Technium Social Sciences Journal,
Год журнала:
2021,
Номер
23, С. 134 - 149
Опубликована: Сен. 9, 2021
Entrepreneurship
is
a
phenomenon
that
has
an
important
influence
on
the
progress
and
welfare
of
world,
so
entrepreneurship
used
as
base
economic
development.
Psychologically,
entrepreneurs
are
people
who
have
strong
internal
drive
effort
to
achieve
certain
goals
they
tendency
experiment
in
showing
character
free
from
control
others.
can
be
seen
various
points
view.
The
angle
context
question
views
several
fields,
namely
according
economists,
management,
business
people,
psychologists
investors.
main
requirement
entrepreneur
must
entrepreneurial
knowledge.
readiness
determined
by
knowledge
possessed
experience
conducting
(Kurniawati,
2019).
In
midst
rapid
development
artificial
intelligence
(AI)
technology
today.
Not
many
know
consists
branches,
one
which
machine
learning.
This
learning
(ML)
branches
AI
very
interesting.
sample
population
this
study
was
obtained
air
transportation
school
consisting
7
populations.
Data
analysis
done
using
.
research
location
with
Machine
Learning
Random
Forest
Classification
cadets,
lecturers
general
public
Abstract
Infectious
diseases
caused
by
microbial
pathogens
remain
a
primary
contributor
to
global
health
burdens.
Prompt
control
and
effective
prevention
of
these
are
critical
for
public
medical
diagnostics.
Conventional
detection
methods
suffer
from
high
complexity,
low
sensitivity,
poor
selectivity.
Therefore,
developing
rapid
reliable
pathogen
has
become
imperative.
Surface‐enhanced
Raman
Spectroscopy
(SERS),
as
an
innovative
non‐invasive
diagnostic
technique,
holds
significant
promise
in
pathogenic
microorganism
due
its
rapid,
reliable,
cost‐effective
advantages.
This
review
comprehensively
outlines
the
fundamental
theories
(RS)
with
focus
on
label‐free
SERS
strategy,
reporting
latest
advancements
technique
detecting
bacteria,
viruses,
fungi
clinical
settings.
Furthermore,
we
emphasize
application
machine
learning
algorithms
spectral
analysis.
Finally,
challenges
faced
probed,
prospective
development
is
discussed.
Chemosensors,
Год журнала:
2024,
Номер
12(7), С. 140 - 140
Опубликована: Июль 15, 2024
Detecting
pathogenic
bacteria
and
their
phenotypes
including
microbial
resistance
is
crucial
for
preventing
infection,
ensuring
food
safety,
promoting
environmental
protection.
Raman
spectroscopy
offers
rapid,
seamless,
label-free
identification,
rendering
it
superior
to
gold-standard
detection
techniques
such
as
culture-based
assays
polymerase
chain
reactions.
However,
its
practical
adoption
hindered
by
issues
related
weak
signals,
complex
spectra,
limited
datasets,
a
lack
of
adaptability
characterization
bacterial
pathogens.
This
review
focuses
on
addressing
these
with
recent
breakthroughs
enabled
machine
learning
(ML),
particularly
deep
methods.
Given
the
regulatory
requirements,
consumer
demand
safe
products,
growing
awareness
risks
pathogens,
this
study
emphasizes
pathogen
in
clinical,
settings.
Here,
we
highlight
use
convolutional
neural
networks
analyzing
clinical
data
surface
enhanced
sensitizing
early
rapid
pathogens
safety
potential
risks.
Deep
methods
can
tackle
adequate
datasets
across
diverse
samples.
We
pending
future
research
directions
needed
accelerating
real-world
impacts
ML-enabled
diagnostics
accurate
diagnosis
surveillance
critical
fields.
The Journal of Physical Chemistry B,
Год журнала:
2023,
Номер
127(9), С. 1940 - 1946
Опубликована: Фев. 23, 2023
Spore-forming
bacteria
accumulate
dipicolinic
acid
(DPA)
to
form
spores
survive
in
extreme
environments.
Vibrational
spectroscopy
is
widely
used
detect
DPA
and
elucidate
the
existence
of
bacteria,
while
vegetative
cells,
another
spore-forming
have
not
been
studied
extensively.
