 2025
Язык: Английский
An evaluation strategy of high-quality traditional Chinese patent medicines with consistency as the core: A case study of Huoxiang Zhengqi Shui
Arabian Journal of Chemistry,
Год журнала:
2025,
Номер
0, С. 1 - 9
Опубликована: Апрель 7, 2025
Язык: Английский
A “seed”-based molecular networking strategy for the screening and identification of unknown glucocorticoids in cosmetics
Arabian Journal of Chemistry,
Год журнала:
2025,
Номер
0, С. 1 - 13
Опубликована: Апрель 7, 2025
Язык: Английский
Advances in intelligent mass spectrometry data processing technology for in vivo analysis of natural medicines
Chinese Journal of Natural Medicines,
Год журнала:
2024,
Номер
22(10), С. 900 - 913
Опубликована: Окт. 1, 2024
Язык: Английский
An integrated approach for studying exposure, metabolism, and disposition of traditional Chinese medicine using PATBS and MDRB tools: a case study of semen Armeniacae Amarum
Chinese Medicine,
Год журнала:
2024,
Номер
19(1)
Опубликована: Ноя. 14, 2024
Abstract
Background
Deciphering
the
in
vivo
processes
of
traditional
Chinese
medicine
(TCM)
is
crucial
for
identifying
new
pharmacodynamic
substances
and
drugs.
Due
to
complexity
diversity
components,
investigating
exposure,
metabolism,
disposition
remains
a
major
challenge
TCM
research.
In
recent
years,
number
non-targeted
smart
mass-spectrometry
(MS)
techniques,
such
as
precise-and-thorough
background-subtraction
(PATBS)
metabolomics,
have
realized
intelligent
identification
components
TCM.
However,
metabolites
characterization
still
largely
relies
on
manual
combination
with
online
databases.
Results
We
developed
scoring
approach
based
structural
similarity
minimal
mass
defect
variations
between
prototypes.
The
current
method
integrates
three
dimensions
spectral
data
including
m/z
,
MS1
MS2,
MS2
fragments,
which
was
sequentially
analyzed
by
R-based
dataset
relevance
bridging
(MDRB)
post-processing
technique.
MDRB
technology
constructed
component
relationship
network
TCM,
significantly
improving
metabolite
efficiency
facilitating
mapping
translational
metabolic
pathways.
By
combining
PATBS
through
this
technology,
we
comprehensive
strategy
identification,
analysis
vivo.
As
proof
concept,
adopted
proposed
investigate
process
Semen
Armeniacae
Amarum
(CKXR)
mice.
Significance
currently
analytical
universally
applicable
demonstrates
its
effectiveness
analyzing
complex
TCMs
vitro
Furthermore,
it
enables
correlation
data,
providing
insights
into
transformations
among
sharing
same
parent
nucleus
structure.
Finally,
platform
publicly
available
(
https://github.com/933ZhangDD/MDRB
)
accelerating
research
scientific
community.
Graphical
Язык: Английский
A tailored database combining reference compound-derived metabolite, metabolism platform and chemical characteristic of Chinese herb followed by activity screening: Application to Magnoliae Officinalis Cortex
Journal of Pharmaceutical Analysis,
Год журнала:
2024,
Номер
unknown, С. 101066 - 101066
Опубликована: Авг. 1, 2024
A
strategy
combining
a
tailored
database
and
high-throughput
activity
screening
that
discover
bioactive
metabolites
derived
from
Magnoliae
Officinalis
Cortex
(MOC)
was
developed
implemented
to
rapidly
profile
in
vivo
traditional
Chinese
medicine
(TCM).
The
possessed
four
characteristics:
1)
consisted
of
big
data-originated
reference
compound,
predicted
silico,
MOC
chemical
profile-based
pseudomolecular
ions.
2)
When
profiling
MOC-derived
vivo,
attentions
were
paid
not
only
on
prototypes
compounds
directly
compounds,
as
reported
by
most
papers,
but
also
isomerized
the
degradation
products
well
their
metabolites.
3)
Metabolite
traceability
performed,
especially
distinguish
isomeric
prototypes-derived
metabolites,
phase
I
other
compounds.
4)
Molecular
docking
utilized
for
molecular
dynamic
simulation
zebrafish
model
used
verification.
Using
this
strategy,
134
swiftly
characterized
after
oral
administration
rats,
several
first
time.
Furthermore,
17
potential
active
discovered
targeting
motilin,
dopamine
D2,
serotonin
type
4
(5-HT4)
receptors,
bioactivities
verified
using
constipation
model.
This
study
extends
application
mass
spectrometry
(MS)
TCM-derived
which
will
help
pharmacologists
potent
complex
matrix.
