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Acute Kidney Injury - BioProject

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Last Updated: 25 September 2022

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Single-cell transcriptomics reveals common epithelial response patterns in human acute kidney injury

Background: Acute kidney disease is common in critically ill patients and is associated with adverse outcomes. Individuals without AKI had renal tissue controls during or post-mortem and after nephrectomy from individuals without AKI. Results: The study of human kidneys affected by AKI revealed enrichment of novel injury-related cell states within the tubular epithelium's four key cell types, including in proximal tubules, thickening limbs, and distal convoluted tubules. Personal molecular responses were largely triggered by the cell type-specific abundance of these four injury subtypes rather than by individual molecular responses. Both individuals with and without COVID-19 were similar, with AKI-related changes in gene expression between people with and without COVID-19 being similar. AKI's personalized molecular disease evaluation may lead to the development of customized therapies. Overall strategy: In https://www. biorxiv. org/content/2021. 11. 15. 472619v1. jpg/content/2021. 12. 15. 472619v1.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/866508


Integrative analysis of renal microRNA and mRNA to identify hub genes and pivotal pathways associated with Cyclosporine-induced acute kidney injury in mice

Cyclosporine is a commonly used immunosuppressive drug that causes acute kidney injury in children. Microbiology and RNA-sequence analyses revealed 25 differentially expressed miRNAs and RNA-sequence analyses, resulting in the discovery of 971 putative target genes for further bioinformatics research. According to Network analysis, mmu-miR-17-5p, mmu-miR-19b-3p, mmu-423-5p, and mmu-423-5p are the top miRNAs with the highest degree from the miRNA regulatory network with the highest degree from miRNA regulatory network. Moreover, the change of expression change of mmu-miR-17-5p, mmu-miR-19b-3p, mmu-423-5p, in real-time PCR results was consistent with small RNA-sequence results, according to small RNA-sequence results. Overall, our report details the pathogenic molecules and pathways that promote CsA-induced AKI from an integrative bioinformatics perspective and may help identify the mechanisms of CsA-induced AKI, which is important for the development of novel targets for gene therapy and drug discovery.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/861019


Integration of transcriptomics and metabolomics reveals the molecular mechanisms underlying the effect of nafamostat mesylate on rhabdomyolysis-induced acute kidney injury

To investigate the role and mechanisms of nafamostat mesylate's acute kidney injury in rhabdomyolysis-induced acute kidney injury. Using glycerol, rats were induced into rats, which were divided into three groups: control group, RIAKI group, and NM intervention group. Cell apoptosis was discovered with TUNEL assay, apoptosis was identified with TUNEL assay. NM shields the kidneys from RIAKI, which is mainly associated with NM-mediated glutathione metabolism, allergic response, ferroptosis-related pathways, and the key DEGs involved, including Anpep, Gclc, Mgt1, Mgt2, Cxcl13, Rgn, and Akr1c1. Targeting these genes may become a potential molecular therapy for RIAKI.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/851578


Urinary single-cell sequencing captures intrarenal injury and repair processes in human acute kidney injury

Acute kidney injury is a significant health issue, the outcome of which are mainly dependent on tubular epithelial cells' destruction and repair processes. Via flow cytometry sorting, we show the feasibility and promise of a novel approach to assess AKI's biological and molecular characteristics. We analyzed 42,608 single cell transcriptomes of 40 urine samples from 32 AKI patients and compared our results to reference material from human AKI post-mortem biopsies and published mouse results. In conclusion, single cell transcriptomics of kidney cells excreted in urine provides non-invasive, unprecedented insight into AKI's cellular functions, opening new avenues for target detection, AKI sub-categorization, and monitoring natural disease course and intervention. Healthy cells were extracted from a 40 human urine specimen of 32 patients with acute kidney disease according to a single-cell RNAseq of flow cytometry.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/819390


Urinary extracellular vesicles and micro-RNA as markers of acute kidney injury after cardiac surgery

We hypothesized that monitoring changes in urinary enzyme levels of EV and miR could help identify the onset of acute kidney injury in cardiac surgery patients. Interventions: Predictive accuracy biomarker analysis was conducted in the REVAKI-2 trial group between September 2015 and September 2018, or dextrose 5% at the start of surgery. Urine EV concentrations in patients with AKI after surgery have substantially increased in patients with AKI, with the percentage of EV positive for aquaporin-2 and u03b21-integrin increasing. Patients with AKI stage 2/3 had elevated urine samples from urine from patients with AKI stage 2/3. MiR-10a-5p levels decreased after surgery in AKI patients; their levels were correlated to the severity of the illness. Preoperative levels of podocalyxin EVs and miR-125a-5p had moderate AKI predictive value, and in a logistic model with ICU lactate levels, aKI prediction was given.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/809648


Transcriptional profiling of septic acute kidney injury in rats

Acute kidney injury is related to a kidney dysfunction loss of kidney function with a mix of etiology, including sepsis, ischemia, and nephrotoxicity. MRNA sequencing was performed in Sprague-Dawley rats' renal cortex to look for differentially expressed genes in septic AKI. The cecum was ligated at half the distance between the distal pole and the cecum's base for the introduction of mid-grade sepsis for the CLP group.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/773976


Spatially resolved transcriptomic analysis of acute kidney injury in a female murine model

We developed and tested a female bilateral ischemia reperfusion injury model. We created spatial maps of gene expression across the injury and repair time course using the 10X Genomics Visium Spatial Gene Expression kit, and utilized two open-source computational services, Giotto and SPOTlight, to increase resolution and measure cell-cell interaction dynamics. An ischemia time of 34 minutes in a female murine model resulted in similar injury to males across the time period of injury and repair. Even after injury, injured proximal tubule cells are characterized by increasing macrophage and lymphocyte interactions, consistent with a pro-inflammatory role for this cell type. Overall structure: 10X Visium was used to create a transcriptomic atlas of female kidney injury to identify, confirm, and measure spatial and temporal expression of injury specific genes.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/758384


Kidney VISTA prevents IFNγ-IL-9 axis-mediated tubulointerstitial fibrosis after acute glomerular injury

Backgrounds: The present research investigated whether a tubular anti-inflammatory cell activation inhibitor, which is specifically expressed in kidney macrophages, has a role in tubulointerstitial fibrotic disease in tubulo-mediated glomerulonephritis. VISTA was highly expressed in kidney macrophages, according to the authors. Tubules suffered additional harm after glomerular injury, though VISTA was depleted. Tubules were also affected by glomerular injury. The contact frequency of macrophages with infiltrated T cells in damaged Vsiru2013/u2013 mice increased, followed by increased T cell importation, which culminated in the overproduction of interferon-u03b3. By VISTA depletion, the blocking antibodies against interferon-u03b3 and interleukin-9 were shielded against the pathological process.

Source link: https://www.ncbi.nlm.nih.gov/bioproject/750914

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions