Metabonomics Analysis of Brain Stem Tissue in Rats with Primary Brain Stem Injury Caused Death.

OBJECTIVES: To explore the potential biomarkers for the diagnosis of primary brain stem injury (PBSI) by using metabonomics method to observe the changes of metabolites in rats with PBSI caused death. METHODS: PBSI, non-brain stem brain injury and decapitation rat models were established, and metabolic maps of brain stem were obtained by LC-MS metabonomics method and annotated to the HMDB database. Partial least square-discriminant analysis (PLS-DA) and random forest methods were used to screen potential biomarkers associated with PBSI diagnosis. RESULTS: Eighty-six potential metabolic markers associated with PBSI were screened by PLS-DA. They were modeled and predicted by random forest algorithm with an accuracy rate of 83.3%. The 818 metabolic markers annotated to HMDB database were used for random forest modeling and prediction, and the accuracy rate was 88.9%. According to the importance in the identification of cause of death, the most important metabolic markers that were significantly up-regulated in PBSI group were HMDB0038126 (genipinic acid, GA), HMDB0013272 (N-lauroylglycine), HMDB0005199 [(R)-salsolinol] and HMDB0013645 (N,N-dimethylsphingosine). CONCLUSIONS: GA, N-lauroylglycine, (R)-salsolinol and N,N-dimethylsphingosine are expected to be important metabolite indicators in the diagnosis of PBSI caused death, thus providing clues for forensic medicine practice.

Risk Factors for Acute Kidney Injury in Critically Ill Neonates: A Systematic Review and Meta-Analysis.

Background and Objective: Acute kidney injury (AKI) is recognized as an independent risk factor for mortality and long-term poor prognosis in neonates. The objective of the study was to identify the risk factors for AKI in critically ill neonates to provide an important basis for follow-up research studies and early prevention. Methods: The PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, WanFang Med, SinoMed, and VIP Data were searched for studies of risk factors in critically ill neonates. Studies published from the initiation of the database to November 19, 2020, were included. The quality of studies was assessed by the Newcastle-Ottawa Scale and the Agency for Healthcare Research and Quality (AHRQ) checklist. The meta-analysis was conducted with Stata 15 and drafted according to the guidelines of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement. Results: Seventeen studies (five cohort studies, ten case-control studies, and two cross-sectional studies) were included in meta-analysis, with 1,627 cases in the case group and 5,220 cases in the control group. The incidence of AKI fluctuated from 8.4 to 63.3%. Fifteen risk factors were included, nine of which were significantly associated with an increased risk of AKI in critically ill neonates: gestational age [standardized mean difference (SMD) = -0.31, 95%CI = (-0.51, -0.12), P = 0.002], birthweight [SMD = -0.37, 95%CI = (-0.67, -0.07), P = 0.015], 1-min Apgar score [SMD = -0.61, 95%CI = (-0.78, -0.43), P = 0.000], 5-min Apgar score [SMD = -0.71, 95%CI = (-1.00, -0.41), P = 0.000], congenital heart disease (CHD) [odds ratio (OR) = 2.94, 95%CI = (2.08, 4.15), P = 0.000], hyperbilirubinemia [OR = 2.26, 95%CI = (1.40, 3.65), P = 0.001], necrotizing enterocolitis (NEC) [OR = 6.32, 95%CI = (2.98, 13.42), P = 0.000], sepsis [OR = 2.21, 95%CI = (1.25, 3.89), P = 0.006], and mechanical ventilation [OR = 2.37, 95%CI = (1.50, 3.75), P = 0.000]. Six of them were not significantly associated with AKI in critically ill neonates: age [SMD = -0.25, 95%CI = (-0.54, 0.04), P = 0.095], male sex [OR = 1.10, 95%CI =(0.97, 1.24), P = 0.147], prematurity [OR = 0.90, 95%CI(0.52, 1.56), P = 0.716], cesarean section [OR = 1.52, 95%CI(0.77, 3.01), P = 0.234], prenatal hemorrhage [OR = 1.41, 95%CI = (0.86, 2.33), P = 0.171], and vancomycin [OR = 1.16, 95%CI = (0.71, 1.89), P = 0.555]. Conclusions: This meta-analysis provides a preliminary exploration of risk factors in critically ill neonatal AKI, which may be useful for the prediction of AKI. Systematic Review Registration: PROSPERO (CRD42020188032).