Translational Genomics in Neurocritical Care: a Review

Investigation into Antioxidant Mechanism of Lycium barbarum Extract in Carbendazim-Induced PC12 Cell Injury Model through Transcriptomics and Metabolomics Analyses

Lycium barbarum L., an important functional food in China, has antioxidant and antiaging activity. However, the exact antioxidant activity mechanism of Lycium barbarum extracts (LBE) is not well understood. Therefore, a carbendazim (CBZ)-induced PC12 cell injury model was constructed and vitrificated to study the antioxidant activity of fresh LBE on the basis of extraction parameter optimization via the full factorial design of experiments (DOE) method. The results showed that the pretreatment of PC12 cells with LBE could reduce the reactive oxygen species (ROS) level by 14.6% and inhibited the mitochondrial membrane potential (MMP) decline by 12.0%. Furthermore, the integrated analysis revealed that LBE played an antioxidant role by activating oxidative phosphorylation (OXPHOS) and restoring MMP, maintaining the tricarboxylic acid (TCA) cycle stability, and regulating the GSH metabolic pathway. The results of the present study provide new ideas for the understanding of the antioxidant function of LBE from a global perspective.

Reverse translation of artificial intelligence in glaucoma: Connecting basic science with clinical applications

Artificial intelligence (AI) has been approved for biomedical research in diverse areas from bedside clinical studies to benchtop basic scientific research. For ophthalmic research, in particular glaucoma, AI applications are rapidly growing for potential clinical translation given the vast data available and the introduction of federated learning. Conversely, AI for basic science remains limited despite its useful power in providing mechanistic insight. In this perspective, we discuss recent progress, opportunities, and challenges in the application of AI in glaucoma for scientific discoveries. Specifically, we focus on the research paradigm of reverse translation, in which clinical data are first used for patient-centered hypothesis generation followed by transitioning into basic science studies for hypothesis validation. We elaborate on several distinctive areas of research opportunities for reverse translation of AI in glaucoma including disease risk and progression prediction, pathology characterization, and sub-phenotype identification. We conclude with current challenges and future opportunities for AI research in basic science for glaucoma such as inter-species diversity, AI model generalizability and explainability, as well as AI applications using advanced ocular imaging and genomic data.

Role of lncRNAs in the Development of Ischemic Stroke and Their Therapeutic Potential

Stroke is a major cause of premature mortality and disability around the world. Therefore, identification of cellular and molecular processes implicated in the pathogenesis and progression of ischemic stroke has become a priority. Long non-coding RNAs (lncRNAs) are emerging as significant players in the pathophysiology of cerebral ischemia. They are involved in different signalling pathways of cellular processes like cell apoptosis, autophagy, angiogenesis, inflammation, and cell death, impacting the progression of cerebral damage. Exploring the functions of these lncRNAs and their mechanism of action may help in the development of promising treatment strategies. In this review, the current knowledge of lncRNAs in ischemic stroke, focusing on the mechanism by which they cause cellular apoptosis, inflammation, and microglial activation, has been summarized. Very few lncRNAs have been functionally annotated. Therefore, the therapies based on lncRNAs still face many hurdles since the potential targets are likely to increase with the identification of new ones. Majority of experiments involving the identification and function of lncRNAs have been carried out in animal models, and the role of lncRNAs in human stroke presents a challenge. However, mitigating these issues through more rational experimental design might lead to the development of lncRNA-based stroke therapies to treat ischemic stroke.

"Omics" in traumatic brain injury: novel approaches to a complex disease

BACKGROUND

To date, there is neither any pharmacological treatment with efficacy in traumatic brain injury (TBI) nor any method to halt the disease progress. This is due to an incomplete understanding of the vast complexity of the biological cascades and failure to appreciate the diversity of secondary injury mechanisms in TBI. In recent years, techniques for high-throughput characterization and quantification of biological molecules that include genomics, proteomics, and metabolomics have evolved and referred to as omics.

METHODS

In this narrative review, we highlight how omics technology can be applied to potentiate diagnostics and prognostication as well as to advance our understanding of injury mechanisms in TBI.

RESULTS

The omics platforms provide possibilities to study function, dynamics, and alterations of molecular pathways of normal and TBI disease states. Through advanced bioinformatics, large datasets of molecular information from small biological samples can be analyzed in detail and provide valuable knowledge of pathophysiological mechanisms, to include in prognostic modeling when connected to clinically relevant data. In such a complex disease as TBI, omics enables broad categories of studies from gene compositions associated with susceptibility to secondary injury or poor outcome, to potential alterations in metabolites following TBI.

CONCLUSION

The field of omics in TBI research is rapidly evolving. The recent data and novel methods reviewed herein may form the basis for improved precision medicine approaches, development of pharmacological approaches, and individualization of therapeutic efforts by implementing mathematical "big data" predictive modeling in the near future.

Neuroinflammation and Precision Medicine in Pediatric Neurocritical Care: Multi-Modal Monitoring of Immunometabolic Dysfunction

The understanding of molecular biology in neurocritical care (NCC) is expanding rapidly and recognizing the important contribution of neuroinflammation, specifically changes in immunometabolism, towards pathological disease processes encountered across all illnesses in the NCC. Additionally, the importance of individualized inflammatory responses has been emphasized, acknowledging that not all individuals have the same mechanisms contributing towards their presentation. By understanding cellular processes that drive disease, we can make better personalized therapy decisions to improve patient outcomes. While the understanding of these cellular processes is evolving, the ability to measure such cellular responses at bedside to make acute care decisions is lacking. In this overview, we review cellular mechanisms involved in pathological neuroinflammation with a focus on immunometabolic dysfunction and review non-invasive bedside tools that have the potential to measure indirect and direct markers of shifts in cellular metabolism related to neuroinflammation. These tools include near-infrared spectroscopy, transcranial doppler, elastography, electroencephalography, magnetic resonance imaging and spectroscopy, and cytokine analysis. Additionally, we review the importance of genetic testing in providing information about unique metabolic profiles to guide individualized interpretation of bedside data. Together in tandem, these modalities have the potential to provide real time information and guide more informed treatment decisions.