2021
DOI: 10.1111/apa.15874
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Metabolic responses in neonatal sepsis—A systematic review of human metabolomic studies

Abstract: This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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Cited by 12 publications
(7 citation statements)
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“…These regulations likely inhibit vast ATP production, which is necessary for strong immune responses, and instead support the maintenance of organ functions. Similar observations were shown previously in septic patients, demonstrating transcriptomic profiles with highly up-regulated glycolysis and HIF-1α signaling (36). When conducting plasma metabolomics, we found metabolic pathways related to the TCA cycle and mitochondrial activities were significantly enhanced in sepsis survivors.…”
Section: Discussionsupporting
confidence: 90%
“…These regulations likely inhibit vast ATP production, which is necessary for strong immune responses, and instead support the maintenance of organ functions. Similar observations were shown previously in septic patients, demonstrating transcriptomic profiles with highly up-regulated glycolysis and HIF-1α signaling (36). When conducting plasma metabolomics, we found metabolic pathways related to the TCA cycle and mitochondrial activities were significantly enhanced in sepsis survivors.…”
Section: Discussionsupporting
confidence: 90%
“…Our ndings shed light on new ways in which platelet activation and mineral absorption may in uence heart metabolism. Many diseases can be better detected and treated early with metabolomic investigations, which provide a precise assessment of individual metabolic reactions to pathophysiological stimuli (Bjerkhaug et al, 2021). When activated in abnormal circumstances, they can induce blood clots in the circulatory system, a leading cause of death in the elderly.…”
Section: Discussionmentioning
confidence: 99%
“…As in any other field of science, Omics technologies and machine learning may be very useful in the advance of the methods used to diagnose NS, including LOS. Transcriptomics [ 247 , 248 , 249 , 250 ], proteomics [ 251 , 252 , 253 , 254 , 255 ] and metabolomics [ 252 , 256 , 257 , 258 ] have been used to characterize the response of preterm neonates to NS [ 259 , 260 ] and, together with machine learning approaches, can help to identify promising biomarkers, to determine NS risk, treatment response and prognosis [ 261 , 262 ]. Some steps were already made in that direction and Pediatric Sepsis Biomarker Risk Model, PERSEVERE, was developed and validated as a prognostic enrichment tool for pediatric septic shock [ 260 , 263 ].…”
Section: Los Diagnosis and Treatmentmentioning
confidence: 99%