Alpha lipoamide inhibits diabetic kidney fibrosis via improving mitochondrial function and regulating RXRα expression and activation.

Previous studies have shown mitochondrial dysfunction in various acute kidney injuries and chronic kidney diseases. Lipoic acid exerts potent effects on oxidant stress and modulation of mitochondrial function in damaged organ. In this study we investigated whether alpha lipoamide (ALM), a derivative of lipoic acid, exerted a renal protective effect in a type 2 diabetes mellitus mouse model. 9-week-old db/db mice were treated with ALM (50 mg·kg-1·d-1, i.g) for 8 weeks. We showed that ALM administration did not affect blood glucose levels in db/db mice, but restored renal function and significantly improved fibrosis of kidneys. We demonstrated that ALM administration significantly ameliorated mitochondrial dysfunction and tubulointerstitial fibrotic lesions, along with increased expression of CDX2 and CFTR and decreased expression of ß-catenin and Snail in kidneys of db/db mice. Similar protective effects were observed in rat renal tubular epithelial cell line NRK-52E cultured in high-glucose medium following treatment with ALM (200 µM). The protective mechanisms of ALM in diabetic kidney disease (DKD) were further explored: Autodock Vina software predicted that ALM could activate RXRα protein by forming stable hydrogen bonds. PROMO Database predicted that RXRα could bind the promoter sequences of CDX2 gene. Knockdown of RXRα expression in NRK-52E cells under normal glucose condition suppressed CDX2 expression and promoted phenotypic changes in renal tubular epithelial cells. However, RXRα overexpression increased CDX2 expression which in turn inhibited high glucose-mediated renal tubular epithelial cell injury. Therefore, we reveal the protective effect of ALM on DKD and its possible potential targets: ALM ameliorates mitochondrial dysfunction and regulates the CDX2/CFTR/ß-catenin signaling axis through upregulation and activation of RXRα. Schematic figure illustrating that ALM alleviates diabetic kidney disease by improving mitochondrial function and upregulation and activation of RXRα, which in turn upregulated CDX2 to exert an inhibitory effect on ß-catenin activation and nuclear translocation. RTEC renal tubular epithelial cell. ROS Reactive oxygen species. RXRα Retinoid X receptor-α. Mfn1 Mitofusin 1. Drp1 dynamic-related protein 1. MDA malondialdehyde. 4-HNE 4-hydroxynonenal. T-SOD Total-superoxide dismutase. CDX2 Caudal-type homeobox transcription factor 2. CFTR Cystic fibrosis transmembrane conductance regulator. EMT epithelial mesenchymal transition. α-SMA Alpha-smooth muscle actin. ECM extracellular matrix. DKD diabetic kidney disease. Schematic figure was drawn by Figdraw ( www.figdraw.com ).

Atorvastatin Restores PPARα Inhibition of Lipid Metabolism Disorders by Downregulating miR-21 Expression to Improve Mitochondrial Function and Alleviate Diabetic Nephropathy Progression.

Atorvastatin is a classical lipid-lowering drug. It has been reported to have renoprotective effects, such as reducing urinary protein excretion and extracellular matrix aggregation. The present study aimed to investigate the specific mechanism of action of Atorvastatin in type 1 diabetic mice (T1DM) in inhibiting renal tubular epithelial cell injury following treatment with high glucose and high fat. The anti-injury mechanism of Atorvastatin involved the inhibition of miR-21 expression and the upregulation of the transcription and expression of its downstream gene Peroxisome proliferator-activated receptors-α(PPARα). An increase in blood glucose and lipid levels was noted in the T1DM model, which was associated with renal fibrosis and inflammation. These changes were accompanied by increased miR-21 levels, downregulation of PPARα and Mfn1 expressions, and upregulation of Drp1 and IL6 expressions in renal tissues. These phenomena were reversed following the administration of Atorvastatin. miR-21 targeted PPARα by inhibiting its mRNA translation. Inhibition of miR-21 expression or Fenofibrate (PPARα agonist) administration prevented the decrease of PPARα in renal tubular epithelial cells under high glucose (HG) and high fat (Palmitic acid, PA) conditions, alleviating lipid metabolism disorders and reducing mitochondrial dynamics and inflammation. Consistent with the in vivo results, the in vitro findings also demonstrated that mRTECs administered with Atorvastatin in HG + PA increased PPARα expression and restored the normal expression of Mfn1 and Drp1, and effectively increasing the number of biologically active mitochondria and ATP content, reducing ROS production, and restoring mitochondrial membrane potential following Atorvastatin intervention. In addition, these effects were noted to the inhibition of FN expression and tubular cell inflammatory response; however, in the presence of miR-21mimics, the aforementioned effects of Atorvastatin were significantly diminished. Based on these observations, we conclude that Atorvastatin inhibits tubular epithelial cell injury in T1DM with concomitant induction of lipid metabolism disorders by a mechanism involving inhibition of miR-21 expression and consequent upregulation of PPARα expression. Moreover, Atorvastatin regulated lipid metabolism homeostasis and PPARα to restore mitochondrial function. The results emphasize the potential of Atorvastatin to exhibit lipid-regulating functions and non-lipid effects that balance mitochondrial dynamics.

