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"Zhou, Li"
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Caspase-11/4 and gasdermin D-mediated pyroptosis contributes to podocyte injury in mouse diabetic nephropathy
Diabetic nephropathy (DN) is characterized by sterile inflammation with continuous injury and loss of renal inherent parenchyma cells. Podocyte is an essential early injury target in DN. The injury and loss of podocytes are closely associated with proteinuria, the early symptom of renal injury in DN. However, the exact mechanism for podocyte injury and death in DN remains ambiguous. In this study we investigated whether pyroptosis, a newly discovered cell death pathway was involved in DN. Diabetic mice were generated by high-fat diet/STZ injections. We showed that the expression levels of caspase-11 and cleavage of gasdermin D (GSDMD-N) in podocytes were significantly elevated, accompanied by reduced expression of podocyte makers nephrin and podocin, loss and fusion in podocyte foot processes, increased inflammatory cytokines NF-κB, IL-1β, and IL-18, macrophage infiltration, glomerular matrix expansion and increased urinary albumin to creatinine ratio (UACR). All these changes in diabetic mice were blunted by knockout of caspase-11 or GSDMD. Cultured human and mouse podocytes were treated with high glucose (30 mM), which significantly increased the expression levels of caspase-11 or caspase-4 (the homolog of caspase-11 in human), GSDMD-N, NF-κB, IL-1β, and IL-18, and decreased the expression of nephrin and podocin. Either caspase-4 or GSDMD knockdown by siRNA significantly blunted these changes. In summary, our results demonstrate that caspase-11/4 and GSDMD-mediated pyroptosis is activated and involved in podocyte loss under hyperglycemia condition and the development of DN.
Journal Article
Image analysis and teaching strategy optimization of folk dance training based on the deep neural network
To improve the recognition effect of the folk dance image recognition model and put forward new suggestions for teachers’ teaching strategies, this study introduces a Deep Neural Network (DNN) to optimize the folk dance training image recognition model. Moreover, a corresponding teaching strategy optimization scheme is proposed according to the experimental results. Firstly, the image preprocessing and feature extraction of DNN are optimized. Secondly, classification and target detection models are established to analyze the folk dance training images, and the C-dance dataset is used for experiments. Finally, the results are compared with those of the Naive Bayes classifier, K-nearest neighbor, decision tree classifier, support vector machine, and logistic regression models. The results of this study provide new suggestions for teaching strategies. The research results indicate that the optimized classification model shows a significant improvement in classification accuracy across various aspects such as action complexity, dance types, movement speed, dance styles, body dynamics, and rhythm. The accuracy, precision, recall, and F1 scores have increased by approximately 14.7, 11.8, 13.2, and 17.4%, respectively. In the study of factors such as different training images, changes in perspective, lighting conditions, and noise interference, the optimized model demonstrates a substantial enhancement in recognition accuracy and robustness. These findings suggest that, compared to traditional models, the optimized model performs better in identifying various dances and movements, enhancing the accuracy and stability of classification. Based on the experimental results, strategies for optimizing the real-time feedback and assessment mechanism in folk dance teaching, as well as the design of personalized learning paths, are proposed. Therefore, this study holds the potential to be applied in the field of folk dance, promoting the development and innovation of folk dance education.
Journal Article
Notes on flat-space limit of AdS/CFT
A
bstract
Different frameworks exist to describe the flat-space limit of AdS/CFT, include momentum space, Mellin space, coordinate space, and partial-wave expansion. We explain the origin of momentum space as the smearing kernel in Poincare AdS, while the origin of latter three is the smearing kernel in global AdS. In Mellin space, we find a Mellin formula that unifies massless and massive flat-space limit, which can be transformed to coordinate space and partial-wave expansion. Furthermore, we also manage to transform momentum space to smearing kernel in global AdS, connecting all existed frameworks. Finally, we go beyond scalar and verify that
VV
O
maps to photon-photon-massive amplitudes.
Journal Article
Seasonal and diurnal patterns of non-structural carbohydrates in source and sink tissues in field maize
Background
Carbohydrate partitioning and utilization is a key determinant of growth rate and of yield in plants and crops. There are few studies on crops in field conditions. In
Arabidopsis
, starch accumulation in leaves is a negative indicator of growth rate.
Results
Here, we wished to establish if starch accumulation in leaves could potentially be a marker for growth rate and yield in crops such as maize. We characterized daily patterns of non-structural carbohydrate (NSC) at different growth stages over two seasons for maize hybrids in the field. In 27 commercial hybrids, we found a significant negative relationship between residual starch in leaves and plant growth, but not with final yield and biomass. We then focused on three typical hybrids and established a method for calculation of C turnover in photosynthetic leaves that took into account photosynthesis, leaf area and NSC accumulation. The ratios of stored NSC decreased from approximately 15% to less than 4% with ongoing ontogeny changes from V7 to 28 days after pollination.
