MARC details
| 000 -LEADER |
|---|
| fixed length control field |
02686nam a2200241Ia 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
200306s2019 xx 000 0 und d |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Zhou, Yubo. |
| 245 #0 - TITLE STATEMENT |
|---|
| Title |
Metabolic dynamics in critically injured patients : |
| Remainder of title |
a prospective cohort study integrated with 1H NMR metabolomics |
| Statement of responsibility, etc. |
Yubo Zhou, Kai Wang, Jun Zeng, Wei Li, Jin Peng, Zhiyuan Zhou, Pengchi Deng, Mingwei Sun, Hao Yang, Shijun Li, Charles Damien Lu, Hua Jiang |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Date of publication, distribution, etc. |
June 2019 |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
unmediated |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
volume |
| 440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE |
|---|
| Number of part/section of a work |
28 : 2, page 411-418 |
| Title |
Asia Pacific Journal of Clinical Nutrition |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Background and Objectives: By combining the techniques of metabolomics and computational biology, this research aims to explore the mechanism of metabolic dynamics in critically injured patients and develop a new early warning method for mortality. Methods and Study Design: A prospective cohort study was conducted, group plasma samples of critically injured patients were collected for 1H-NMR metabolomics analysis. The data was processed with partial least squares regression, to explore the role of enzyme-gene network regulatory mechanism in critically injured metabolic network regulation and to build a quantitative prediction model for early warning of fast death. Results: In total, 60 patients were enrolled. There were significant differences in plasma metabolome between the surviving patients and the deceased ones. Compared to the surviving patients, 112 enzymes and genes regulating the 6 key metabolic marker disturbances of neopterin, corticosterone, 3-methylhistidine, homocysteine, Serine, tyrosine, prostaglandin E2, tryptophan, testosterone and estriol, were observed in the plasmas of deceased ones. Among patients of different injury stages, there were significant differences in plasma metabolome. Progressing from T0 to T50 stages of injury, increased levels of neopterin, corticosterone, prostaglandin E2, tryptophan and testosterone, together with decreased levels of homocysteine, and estriol, were observed. Eventually, the quantitative prediction model of death warning was established. Cross-validation results showed that the predictive effect was good (RMSE=0.18408, R2=0.87 p=0.036). Conclusions: Metabolomics approaches can be used to quantify the metabolic dynamics of patients with critically injuries and to predict death of critically injured patients by plasma 1H-NMR metabolomics.. |
| 521 ## - TARGET AUDIENCE NOTE |
|---|
| Target audience note |
Nutrition. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Complex metabolic network. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Critically ill injury. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Gene ontology. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Metabolism-dynamics. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Metabolomics |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Articles |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) |
|---|
| Cataloger's initials, CIN (RLIN) |
84361 |
| First Date, FD (RLIN) |
142724 |