Senescent renal tubular epithelial cells activate fibroblasts by secreting Shh to promote the progression of diabetic kidney disease.

Introduction: Diabetic kidney disease (DKD) is one of the complications of diabetes; however, the pathogenesis is not yet clear. A recent study has shown that senescence is associated with the course of DKD. In the present study, we explored whether senescent renal tubular cells promote renal tubulointerstitial fibrosis by secreting Sonic hedgehog (Shh) which mediates fibroblast activation and proliferation in DKD. Methods: A 36-week-old db/db mice model and the renal tubular epithelial cells were cultured in high glucose (HG, 60 mmol/L) medium for in vivo and in vitro experiments. Results: Compared to db/m mice, blood glucose, microalbuminuria, serum creatinine, urea nitrogen, and UACR (microalbuminuria/urine creatinine) were markedly increased in db/db mice. Collagen III, monocyte chemoattractant protein-1 (MCP-1), and tumor necrosis factor-alpha (TNF-α) were also increased in db/db mice kidneys, suggesting fibrosis and inflammation in the organ. Moreover, the detection of SA-ß-galactosidase (SA-ß-Gal) showed that the activity of SA-ß-Gal in the cytoplasm of renal tubular epithelial cells increased, and the cell cycle inhibition of the expression of senescence-related gene cell cycle inhibitor p16 INK4A protein and p21 protein increased, indicating that renal fibrosis in db/db mice was accompanied by cell senescence. Furthermore, Shh is highly expressed in the injured renal tubules and in the kidney tissue of db/db mice, as detected by enzyme-linked immunosorbent assay (ELISA). The results of immunofluorescence staining showed increased positive staining for Shh in renal tubular epithelial cells of db/db mice and decreased positive staining for Lamin B1, but increased positive staining for γH2A.X in cells with high Shh expression; similar results were obtained in vitro. In addition, HG stimulated renal tubular epithelial cells to secrete Shh in the supernatant of the medium. D-gal treatment of renal tubular epithelial cells increased the protein levels of Shh and p21. We also found enhanced activation and proliferation of fibroblasts cultured with the supernatant of renal tubular epithelial cells stimulated by HG medium but the proliferative effect was significantly diminished when co-cultured with cyclopamine (CPN), an inhibitor of the Shh pathway. Discussion: In conclusion, HG induces renal tubular epithelial cell senescence, and the secretion of senescence-associated proteins and Shh mediates inflammatory responses and fibroblast activation and proliferation, ultimately leading to renal fibrosis.

First Human Results With the 256 Channel Intelligent Micro Implant Eye (IMIE 256).

Purpose: To report on the safety and efficacy of the 256-channel Intelligent Micro Implant Eye epiretinal prosthesis system (IMIE 256). Methods: The IMIE 256 implants were implanted in the right eyes of five subjects with end-stage retinitis pigmentosa. Following implantation, the subjects underwent visual rehabilitation training for 90 days, and their visual performance was evaluated using the grating visual acuity test, Tumbling E visual acuity test, direction of motion, square localization, and orientation and mobility test. To evaluate the safety of the IMIE 256, all adverse events were recorded. Results: Subjects performed significantly better on all evaluations with the IMIE 256 system on as compared with the performance at baseline or with the system off. There was a steady improvement in performance at each observation interval, indicating that the training and/or practice helped the subjects use the IMIE 256. There were two serious adverse events-electrode array movement and low intraocular pressure in one subject, which resolved with surgery. There were no other adverse events observed except those expected in the course of postoperative healing. Conclusions: These results show an improved safety and efficacy profile compared with that of the Argus II implant. Further clinical trials are needed to confirm these results in a larger number of subjects and over longer durations. Translational Relevance: To our knowledge, this study reports the first in-human data from a high-density (256 electrodes) epiretinal implant to restore sight to a subset of blind patients.

