ShodhKosh Journal of Visual and Performing Arts,
Journal Year:
2024,
Volume and Issue:
5(6)
Published: June 30, 2024
Melanoma
detection
has
come
a
long
way,
mostly
thanks
to
breakthroughs
in
image
technologies
and
machine
learning
techniques
that
aim
make
diagnoses
more
accurate
improve
patient
results.
Traditional
like
dermoscopy
biopsy
are
still
very
important.
However,
newer
multispectral
images
computer-assisted
analysis
have
made
it
much
easier
tell
the
difference
between
normal
cancerous
tumours
early
on.
This
review
talks
about
how
melanoma
tools
changed
over
time
where
they
now.
It
also
artificial
intelligence
(AI)
is
being
used
dermatology.
Some
new
developments
high-resolution
imaging,
confocal
microscopy
optical
coherence
tomography,
offer
non-invasive
options
for
deeper
tissue
real-time
identification
of
cells,
which
can
be
important
starting
treatment
early.
Also,
improvements
teledermatology
do
screenings
from
afar,
making
people
get
expert
care
second
views,
especially
helpful
areas
don't
enough
resources.
been
forever
by
use
deep
models
look
at
pictures
skin
lesions
with
same
level
accuracy
as
doctors.
These
AI
systems
trained
on
large
datasets
help
doctors
decisions,
could
cut
down
medical
mistakes
bias.
Not
only
that,
but
AI-powered
show
lot
promise
keeping
track
change
time,
an
part
watching
melanoma.
genetic
markers
biomarkers
become
useful
finding
who
risk,
allows
proactive
control
personalised
plans.
International Journal of Molecular Sciences,
Journal Year:
2024,
Volume and Issue:
25(3), P. 1796 - 1796
Published: Feb. 1, 2024
Uveal
melanoma
(UM)
is
the
most
common
primary
intraocular
malignancy
with
a
limited
five-year
survival
for
metastatic
patients.
Limited
therapeutic
treatments
are
currently
available
disease,
even
if
genomics
of
this
tumor
has
been
deeply
studied
using
next-generation
sequencing
(NGS)
and
functional
experiments.
The
profound
knowledge
molecular
features
that
characterize
not
led
to
development
efficacious
therapies,
patients
changed
decades.
Several
bioinformatics
methods
have
applied
mine
NGS
data
in
order
unveil
biology
detect
possible
targets
new
therapies.
Each
application
can
be
single
domain
based
while
others
more
focused
on
integration
from
multiple
domains
(as
gene
expression
methylation
data).
Examples
approaches
include
differentially
expressed
(DEG)
analysis
statistical
such
as
SAM
(significance
microarray)
or
prioritization
complex
algorithms
deep
learning.
Data
fusion
merge
information
define
clusters
relevant
genes,
according
data.
In
work,
we
compare
different
strategies
genes
disease
prediction
TCGA
uveal
(UVM)
dataset.
Detected
validated
multi-gene
score
larger
UM
microarray
Immunology,
Journal Year:
2024,
Volume and Issue:
172(3), P. 486 - 499
Published: March 28, 2024
To
explore
the
effect
of
K33
only
mutant
ubiquitin
(K33O)
on
bone
marrow-derived
dendritic
cells'
(BMDCs')
maturity,
antigen
uptake
capability,
surface
molecule
expressions
and
BMDC-mediated
CTL
priming,
further
investigate
role
PI3K-Akt
engaged
in
K33O-increased
BMDC
maturation,
presentation,
BMDC-based
priming.
BMDCs
were
conferred
K33O
other
mutants
(K33R,
K48R,
K63R-mutant
ubiquitin)
incubation
or
LY294002
wortmannin
pretreatment.
phosphorylation,
uptake,
antigenic
presentation
CD86/MHC
class
I
expression
determined
by
western
blot
flow
cytometry.
proliferation
priming
vitro
mixed
lymphocyte
reaction
(MLR),
ex
vivo
enzyme-linked
immunospot
assay
(Elispot)
cytometry
with
intracellular
staining,
respectively.
The
treatment
effectively
augmented
BMDCs'
CD11c
expressions.
MLR,
Elispot
revealed
that
obviously
enhanced
proliferation,
perforin/granzyme
B
expression.
pretreatment
inhibitors
efficiently
abrogated
K33O's
effects
BMDC.
replenishment
augments
cells
via
signalling.
Research Square (Research Square),
Journal Year:
2024,
Volume and Issue:
unknown
Published: Oct. 25, 2024
Abstract
Acute
Myeloid
Leukemia
(AML)
with
KMT2A
rearrangements
(KMT2Ar),
found
on
chromosome
11q23,
is
often
called
KMT2A-rearranged
AML
(KMT2Ar-AML).
This
variant
highly
aggressive,
characterized
by
rapid
disease
progression
and
poor
outcomes.
Growing
knowledge
of
epigenetic
changes,
especially
lactylation,
has
opened
new
avenues
for
investigation
management
this
subtype.
Lactylation
plays
a
significant
role
in
cancer,
inflammation,
tissue
regeneration,
but
the
underlying
mechanisms
are
not
yet
fully
understood.
research
examined
influence
lactylation
gene
expression
within
KMT2Ar-AML,
initially
identifying
twelve
notable
lactylation-dependent
differentially
expressed
genes
(DEGs).
