Application Potential of Extracellular Vesicles Derived From Mesenchymal Stem Cells in Renal Diseases.

The high prevalence and complex etiology of renal diseases already impose a heavy disease burden on patients and society. In certain kidney diseases such as acute kidney injury and chronic kidney disease, current treatments are limited to slowing rather than stabilizing or reversing disease progression. Therefore, it is crucial to study the pathological mechanisms of kidney disease and discover new therapeutic targets and effective therapeutic drugs. As cell-free therapeutic strategies are continually being developed, extracellular vesicles derived from mesenchymal stem cells (MSC-EVs) have emerged as a hot topic for research in the field of renal diseases. Studies have demonstrated that MSC-EVs not only reproduce the therapeutic effects of MSCs but also localize to damaged kidney tissue. Compared to MSCs, MSC-EVs have several advantages, including ease of preservation, low immunogenicity, an inability to directly form tumors, and ease of artificial modification. Exploring the detailed mechanisms of MSC-EVs by developing standardized culture, isolation, purification, and drug delivery strategies will help facilitate their clinical application in kidney diseases. Here, we provide a comprehensive overview of studies about MSC-EVs in kidney diseases and discuss their limitations at the human nephrology level.

Neferine mitigates cisplatin-induced acute kidney injury in mice by regulating autophagy and apoptosis.

PURPOSE: The nephrotoxicity caused by cisplatin severely limits the application and affects related platinum-based therapeutics. Neferine is a dibenzylisoquinoline alkaloid extracted from a Chinese medicinal herb (Nelumbo nucifera Gaertn), which can decrease cisplatin-induced apoptosis of NRK-52E cells by activating autophagy in vitro in our previous study. In this article, we aimed to further investigate the protective effect of neferine, against to the cispltain-induced kidney damage in mice. METHODS: Six groups were designed in our study. Renal index, mice serum creatinine and blood urea nitrogen levels were detected after the mice were killed. HE staining was used to observe the pathological changes of each group. The apoptosis of mouse kidney tissue was detected by TUNEL. Immunofluorescence and Western blot were used to detect the expression of cleaved-caspase3 and LC3. The transmission electron microscope was used to reveal the changes of apoptosis and autophagy of renal tubular epithelial cells in different groups. RESULTS: In our findings, the pathological changes of acute kidney injury were easily observed in cisplatin-treated mice while those in the neferine-pretreated groups were significantly alleviated. The apoptosis induced by cisplatin in mice increased evidently compared with the control group, which was decreased in the mice with neferine pretreatment. What' more, we found that autophagy increased obviously in mice pretreated by neferine contrast to the cisplatin-treated mice. CONCLUSION: In our study, neferine can effectively alleviate cisplatin-induced renal injury in mice, as well act as an autophagy-regulator in kidney protection.

Elevation of LncRNA ENST00000453774.1 Prevents Renal Fibrosis by Upregulating FBN1, IGF1R, and KLF7.

INTRODUCTION: Transforming growth factor-ß (TGF-ß), a common outcome of various progressive chronic kidney diseases, can regulate and induce fibrosis. OBJECTIVE: The study aimed to identify downstream targets of lncRNA ENST00000453774.1 (lnc453774.1) and outline their functions on the development of renal fibrosis. METHODS: HK-2 cells were induced with 5 ng/mL TGF-ß1 for 24 h to construct a renal fibrosis cell model. Differentially expressed genes (DEGs) targeted by lnc453774.1 in TGF-ß1-induced renal fibrosis were identified using RNA sequencing. The dataset GSE23338 was employed to identify DEGs in 48-h TGF-ß1-stimulated human kidney epithelial cells, and these DEGs were intersected with genes in the key module using weighted gene co-expression network analysis to generate key genes associated with renal fibrosis. MicroRNAs (miRs) that had targeting relationship with keys genes and lnc453774.1 were predicted by using Miranda software, and important genes were intersected with key genes that had targeting relationship with these miRs. Key target genes by lnc453774.1 were identified in a protein-protein interaction network among lnc453774.1, important genes, and reported genes related to autophagy, oxidative stress, and cell adhesion. RESULTS: Key genes in the key module (turquoise) were intersected with DEGs in the dataset GSE23338 and yielded 20 key genes regulated by lnc453774.1 involved in renal fibrosis. Fourteen miRs had targeting relationship with lnc453774.1 and key genes, and 8 important genes targeted by these 14 miRs were identified. Fibrillin-1 (FBN1), insulin-like growth factor 1 receptor (IGF1R), and Kruppel-like factor 7 (KLF7) were identified to be involved in autophagy, oxidative stress, and cell adhesion and were elevated in the lnc453774.1-overexpressing TGF-ß1-induced cells. CONCLUSION: These results show FBN1, IGF1R, and KLF7 serve as downstream targets of lnc453774.1, and that lnc453774.1 may protect against renal fibrosis through competing endogenous miRs which target FBN1, IGF1R, and KLF7 mRNAs.

The epidemiology and clinical information about COVID-19.

In December 2019, pneumonia of unknown cause occurred in Wuhan, Hubei Province, China. On 7 January 2020, a novel coronavirus, named as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), was identified in the throat swab sample of one patient. The World Health Organization (WHO) announced the epidemic disease caused by SARS-CoV-2 as coronavirus disease 2019 (COVID-19). Currently, COVID-19 has spread widely around the world, affecting more than seventy countries. China, with a huge burden of this disease, has taken strong measures to control the spread and improve the curative rate of COVID-19. In this review, we summarized the epidemiological characteristics, clinical features, diagnosis, treatment, and prognosis of COVID-19. A comprehensive understanding will help to control the disease.

Role of Artificial Intelligence in Kidney Disease.

