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Filename: drivers/Session_files_driver.php
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Filename: Session/Session.php
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Function: require_once
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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
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Function: _error_handler
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Function: require_once
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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
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Function: _error_handler
File: /var/www/html/index.php
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Message: Trying to access array offset on value of type null
Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
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Function: _error_handler
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Filename: models/Detail_model.php
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Function: strpos
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Function: insertAPISummary
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Filename: helpers/my_audit_helper.php
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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
Line: 256
Function: _error_handler
File: /var/www/html/index.php
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Filename: controllers/Detail.php
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Function: _error_handler
File: /var/www/html/index.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
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Objective: The present study aimed to investigate the potential mechanism of on colorectal cancer and the relevant targets in the pathway using a network pharmacological approach.
Methods: (1) We identified the major bioactive components of by UPLC-ESI-MS/MS and established the in-house library by using the literature mining method. (2) Target prediction was performed by SwissADME and SwissTargetPrediction. (3) A protein-protein interaction (PPI) network and component-target-pathway network (C-T-P network) were constructed. (4) The GO pathways and the KEGG pathway enrichment analysis were carried out by the Metascape database. (5) Molecular docking was performed by AutoDock software. (6) A series of experimental assays including cell proliferation, cell invasion and migration, and TUNEL staining in CRC were performed in CRC cell lines (HT-29, Lovo, SW-620, and HCT-116) to confirm the inhibitory effects of .
Results: (1) In total, 396 candidate active components of were identified by UPLC-ESI-MS/MS and selected from the database. (2) From OMIM, GeneCards, DrugBank, and TTD databases, 1,666 gene symbols related to CRC were gathered, and (3) 34 overlapping gene symbols related to CRC and drugs were obtained. (4) These results suggested that the anti-CRC components of were mainly apigenin, naringenin, caffeic acid, γ-linolenic acid, α-linolenic acid, cis-10-heptadecenoic acid, etc., and the core targets of action were mainly ESR1, EGFR, PTGS2, MMP9, MMP2, PPARG, etc. (5) The proliferation of muscle cells, the regulation of inflammatory response, the response of cells to organic cyclic compounds, and the apoptotic signaling pathway might serve as principal pathways for CRC treatment. (6) The reliability of some important active components and targets was further validated by molecular docking. The molecular docking analysis suggested an important role of apigenin, naringenin, PTGS2, and MMP9 in delivering the pharmacological activity of against CRC. (7) These results of the evaluation experiment suggested that had a strong inhibitory effect on CRC cell lines, and it exerted anti-CRC activity by activating CRC cell apoptosis and inhibiting CRC cell migration and invasion.
Conclusion: This study may provide valuable insights into exploring the mechanism of action of against CRC.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9280342 | PMC |
http://dx.doi.org/10.3389/fmed.2022.879986 | DOI Listing |
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