Early Impairment of Cerebral Bioenergetics After Cardiopulmonary Bypass in Neonatal Swine.

Objectives: We previously demonstrated cerebral mitochondrial dysfunction in neonatal swine immediately following a period of full-flow cardiopulmonary bypass (CPB). The extent to which this dysfunction persists in the postoperative period and its correlation with other markers of cerebral bioenergetic failure and injury is unknown. We utilized a neonatal swine model to investigate the early evolution of mitochondrial function and cerebral bioenergetic failure after CPB. Methods: Twenty piglets (mean weight 4.4 ± 0.5 kg) underwent 3 h of CPB at 34 °C via cervical cannulation and were followed for 8, 12, 18, or 24 h (n = 5 per group). Markers of brain tissue damage (glycerol) and bioenergetic dysfunction (lactate to pyruvate ratio) were continuously measured in cerebral microdialysate samples. Control animals (n = 3, mean weight 4.1 ± 1.2 kg) did not undergo cannulation or CPB. Brain tissue was extracted immediately after euthanasia to obtain ex-vivo cortical mitochondrial respiration and frequency of cortical microglial nodules (indicative of cerebral microinfarctions) via neuropathology. Results: Both the lactate to pyruvate ratio (P < .0001) and glycerol levels (P = .01) increased in cerebral microdialysate within 8 h after CPB. At 24 h post-CPB, cortical mitochondrial respiration was significantly decreased compared with controls (P = .046). The presence of microglial nodules increased throughout the study period (24 h) (P = .01, R2 = 0.9). Conclusion: CPB results in impaired cerebral bioenergetics that persist for at least 24 h. During this period of bioenergetic impairment, there may be increased susceptibility to secondary injury related to alterations in metabolic delivery or demand, such as hypoglycemia, seizures, and decreased cerebral blood flow.

A Template for Translational Bioinformatics: Facilitating Multimodal Data Analyses in Preclinical Models of Neurological Injury.

Background: Pediatric neurological injury and disease is a critical public health issue due to increasing rates of survival from primary injuries (e.g., cardiac arrest, traumatic brain injury) and a lack of monitoring technologies and therapeutics for the treatment of secondary neurological injury. Translational, preclinical research facilitates the development of solutions to address this growing issue but is hindered by a lack of available data frameworks and standards for the management, processing, and analysis of multimodal data sets. Methods: Here, we present a generalizable data framework that was implemented for large animal research at the Children's Hospital of Philadelphia to address this technological gap. The presented framework culminates in an interactive dashboard for exploratory analysis and filtered data set download. Results: Compared with existing clinical and preclinical data management solutions, the presented framework accommodates heterogeneous data types (single measure, repeated measures, time series, and imaging), integrates data sets across various experimental models, and facilitates dynamic visualization of integrated data sets. We present a use case of this framework for predictive model development for intra-arrest prediction of cardiopulmonary resuscitation outcome. Conclusions: The described preclinical data framework may serve as a template to aid in data management efforts in other translational research labs that generate heterogeneous data sets and require a dynamic platform that can easily evolve alongside their research.