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Ecmo-ccu

ABSTRACT: ecmo-ccu

PROVIDER: PRJEB60423 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	ERR10967900.fastq.gz	Fastqsanger.gz
	ERR10967901.fastq.gz	Fastqsanger.gz
	ERR10967902.fastq.gz	Fastqsanger.gz
	ERR10967903.fastq.gz	Fastqsanger.gz
	ERR10967904.fastq.gz	Fastqsanger.gz

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Gene expression signatures identify pediatric patients with multiple organ dysfunction who require advanced life support in the intensive care unit

Project description:Multiple organ dysfunction syndrome (MODS) can result from a variety of initiating events such as infection or trauma. The clinical condition of some MODS patients may deteriorate and require intense resource and high-risk cardiopulmonary support via extracorporeal membrane oxygenation (ECMO). Until now, no diagnostic criteria/molecular biomarker has been developed to identify MODS patients who require subsequent ECMO support. We used multi-time point (0h, 72h and 8d) whole transcriptomics from total blood of 27 patients (contro-4, MODS-17 and ECMO-6) to derived the molecular signatures to diagnose the MODS patients required ECMO support. We observed that immune response (neutrophil level) was compromised in MODS patients, who required ECMO support. Differential gene expression analysis and gene ontology enrichment has revealed that epigenetic modifications has got activated during the MODS deterioration to ECMO. In addition, signature of 6 genes were identified using logistic regression, which can be used as putative diagnostic markers for patients needed ECMO support.

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The characterisation of protein binding in paediatric extracorporeal membrane oxygenation (ECMO) circuits

Project description:The present study aims to characterise proteins bound to circuits collected from children on extracorporeal membrane oxygenation (ECMO). ECMO circuits were collected from 6 patients. Quantification of concentrations for proteins bound to the ECMO circuit samples was performed using bicinchoninic acid (BCA) protein assay, whilst characterisation of the bound proteome was performed using Data-independent acquisition Mass Spectrometry (DIA-MS). Reactome Over-representation Pathway Analyses tool was used to identify functional pathways corresponding to the common proteins bound to circuits across all patients.

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