Minoxidil Regulates Aging-Like Phenotypes in Rat Cortical Astrocytes In Vitro

Mainly due to the slanted focus on the mechanism and regulation of neuronal aging, research on astrocyte aging and its modulation during brain aging is scarce. In this study, we established aged astrocyte culture model by long-term culturing. Cellular senescence was confirmed through SA-β-gal staining as well as through the examination of morphological, molecular, and functional markers. RNA sequencing and functional analysis of astrocytes were performed to further investigate the detailed characteristics of the aged astrocyte model. Along with aged phenotypes, decreased astrocytic proliferation, migration, mitochondrial energetic function and support for neuronal survival and differentiation has been observed in aged astrocytes. In addition, increased expression of cytokines and chemokine-related factors including plasminogen activator inhibitor -1 (PAI-1) was observed in aged astrocytes. Using the RNA sequencing results, we searched potential drugs that can normalize the dysregulated gene expression pattern observed in long-term cultured aged astrocytes. Among several candidates, minoxidil, a pyrimidine-derived anti-hypertensive and anti-pattern hair loss drug, normalized the increased number of SA-β-gal positive cells and nuclear size in aged astrocytes. In addition, minoxidil restored up-regulated activity of PAI-1 and increased mitochondrial superoxide production in aged astrocytes.We concluded that long term culture of astrocytes can be used as a reliable model for the study of astrocyte senescence and minoxidil can be a plausible candidate for the regulation of brain aging.

Effects of Intraperitoneal N-methyl-D-aspartate (NMDA) Administration on Nociceptive/Repetitive Behaviors in Juvenile Mice

Dysregulation of excitatory neurotransmission has been implicated in the pathogenesis of neuropsychiatric disorders. Pharmacological inhibition of N-methyl-D-aspartate (NMDA) receptors is widely used to model neurobehavioral pathologies and underlying mechanisms. There is ample evidence that overstimulation of NMDA-dependent neurotransmission may induce neurobehavioral abnormalities, such as repetitive behaviors and hypersensitization to nociception and cognitive disruption, pharmacological modeling using NMDA has been limited due to the induction of neurotoxicity and blood brain barrier breakdown, especially in young animals. In this study, we examined the effects of intraperitoneal NMDA-administration on nociceptive and repetitive behaviors in ICR mice. Intraperitoneal injection of NMDA induced repetitive grooming and tail biting/licking behaviors in a dose- and age-dependent manner. Nociceptive and repetitive behaviors were more prominent in juvenile mice than adult mice. We did not observe extensive blood brain barrier breakdown or neuronal cell death after peritoneal injection of NMDA, indicating limited neurotoxic effects despite a significant increase in NMDA concentration in the cerebrospinal fluid. These findings suggest that the observed behavioral changes were not mediated by general NMDA toxicity. In the hot plate test, we found that the latency of paw licking and jumping decreased in the NMDA-exposed mice especially in the 75 mg/kg group, suggesting increased nociceptive sensitivity in NMDA-treated animals. Repetitive behaviors and increased pain sensitivity are often comorbid in psychiatric disorders (e.g., autism spectrum disorder). Therefore, the behavioral characteristics of intraperitoneal NMDA-administered mice described herein may be valuable for studying the mechanisms underlying relevant disorders and screening candidate therapeutic molecules.

Ovarian Cancer Prognostic Prediction Model Using RNA Sequencing Data

Ovarian cancer is one of the leading causes of cancer-related deaths in gynecological malignancies. Over 70% of ovarian cancer cases are high-grade serous ovarian cancers and have high death rates due to their resistance to chemotherapy. Despite advances in surgical and pharmaceutical therapies, overall survival rates are not good, and making an accurate prediction of the prognosis is not easy because of the highly heterogeneous nature of ovarian cancer. To improve the patient's prognosis through proper treatment, we present a prognostic prediction model by integrating high-dimensional RNA sequencing data with their clinical data through the following steps: gene filtration, pre-screening, gene marker selection, integrated study of selected gene markers and prediction model building. These steps of the prognostic prediction model can be applied to other types of cancer besides ovarian cancer.