Cellular cross-talk drives mesenchymal transdifferentiation in diabetic kidney disease
Arunita Chatterjee,
Jacqueline Tumarin,
Sharma Prabhakar
и другие.
Frontiers in Medicine,
Год журнала:
2025,
Номер
11
Опубликована: Янв. 7, 2025
While
changes
in
glomerular
function
and
structure
may
herald
diabetic
kidney
disease
(DKD),
many
studies
have
underscored
the
significance
of
tubule-interstitial
progression
DKD.
Indeed,
fibrosis
be
most
important
determinant
DKD
as
forms
chronic
glomerulopathies.
The
mechanisms
underlying
effects
tubular
on
intrigued
investigators,
therefore,
signaling
cross-talk
between
cells
been
focus
investigation
recent
studies.
Additionally,
observations
slowing
filtration
rate
(GFR)
decline
reduction
proteinuria
by
drugs
such
SGLT-2
blockers,
whose
primary
mechanism
action
is
proximal
tubules,
further
strengthen
concept
cells.
Recently,
research
pathogenesis
has
primarily
centered
around
exploring
various
pathways
well
endothelial
podocytes
with
special
relevance
to
epithelial-to-mesenchymal
transition
(EMT)
endothelial-to-mesenchymal
(EndoMT).
this
review
provide
a
general
description
cell-to-cell
highlight
these
concepts
evidence
relation
physiology
pathophysiology
Язык: Английский
Unraveling Diabetic Kidney Disease: The Roles of Mitochondrial Dysfunction and Immunometabolism
Kidney International Reports,
Год журнала:
2024,
Номер
9(12), С. 3386 - 3402
Опубликована: Окт. 4, 2024
Язык: Английский
Uncovering glycolysis-driven molecular subtypes in diabetic nephropathy: a WGCNA and machine learning approach for diagnostic precision
Biology Direct,
Год журнала:
2025,
Номер
20(1)
Опубликована: Янв. 21, 2025
Diabetic
nephropathy
(DN)
is
a
common
diabetes-related
complication
with
unclear
underlying
pathological
mechanisms.
Although
recent
studies
have
linked
glycolysis
to
various
states,
its
role
in
DN
remains
largely
underexplored.
In
this
study,
the
expression
patterns
of
glycolysis-related
genes
(GRGs)
were
first
analyzed
using
GSE30122,
GSE30528,
and
GSE96804
datasets,
followed
by
an
evaluation
immune
landscape
DN.
An
unsupervised
consensus
clustering
samples
from
same
dataset
was
conducted
based
on
differentially
expressed
GRGs.
The
hub
associated
clusters
identified
via
weighted
gene
co-expression
network
analysis
(WGCNA)
machine
learning
algorithms.
Finally,
these
validated
single-cell
sequencing
data
quantitative
real-time
polymerase
chain
reaction
(qRT-PCR).
Eleven
GRGs
showed
abnormal
samples,
leading
identification
two
distinct
clusters,
each
own
profile
functional
pathways.
GSE142153
that
had
specific
characteristics.
Furthermore,
Extreme
Gradient
Boosting
(XGB)
model
most
effective
diagnosing
five
significant
variables,
including
GATM,
PCBD1,
F11,
HRSP12,
G6PC,
as
for
further
investigation.
Single-cell
predominantly
proximal
tubular
epithelial
cells.
vitro
experiments
confirmed
pattern
NC.
Our
study
provides
valuable
insights
into
molecular
mechanisms
DN,
highlighting
involvement
cell
infiltration.
Язык: Английский
Personalized federated learning via decoupling self-knowledge distillation and global adaptive aggregation
Multimedia Systems,
Год журнала:
2025,
Номер
31(2)
Опубликована: Фев. 27, 2025
Язык: Английский
Identification of key genes and immune infiltration of diabetic peripheral neuropathy in mice and humans based on bioinformatics analysis
Frontiers in Endocrinology,
Год журнала:
2024,
Номер
15
Опубликована: Ноя. 18, 2024
Background
Diabetic
peripheral
neuropathy
(DPN)
is
a
common
chronic
complication
of
diabetes,
while
the
underlying
molecular
mechanisms
are
still
unclear.
The
aim
this
study
was
to
screen
key
genes
and
roles
immune
infiltration
in
DPN
using
bioinformatics
analysis.
Methods
mice
datasets
including
GSE222778,
GSE11343,
GSE70852,
GSE27382,
GSE34889
were
retrieved
from
GEO
database.
Data
human
dbGaP.
differentially
expressed
(DEGs)
selected
further
analyzed
by
Gene
Ontology,
Kyoto
Encyclopedia
Genes
Genomes
enrichment
analysis,
Set
Enrichment
Analysis
(GSEA)
find
shared
pathway.
Protein–protein
interaction
networks
built
mouse
DEGs.
hub
verified
vitro
high-
glucose-treated
PC12
cells
Schwann
cells.
single-sample
GSEA
(ssGSEA)
algorithm
used
analyze
proportions
infiltrating
subsequent
correlations
with
genes.
Results
A
total
323
DEGs
501
selected,
they
found
significantly
enriched
immune-related
biological
functions
pathways.
13
datasets,
among
them,
there
7
genes,
namely,
PLAUR,
S100A8,
IL7R,
CXCL13,
SRPX2,
CD300LB,
CFI.
expression
Cfi,
S100a8,
Cxcl13,
Cd300lb
consistently
confirmed
.
scores
neutrophils
NK
CD56bright
varied
most
cell
analysis
(
p
<
0.01).
Furthermore,
be
highly
correlated
infiltration.
Conclusion
Our
indicated
importance
dysregulations
identified
several
through
combined
samples,
thus
providing
potential
diagnostic
therapeutic
targets
future.
Язык: Английский