Язык: Английский
An Integrated Approach for Studying Exposure, Metabolism, and Disposition of Traditional Chinese Medicine using PATBS and MDRB Tools: A Case Study of Semen Armeniacae Amarum
Research Square (Research Square),
Год журнала:
2024,
Номер
unknown
Опубликована: Окт. 21, 2024
Abstract
Background:
Traditional
Chinese
medicine
(TCM)
in
vivoprocess
research
is
crucial
for
the
development
of
TCM
pharmacodynamic
substances
and
new
drugs.
Exposure,
metabolism,
disposition
are
always
difficulties
topical
issues
in
study,
due
to
complexity
diversity
its
components.
In
recent
years,
a
number
non-targeted
smart
mass-spectrometry
(MS)
techniques,
such
as
precise-and-thorough
background-subtraction
(PATBS)
metabolomics,
have
realized
intelligent
identification
vivo
components
TCM.
However,
characterization
metabolites
still
mainly
relies
on
manual
combination
with
online
databases.
Results:
We
design
scoring
approach,
based
structural
similarity
well
small
difference
mass
defect
between
prototypes.
details,
it
was
three
dimensions
spectral
data:
m/z,
MS1
MS2,
MS2
fragments,
where
R
language
editing
algorithms
were
utilized
develop
novel
dataset
relevance
bridging
(MDRB)
data
post-processing
technique.
MDRB
technology
can
realize
construction
component
relationship
network
TCM,
which
effectively
enhance
efficiency
help
mapping
translational
metabolic
pathways.
A
has
been
developed
PATBS,
construct
complete
strategy
identification,
analysis
metabolite
vivo.
Based
this
proposed
strategy,
we
take
Semen
Armeniacae
Amarum
(CKXR)
an
example
conduct
whole
process
study
exposure,
mice.
Significance:
The
previously
described
analytical
approach
universally
applicable
demonstrates
effectiveness
analyzing
complex
TCMs
vitro
Furthermore,
correlation
them
also
be
realized,
transformation
same
parent
nucleus
structure
explored
depth.
Last
but
not
least,
code
algorithmic
uploaded
platform
(https://github.com/933ZhangDD/MDRB)
publicly
available.
Язык: Английский
Metabolomics-Driven Prediction of Vegetable Food Metabolite Patterns: Advances in Machine Learning Approaches
Food Reviews International,
Год журнала:
2024,
Номер
unknown, С. 1 - 30
Опубликована: Ноя. 24, 2024
Understanding
food
metabolite
patterns
is
crucial
for
various
aspects
of
science,
including
quality
assessment
and
safety
evaluation.
This
comprehensive
review
explores
the
integration
machine
learning
metabolomics
technologies
predicting
vegetable
patterns.
The
significance
in
analyzing
omics
data
highlighted.
Various
techniques,
supervised,
unsupervised,
deep
algorithms,
are
examined
their
efficacy
metabolites.
Challenges
integrating
learning,
such
as
preprocessing,
dimensionality
reduction,
model
interpretability,
addressed,
alongside
potential
solutions.
Applications
patterns,
authentication,
assessment,
personalized
nutrition,
flavor
profiling,
explored
through
case
studies.
Future
perspectives
highlight
emerging
trends,
applications
precision
agriculture
industry,
need
advancements
to
facilitate
widespread
adoption.
Язык: Английский
CNN-FSPM-Based Fingerprint Indexing and Matching for Detecting, Predicting, and Preventing Cheating in Online Examinations
International Journal of Knowledge and Systems Science,
Год журнала:
2024,
Номер
15(1), С. 1 - 20
Опубликована: Дек. 20, 2024
This
paper
presents
a
comprehensive
approach
to
the
detection
and
prevention
of
cheating
in
online
exams
using
AI.
The
authors
employ
various
technical
solutions
monitor
proctors
throughout
all
stages
exam:
before,
during,
after.
To
address
formulations
ensure
continuous
expansion
database,
rely
on
fast
convolutional
neural
network
(CNN)
that
utilizes
full-scope
pattern
matching
algorithm
(FSPM)
enhance
ability
match
fingerprint
formats
descriptive
cryptography.
anticipate
reliable
across
complete
image
set
through
utilization
deep-learning
(DL)
symbols.
Furthermore,
demonstrate
solving
image-matching
problems
does
not
necessitate
tool
training
data,
which
is
typically
required
for
such
problems.
Thanks
highly
parallelizable
nature
these
tasks,
provide
an
efficient
method
with
minimal
computational
cost
during
test
time
detect
some
at
School
Computer
Science
Danang
University
Technology
(SCS-DTU)
University,
Vietnam.
Язык: Английский
Response surface methodology for supercritical CO2 extraction and microencapsulation of multi-components from “Pericarpium Citri Reticulatae - Fructus Aurantii” contained in herbal formulations
Industrial Crops and Products,
Год журнала:
2024,
Номер
223, С. 120171 - 120171
Опубликована: Дек. 6, 2024
Язык: Английский