Herein,
we
applied
coherent
anti-Stokes
Raman
scattering
(CARS)
microscopy
spectroscopically
identify
both
cells
without
staining
or
molecular
tagging.
The
were
identified
by
strong
CARS
signals
due
DPA.
Furthermore,
observed
bright
spots
image
at
1735
cm–1.
contained
species
with
C=O
bonds
because
this
vibrational
mode
was
associated
carbonyl
group.
One
candidate
diketopimelic
(DKP),
a
precursor.
This
hypothesis
verified
comparing
spectrum
obtained
that
DKP
analogue
(ketopimelic
acid)
result
DFT
calculation.
results
indicate
cell
sporulation
process.
spectra
can
be
monitor
maturation
preformation
spores.
Frontiers in Microbiology,
Год журнала:
2023,
Номер
14
Опубликована: Март 22, 2023
Integrating
artificial
intelligence
and
new
diagnostic
platforms
into
routine
clinical
microbiology
laboratory
procedures
has
grown
increasingly
intriguing,
holding
promises
of
reducing
turnaround
time
cost
maximizing
efficiency.
At
least
one
billion
people
are
suffering
from
fungal
infections,
leading
to
over
1.6
million
mortality
every
year.
Despite
the
increasing
demand
for
diagnosis,
current
approaches
suffer
manual
bias,
long
cultivation
(from
days
months),
low
sensitivity
(only
50%
produce
positive
cultures).
Delayed
inaccurate
treatments
consequently
lead
higher
hospital
costs,
mobility
rates.
Here,
we
developed
single-cell
Raman
spectroscopy
achieve
rapid
identification
infectious
fungi.
The
classification
between
fungi
bacteria
infections
was
initially
achieved
with
100%
specificity
using
spectra
(SCRS).
Then,
constructed
a
dataset
isolates
obtained
94
patients,
consisting
115,129
SCRS.
By
training
model
an
optimized
feedback
loop,
just
5
cells
per
patient
(acquisition
2
s
cell)
made
most
accurate
classification.
This
protocol
accuracies
at
species
level.
transformed
assessing
samples
urinary
tract
infection,
obtaining
correct
diagnosis
raw
sample-to-result
within
1
h.
Current Opinion in Biotechnology,
Год журнала:
2023,
Номер
83, С. 102975 - 102975
Опубликована: Авг. 11, 2023
Single-cell
analysis
can
unravel
functional
heterogeneity
within
cell
populations
otherwise
obscured
by
ensemble
measurements.
However,
noninvasive
techniques
that
probe
chemical
entities
and
their
dynamics
are
still
lacking.
This
challenge
could
be
overcome
novel
sensors
based
on
nitrogen-vacancy
(NV)
centers
in
diamond,
which
enable
nuclear
magnetic
resonance
(NMR)
spectroscopy
unprecedented
sample
volumes.
In
this
perspective,
we
briefly
introduce
NV-based
quantum
sensing
review
the
progress
made
microscale
NV-NMR
spectroscopy.
Last,
discuss
approaches
to
enhance
sensitivity
of
NV
magnetometers
detect
biologically
relevant
concentrations
provide
a
roadmap
toward
application
single-cell
analysis.
Frontiers in Microbiology,
Год журнала:
2023,
Номер
14
Опубликована: Янв. 26, 2023
Respiratory
infections
rank
fourth
in
the
global
economic
burden
of
disease.
Lower
respiratory
tract
are
leading
cause
death
low-income
countries.
The
rapid
identification
pathogens
causing
lower
to
help
guide
use
antibiotics
can
reduce
mortality
patients
with
infections.
Single-cell
Raman
spectroscopy
is
a
“whole
biological
fingerprint”
technique
that
be
used
identify
microbial
samples.
It
has
advantages
no
marking
and
fast
non-destructive
testing.
In
this
study,
single-cell
was
collect
spectral
data
six
pathogen
isolates.
T-distributed
stochastic
neighbor
embedding
(t-SNE)
isolation
analysis
algorithm
compare
differences
between
pathogens.
eXtreme
Gradient
Boosting
(XGBoost)
establish
phenotype
database
model.
classification
accuracy
isolated
samples
93–100%,
clinical
more
than
80%.