Using
advanced
machine
learning
techniques,
six
key
lactylation-associated
(PFN1,
S100A6,
CBR1,
LDHB,
LGALS1,
PRDX1)
were
identified
as
essential
prognostic
evaluation
linked
to
relevant
pathways.
The
study
also
suggested
PI3K
inhibitors
Pevonedistat
possible
therapeutic
options
modulate
immune
cell
infiltration.
Our
findings
confirm
critical
KMT2Ar-AML
identify
that
may
serve
biomarkers
diagnosis
treatment.
In
addition
highlighting
need
further
validation
clinical
settings,
these
contribute
our
understanding
KMT2Ar-AML's
molecular
mechanisms.
International Journal of Molecular Sciences,
Journal Year:
2024,
Volume and Issue:
25(23), P. 12974 - 12974
Published: Dec. 3, 2024
Cell
division
cycle
6
(CDC6)
is
essential
for
the
initiation
of
DNA
replication
in
eukaryotic
cells
and
contributes
to
development
various
human
tumors.
Polycystic
ovarian
syndrome
(PCOS)
a
reproductive
endocrine
disease
women
childbearing
age,
with
significant
risk
endometrial
cancer
(EC).
However,
role
CDC6
progression
PCOS
EC
unclear.
Therefore,
we
examined
expression
patients
EC.
We
evaluated
relationship
between
its
prognostic
value,
potential
biological
functions,
immune
infiltrates
In
vitro
analyses
were
performed
investigate
effects
knockdown
on
proliferation,
migration,
invasion,
apoptosis.
was
significantly
upregulated
Moreover,
this
protein
caused
by
promoting
aberrant
infiltration
macrophages
into
microenvironment
PCOS.
A
functional
enrichment
analysis
revealed
that
exerted
pro-cancer
pro-immune
cell
functions
via
PI3K-AKT
pathway.
it
promoted
invasion
but
inhibited
This
reduced
survival
when
mutated.
These
findings
demonstrate
regulates
promotes
infiltration.
Toxicology Research,
Journal Year:
2024,
Volume and Issue:
13(6)
Published: Nov. 5, 2024
Abstract
Background
Arthritis
is
a
degenerative
joint
disease
influenced
by
various
environmental
factors,
including
exposure
to
Benzophenone-3
(BP3),
common
UV
filter.
This
study
aims
elucidate
the
toxicological
impact
of
BP3
on
arthritis
pathogenesis
using
network
toxicology
approaches.
Method
We
integrated
data
from
Comparative
Toxicogenomics
Database
(CTD)
and
Gene
Expression
Omnibus
(GEO)
identify
differentially
expressed
BP3-related
targets
in
osteoarthritis
(OA).
Enrichment
analyses
were
conducted
determine
implicated
biological
processes,
cellular
components,
molecular
functions.
Further,
involvement
PI3K-Akt
signaling
pathway
was
investigated,
along
with
correlations
immune
cell
infiltration
immune-related
pathways.
Molecular
docking
analysis
performed
examine
interactions
key
proteins.
Results
A
total
74
identified.
revealed
significant
pathways,
PI3K-Akt,
MAPK,
HIF-1
signaling.
The
showed
notable
dysregulation
OA,
reduced
activity
differential
expression
genes
such
as
ANGPT1,
ITGA4,
PIK3R1.
Correlation
indicated
associations
between
types
highlighted
strong
proteins
like
AREG,
suggesting
potential
disruptions
processes.
Conclusions
significantly
alters
disrupts
PI3KAkt
pathway,
contributing
OA
pathogenesis.
These
findings
provide
insights
into
mechanisms
BP3-induced
therapeutic
for
mitigating
its
effects.
ShodhKosh Journal of Visual and Performing Arts,
Journal Year:
2024,
Volume and Issue:
5(6)
Published: June 30, 2024
Melanoma
detection
has
come
a
long
way,
mostly
thanks
to
breakthroughs
in
image
technologies
and
machine
learning
techniques
that
aim
make
diagnoses
more
accurate
improve
patient
results.
Traditional
like
dermoscopy
biopsy
are
still
very
important.
However,
newer
multispectral
images
computer-assisted
analysis
have
made
it
much
easier
tell
the
difference
between
normal
cancerous
tumours
early
on.
This
review
talks
about
how
melanoma
tools
changed
over
time
where
they
now.
It
also
artificial
intelligence
(AI)
is
being
used
dermatology.
Some
new
developments
high-resolution
imaging,
confocal
microscopy
optical
coherence
tomography,
offer
non-invasive
options
for
deeper
tissue
real-time
identification
of
cells,
which
can
be
important
starting
treatment
early.
Also,
improvements
teledermatology
do
screenings
from
afar,
making
people
get
expert
care
second
views,
especially
helpful
areas
don't
enough
resources.
been
forever
by
use
deep
models
look
at
pictures
skin
lesions
with
same
level
accuracy
as
doctors.
These
AI
systems
trained
on
large
datasets
help
doctors
decisions,
could
cut
down
medical
mistakes
bias.
Not
only
that,
but
AI-powered
show
lot
promise
keeping
track
change
time,
an
part
watching
melanoma.
genetic
markers
biomarkers
become
useful
finding
who
risk,
allows
proactive
control
personalised
plans.
