2 research outputs found

    Cell-specific and region-specific transcriptomics in the multiple sclerosis model: Focus on astrocytes.

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    Changes in gene expression that occur across the central nervous system (CNS) during neurological diseases do not address the heterogeneity of cell types from one CNS region to another and are complicated by alterations in cellular composition during disease. Multiple sclerosis (MS) is multifocal by definition. Here, a cell-specific and region-specific transcriptomics approach was used to determine gene expression changes in astrocytes in the most widely used MS model, experimental autoimmune encephalomyelitis (EAE). Astrocyte-specific RNAs from various neuroanatomic regions were attained using RiboTag technology. Sequencing and bioinformatics analyses showed that EAE-induced gene expression changes differed between neuroanatomic regions when comparing astrocytes from spinal cord, cerebellum, cerebral cortex, and hippocampus. The top gene pathways that were changed in astrocytes from spinal cord during chronic EAE involved decreases in expression of cholesterol synthesis genes while immune pathway gene expression in astrocytes was increased. Optic nerve from EAE and optic chiasm from MS also showed decreased cholesterol synthesis gene expression. The potential role of cholesterol synthesized by astrocytes during EAE and MS is discussed. Together, this provides proof-of-concept that a cell-specific and region-specific gene expression approach can provide potential treatment targets in distinct neuroanatomic regions during multifocal neurological diseases

    Effect of Frailty on Hospital Outcomes Among Pediatric Cancer Patients in the United States: Results From the National Inpatient Sample.

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    BACKGROUND: Studies on frailty among pediatric patients with cancer are scarce. In this study, we sought to understand the effects of frailty on hospital outcomes in pediatric patients with cancer. METHODS: This retrospective study used data collected and stored in the Nationwide Inpatient Sample (NIS) between 2005 and 2014. These were hospitalized patients and hence represented the sickest group of patients. Frailty was measured using the frailty definition diagnostic indicator by Johns Hopkins Adjusted Clinical Groups. RESULTS: Of 187,835 pediatric cancer hospitalizations included in this analysis, 11,497 (6.1%) were frail. The average hospitalization costs were 86,910amongfrailand86,910 among frail and 40,358 for nonfrail patients. In propensity score matching analysis, the odds of in-hospital mortality (odds ratio, 2.08; 95% CI, 1.71-2.52) and length of stay (odds ratio, 3.76; 95% CI, 3.46-4.09) were significantly greater for frail patients. The findings of our study suggest that frailty is a crucial clinical factor to be considered when treating pediatric cancer patients in a hospital setting. CONCLUSIONS: These findings highlight the need for further research on frailty-based risk stratification and individualized interventions that could improve outcomes in frail pediatric cancer patients. The adaptation and validation of a frailty-defining diagnostic tool in the pediatric population is a high priority in the field
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