The role of CDX2 in renal tubular lesions during diabetic kidney disease.

Renal tubules are vulnerable targets of various factors causing kidney injury in diabetic kidney disease (DKD), and the degree of tubular lesions is closely related to renal function. Abnormal renal tubular epithelial cells (RTECs) differentiation and depletion of cell junction proteins are important in DKD pathogenesis. Caudal-type homeobox transcription factor 2 (CDX2), represents a key nuclear transcription factor that maintains normal proliferation and differentiation of the intestinal epithelium. The present study aimed to evaluate the effects of CDX2 on RTECs differentiation and cell junction proteins in DKD. The results demonstrated that CDX2 was mainly localized in renal tubules, and downregulated in various DKD models. CDX2 upregulated E-cadherin and suppressed partial epithelial-mesenchymal transition (EMT), which can alleviate hyperglycemia-associated RTECs injury. Cystic fibrosis transmembrane conductance regulator (CFTR) was regulated by CDX2 in NRK-52E cells, and CFTR interfered with ß-catenin activation by binding to Dvl2, which is an essential component of Wnt/ß-catenin signaling. CFTR knockdown abolished the suppressive effects of CDX2 on Wnt/ß-catenin signaling, thereby upregulating cell junction proteins and inhibiting partial EMT in RTECs. In summary, CDX2 can improve renal tubular lesions during DKD by increasing CFTR amounts to suppress the Wnt/ß-catenin signaling pathway.

EI24 alleviates renal interstitial fibrosis through inhibition of epithelial-mesenchymal transition and fibroblast activation.

Etoposide-induced 2.4 (EI24) exerts tumor suppressor activity through participating in cell apoptosis, autophagy, and inflammation. However, its role in renal diseases has not been elucidated. This study showed that the EI24 level decreased gradually in the kidneys of mice with unilateral ureteral obstruction (UUO) and in another fibrosis model induced by diabetic kidney disease. The overexpression of EI24 was used to investigate the possible role both in vivo and in vitro. The overexpression 1 day after UUO through tail vein injection alleviated the progression of renal interstitial fibrosis (RIF). EI24 inhibited epithelial-mesenchymal transition, excessive deposition of the extracellular matrix, and activation of fibroblasts. Furthermore, administration of EI24-overexpressing plasmids restrained the phosphorylation of nuclear factor-κB (NF-κB) and c-Jun kinase (JNK) through regulating the proteasome-dependent degradation of TRAF2, and then, inhibited the expression of downstream inflammation-associated cytokines (interleukin-6, tumor necrosis factor-α, and monocyte chemotactic protein-1) and infiltration of macrophages and neutrophils in mouse kidney after UUO. In conclusion, the data indicated that EI24, a novel anti-fibrosis regulator, was important in the progression of RIF.

Convolutional Correlation Analysis for Enhancing the Performance of SSVEP-Based Brain-Computer Interface.

Currently, most of the high-performance models for frequency recognition of steady-state visual evoked potentials (SSVEPs) are linear. However, SSVEPs collected from different channels can have non-linear relationship among each other. Linearly combining electroencephalogram (EEG) from multiple channels is not the most accurate solution in SSVEPs classification. To further improve the performance of SSVEP-based brain-computer interface (BCI), we propose a convolutional neural network-based non-linear model, i.e. convolutional correlation analysis (Conv-CA). Different from pure deep learning models, Conv-CA use convolutional neural networks (CNNs) at the top of a self-defined correlation layer. The CNNs function on how to transform multiple channel EEGs into a single EEG signal. The correlation layer calculates the correlation coefficients between the transformed single EEG signal and reference signals. The CNNs provide non-linear operations to combine EEGs in different channels and different time. And the correlation layer constrains the fitting space of the deep learning model. A comparison study between the proposed Conv-CA method and the task-related component analysis (TRCA) based methods is conducted. Both methods are validated on a 40-class SSVEP benchmark dataset recorded from 35 subjects. The study verifies that the Conv-CA method significantly outperforms the TRCA-based methods. Moreover, Conv-CA has good explainability since its inputs of the correlation layer can be analyzed for visualizing what the model learnt from the data. Conv-CA is a non-linear extension of spatial filters. Its CNN structures can be further explored and tuned for reaching a better performance. The structure of combining neural networks and unsupervised features has the potential to be applied to the classification of other signals.