Conclusion
The proportion rather than absolute amount of carbon partitioned to starch in leaves at all stages of development related well with yield and biomass accumulation. It is proposed that screening plants at an early vegetative growth stage such as V7 for partitioning into storage may provide a prospective method for maize hybrid selection. Our study provides the basis for further validation as a screening tool for yield.
Journal Article
Heavy-light bootstrap from Lorentzian inversion formula
A
bstract
We study heavy-light four-point function by employing Lorentzian inversion formula, where the conformal dimension of heavy operator is as large as central charge
C
T
→ ∞
. We implement the Lorentzian inversion formula back and forth to reveal the universality of the lowest-twist multi-stress-tensor
T
k
as well as large spin double-twist operators
O
H
O
L
n
′
,
J
′
. In this way, we also propose an algorithm to bootstrap the heavy- light four-point function by extracting relevant OPE coefficients and anomalous dimensions. By following the algorithm, we exhibit the explicit results in
d
= 4 up to the triple-stress- tensor. Moreover, general dimensional heavy-light bootstrap up to the double-stress-tensor is also discussed, and we present an infinite series representation of the lowest-twist double- stress-tensor OPE coefficient. Exact expressions of lowest-twist double-stress-tensor OPE coefficients in
d
= 6
,
8
,
10 are also obtained as further examples.
Journal Article
Evaluation of fecal microbiota transplantation in Parkinson's disease patients with constipation
Parkinson’s disease (PD) is a neurodegenerative disorder and 70–80% of PD patients suffer from gastrointestinal dysfunction such as constipation. We aimed to assess the efficacy and safety of fecal microbiota transplantation (FMT) for treating PD related to gastrointestinal dysfunction. We conducted a prospective, single- study. Eleven patients with PD received FMT. Fecal samples were collected before and after FMT and subjected to 16S ribosomal DNA (rDNA) gene sequencing. Hoehn-Yahr (H-Y) grade, Unified Parkinson's Disease Rating Scale (UPDRS) score, and the Non-Motion Symptom Questionnaire (NMSS) were used to assess improvements in motor and non-motor symptoms. PAC-QOL score and Wexner constipation score were used to assess the patient's constipation symptoms. All patients were tested by the small intestine breath hydrogen test, performed before and after FMT. Community richness (chao) and microbial structure in before-FMT PD patients were significantly different from the after-FMT. We observed an increased abundance of
Blautia
and
Prevotella
in PD patients after FMT, while the abundance of
Bacteroidetes
decreased dramatically. After FMT, the H-Y grade, UPDRS, and NMSS of PD patients decreased significantly. Through the lactulose H2 breath test, the intestinal bacterial overgrowth (SIBO) in PD patients returned to normal. The PAC-QOL score and Wexner constipation score in after-FMT patients decreased significantly. Our study profiles specific characteristics and microbial dysbiosis in the gut of PD patients. FMT might be a therapeutic potential for reconstructing the gut microbiota of PD patients and improving their motor and non-motor symptoms.
Journal Article
Itaconate inhibits TET DNA dioxygenases to dampen inflammatory responses
As one of the most induced genes in activated macrophages,
immune-responsive gene 1
(
IRG1
) encodes a mitochondrial metabolic enzyme catalysing the production of itaconic acid (ITA). Although ITA has an anti-inflammatory property, the underlying mechanisms are not fully understood. Here we show that ITA is a potent inhibitor of the TET-family DNA dioxygenases. ITA binds to the same site on TET2 as the co-substrate α-ketoglutarate, inhibiting TET2 catalytic activity. Lipopolysaccharide treatment, which induces Irg1 expression and ITA accumulation, inhibits Tet activity in macrophages. Transcriptome analysis reveals that TET2 is a major target of ITA in suppressing lipopolysaccharide-induced genes, including those regulated by the NF-κB and STAT signalling pathways. In vivo, ITA decreases the levels of 5-hydroxymethylcytosine, reduces lipopolysaccharide-induced acute pulmonary oedema as well as lung and liver injury, and protects mice against lethal endotoxaemia, depending on the catalytic activity of Tet2. Our study thus identifies ITA as an immune modulatory metabolite that selectively inhibits TET enzymes to dampen the inflammatory responses.
Chen et al. report that the immune modulatory metabolite itaconic acid selectively inhibits the activity of TET DNA dioxygenases to repress the inflammatory responses.
Journal Article