Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Background: Acute kidney injury (AKI) is characterized by rapid loss of renal function and is associated with severe clinical outcomes. Understanding the cellular heterogeneity in urine samples during AKI may provide insights into the underlying pathophysiological mechanisms and potential therapeutic targets.
Objectives: To explore the cellular composition and gene expression patterns in urine samples from AKI and non-AKI conditions using Uniform Manifold Approximation and Projection (UMAP) to identify key cellular interactions and pathway activations related to AKI.
Methods: We utilized publicly available the dataset GSE180595 from the Gene Expression Omnibus (GEO) database. Urine samples were collected from AKI and non-AKI patients. Single-cell RNA sequencing (scRNA-seq) was performed to profile the mononuclear cell populations. Differential gene expression analysis was conducted to identify key molecular pathways, with a focus on ECM-related pathways. MAPK1 expression was quantified and compared between the two patient groups.
Results: UMAP analysis revealed significant differences in cellular composition between AKI and non-AKI samples. Fifteen unique cell clusters were identified, each associated with distinct transcriptional profiles. In AKI samples, increased clustering of immune response cells such as monocytes was observed. Pathway analysis highlighted enhanced activation of DNA replication and ECM-related genes pathways in cells from AKI conditions, indicating their potential roles in injury response and tissue remodeling. The differential gene enrichment analysis identified ECM-related pathways as significantly enriched in the AKI group, with MAPK1 being a crucial gene regulating these pathways.
Conclusion: Our findings provide evidence that MAPK1 is upregulated in urinary mononuclear cells of AKI patients and plays a key role in regulating ECM-related pathways. MAPK1 could serve as a potential biomarker for AKI diagnosis and prognosis and may represent a promising therapeutic target for limiting ECM remodeling and fibrosis in AKI. Further studies are needed to explore the clinical implications of targeting MAPK1 in AKI treatment.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12399797 | PMC |
http://dx.doi.org/10.3389/fphar.2025.1573469 | DOI Listing |