Combined
heavy
water
labeling
technology,
drug
resistance
determined.
study
showed
spectroscopy–D
2
O
(SCRS–D
O)
could
rapidly
within
h.
Heliyon,
Год журнала:
2024,
Номер
10(6), С. e27824 - e27824
Опубликована: Март 1, 2024
In
a
previous
publication,
we
trained
predictive
models
based
on
Raman
bulk
spectra
of
microorganisms
placed
silicon
dioxide
protected
silver
mirror
slide
to
make
predictions
for
new
spectra,
unknown
the
models,
different
substrate,
namely
stainless
steel.
Now
have
combined
large
sections
this
data
and
convolutional
neural
network
(CNN)
single
cell
spectra.
We
show
that
database
microbial
material
is
conditionally
suited
same
species
in
terms
cells.
Data
13
(bacteria
yeasts)
were
used.
Two
could
be
identified
90%
correctly
five
other
71%–88%.
The
six
remaining
predicted
by
only
0%–49%.
Especially
stronger
fluorescence
compared
cells
but
also
photodegradation
carotenoids
are
some
effects
can
complicate
data.
results
helpful
assessing
universal
tools
or
databases.
Journal of Raman Spectroscopy,
Год журнала:
2025,
Номер
unknown
Опубликована: Март 22, 2025
ABSTRACT
Bacterial
discrimination
using
single‐cell
Raman
spectroscopy
and
machine/deep
learning
techniques
has
been
widely
explored
for
promising
applications
in
medical,
environmental,
food
sciences.
To
construct
a
machine‐learning
model
that
can
achieve
highly
accurate
robust
of
bacteria
real‐world
samples,
data
consisting
spectra
bacterial
cells
acquired
under
various
physiological
conditions
are
essential.
Despite
much
effort
to
study
the
effects
growth
phase
on
discrimination,
it
is
not
yet
fully
elucidated
which
phase(s)
needs
be
included
training
efficiently
improve
accuracy
what
phase‐dependent
changes
cellular
components
underlie
discrimination.
Here,
we
used
random
forest
(RF),
an
ensemble
machine
method,
discriminate
six
species,
including
both
Gram‐positive
Gram‐negative
bacteria,
at
five
different
phases
ranging
from
lag
late
stationary
phases.
We
compared
four
RF
classification
models
were
trained
one
(either
midexponential
or
stationary),
two
(midexponential
all
The
species
built
distinctly
exceeded
80%
with
marked
increase
24%
32.5%
relative
single
phase.
This
was
greater
than
found
going
(13%).
also
revealed
bands
relatively
invariant
(e.g.,
proteins)
specific
DNA/RNA
intracellular
storage
materials)
important
attaining
present
provides
simple
effective
way
good
performance,
could
extended
other
such
as
nutrient,
temperature,
pH.
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Фев. 22, 2024
Abstract
Early
diagnosis
remains
of
pivotal
importance
in
reducing
patient
morbidity
and
mortality
cancer.
To
this
end,
liquid
biopsy
is
emerging
as
a
tool
to
perform
broad
cancer
screenings.
Small
extracellular
vesicles
(sEVs),
also
called
exosomes,
found
bodily
fluids
can
serve
important
biomarkers
these
Our
group
has
recently
developed
label-free
electrokinetic
microchip
purify
sEVs
from
blood.
Herein,
we
demonstrate
the
feasibility
integrate
approach
with
surface-enhanced
Raman
scattering
(SERS)
analysis.
SERS
be
used
characterized
extracted
through
their
vibrational
fingerprint
that
changes
depending
on
origin
sEVs.
While
are
not
easily
identified
spectra,
they
modeled
machine
learning
(ML)
approaches.
Common
ML
approaches
field
spectral
analysis
use
dimensionality
reduction
method
often
function
black
box.
avoid
pitfall,
Shapley
additive
explanations
(SHAP)
type
explainable
AI
(XAI)
bridges
models
human
comprehension
by
calculating
specific
contribution
individual
features
model’s
predictions,
directly
correlating
model/decisions
original
data.
Using
demonstrated
proof-of-concept
model
predictive
isolated
sEVs,
integrating
device
SERS.
This
work
explores
diagnostic
complex
data
clinical
samples,
while
reporting
interpretable
biochemical
information.