Artificial intelligence (AI), as an advanced science technology, has been widely used in medical fields to promote medical development, mainly applied to early detections, disease diagnoses, and management. Owing to the huge number of patients, kidney disease remains a global health problem. Challenges remain in its diagnosis and treatment. AI could take individual conditions into account, produce suitable decisions and promise to make great strides in kidney disease management. Here, we review the current studies of AI applications in kidney disease in alerting systems, diagnostic assistance, guiding treatment and evaluating prognosis. Although the number of studies related to AI applications in kidney disease is small, the potential of AI in the management of kidney disease is well recognized by clinicians; AI will greatly enhance clinicians' capacity in their clinical practice in the future.

A survey on acute kidney injury in severely and critically ill COVID-19 patients without chronic kidney disease.

BACKGROUND: Research has shown that acute kidney injury (AKI) has a noticeable incidence in critically ill patients with coronavirus disease 2019 (COVID-19). Patients with prior renal insufficiency are particularly susceptible to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), due to their immune dysfunction. However, most patients with COVID-19 do not have a history of kidney dysfunction, and few studies have focused on the incidence of AKI among COVID-19 patients without chronic kidney disease (CKD). In this study, we aimed to investigate the occurrence of AKI in severely and critically ill COVID-19 patients, with a particular focus on those without a CKD history. METHODS: A single-center retrospective study of 96 patients with COVID-19 in China between February 7 and March 3, 2020 was conducted. All patients were diagnosed by nucleic acid test (NAT) for SARS-CoV-2. Enrolled patients were divided into the severely or critically ill group according to the defined criteria. Patients' epidemiological, clinical, and laboratory characteristics, along with their treatment information, were collected from the medical history system. The occurrence of AKI was compared between the severe and critical patients, and between patients with or without a history of CKD. The diagnostic criteria for AKI included an increase in the serum creatinine level to ≥1.5-fold the level at baseline within 7 days according to the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines. Renal outcomes were defined as AKI or non-AKI. RESULTS: Four patients (4.2%) developed AKI, all of whom were in the critically ill group, and 3 (75%) of whom died. Out of the 90 severely and critically ill COVID-19 patients without CKD, 3 (3.3%) patients developed AKI; out of the 6 patients with CKD, 1 (16.7%) patient developed AKI. Age, disease severity, procalcitonin, C-reactive protein, and interleukin-6 were correlated with AKI onset in severely and critically ill COVID-19 patients, while lymphocyte count and estimated glomerular filtration rate at admission were inversely related to the development of AKI. CONCLUSIONS: Only 3.3% of severely and critically ill COVID-19 patients without CKD in our research cohort developed AKI. Critically ill patients may be more susceptible to AKI than severely ill patients.

Identification of C3 as a therapeutic target for diabetic nephropathy by bioinformatics analysis.

The pathogenesis of diabetic nephropathy is not completely understood, and the effects of existing treatments are not satisfactory. Various public platforms already contain extensive data for deeper bioinformatics analysis. From the GSE30529 dataset based on diabetic nephropathy tubular samples, we identified 345 genes through differential expression analysis and weighted gene coexpression correlation network analysis. GO annotations mainly included neutrophil activation, regulation of immune effector process, positive regulation of cytokine production and neutrophil-mediated immunity. KEGG pathways mostly included phagosome, complement and coagulation cascades, cell adhesion molecules and the AGE-RAGE signalling pathway in diabetic complications. Additional datasets were analysed to understand the mechanisms of differential gene expression from an epigenetic perspective. Differentially expressed miRNAs were obtained to construct a miRNA-mRNA network from the miRNA profiles in the GSE57674 dataset. The miR-1237-3p/SH2B3, miR-1238-5p/ZNF652 and miR-766-3p/TGFBI axes may be involved in diabetic nephropathy. The methylation levels of the 345 genes were also tested based on the gene methylation profiles of the GSE121820 dataset. The top 20 hub genes in the PPI network were discerned using the CytoHubba tool. Correlation analysis with GFR showed that SYK, CXCL1, LYN, VWF, ANXA1, C3, HLA-E, RHOA, SERPING1, EGF and KNG1 may be involved in diabetic nephropathy. Eight small molecule compounds were identified as potential therapeutic drugs using Connectivity Map.

Clinical characteristics of acute glomerulonephritis with presentation of nephrotic syndrome at onset in children.

BACKGROUND: Acute glomerulonephritis (AGN) is a common disease in children, which places a huge burden on developing countries. The prognosis of it may not always be good. However, the clinical characteristics of AGN with nephrotic syndrome (NS) at onset have not been fully clarified. METHODS: One hundred and thirteen cases were analyzed retrospectively. Clinical data, pathological results and prognosis between AGN with NS (AGN-NS) and AGN without NS (AGN-no-NS) were compared. RESULTS: Twenty (17.7%) of 113 patients were AGN-NS. The patients with AGN-NS were more likely to have hypertension (55.0% vs. 25.8%) and acute kidney injury (AKI) (50.0% vs. 17.2%). AKI was significantly related to the manifestation of AGN-NS in children (OR = 3.812, P = 0.040). Compared with the AGN-no-NS, the immunosuppressive treatments were more common in AGN-NS. A more severe pathological grade was significantly related to lower C3 fraction, estimated glomerular filtration rate (eGFR), and AKI, but not to the performance of AGN-NS. There was no difference in prognosis between the two groups. CONCLUSIONS: AKI was significantly associated with AGN-NS. The prognosis of AGN-NS and AGN-no-NS in our study was almost good. Given the fact that AGN-NS patients are more likely to use immunosuppressive therapy, the long-term outcome of AGN-NS warrants further research.