Machine learning approach to detect dynamical states from recurrence measures.

We integrate machine learning approaches with nonlinear time series analysis, specifically utilizing recurrence measures to classify various dynamical states emerging from time series. We implement three machine learning algorithms: Logistic Regression, Random Forest, and Support Vector Machine for this study. The input features are derived from the recurrence quantification of nonlinear time series and characteristic measures of the corresponding recurrence networks. For training and testing, we generate synthetic data from standard nonlinear dynamical systems and evaluate the efficiency and performance of the machine learning algorithms in classifying time series into periodic, chaotic, hyperchaotic, or noisy categories. Additionally, we explore the significance of input features in the classification scheme and find that the features quantifying the density of recurrence points are the most relevant. Furthermore, we illustrate how the trained algorithms can successfully predict the dynamical states of two variable stars, SX Her and AC Her, from the data of their light curves. We also indicate how the algorithms can be trained to classify data from discrete systems.

Perineurioma -a rare cause of proptosis.

Perineurioma is a rare benign soft tissue tumor arising from the peripheral nerve sheath. To date only two cases of orbital perineurioma have been reported in literature. A 45-year-old, with no comorbidities, presented with protrusion of the right eye since one-year. Examination revealed 8mm proptosis of the right eye. Dilated fundoscopy of the right eye showed a pale optic disc with choroidal folds temporal to it. Computerised Tomogram (CT) of the orbit showed a well-defined intraconal mass in the inferotemporal part of the orbit. A trans conjunctival orbitotomy with lateral canthotomy was performed and the tumor was removed en bloc. On immunohistochemistry, the tumour was negative for S-100 and showed patchy weak Epithelial Membrane Antigen positivity which was suggestive of a soft tissue perineurioma.

Therapeutic potential of targeting microRNA-10b in established intracranial glioblastoma: first steps toward the clinic.

MicroRNA-10b (miR-10b) is a unique oncogenic miRNA that is highly expressed in all GBM subtypes, while absent in normal neuroglial cells of the brain. miR-10b inhibition strongly impairs proliferation and survival of cultured glioma cells, including glioma-initiating stem-like cells (GSC). Although several miR-10b targets have been identified previously, the common mechanism conferring the miR-10b-sustained viability of GSC is unknown. Here, we demonstrate that in heterogeneous GSC, miR-10b regulates cell cycle and alternative splicing, often through the non-canonical targeting via 5'UTRs of its target genes, including MBNL1-3, SART3, and RSRC1. We have further assessed the inhibition of miR-10b in intracranial human GSC-derived xenograft and murine GL261 allograft models in athymic and immunocompetent mice. Three delivery routes for the miR-10b antisense oligonucleotide inhibitors (ASO), direct intratumoral injections, continuous osmotic delivery, and systemic intravenous injections, have been explored. In all cases, the treatment with miR-10b ASO led to targets' derepression, and attenuated growth and progression of established intracranial GBM. No significant systemic toxicity was observed upon ASO administration by local or systemic routes. Our results indicate that miR-10b is a promising candidate for the development of targeted therapies against all GBM subtypes.

The Cancer Genome Atlas Analysis Predicts MicroRNA for Targeting Cancer Growth and Vascularization in Glioblastoma.

Using in silico analysis of The Cancer Genome Atlas (TCGA), we identified microRNAs associated with glioblastoma (GBM) survival, and predicted their functions in glioma growth and progression. Inhibition of two "risky" miRNAs, miR-148a and miR-31, in orthotopic xenograft GBM mouse models suppressed tumor growth and thereby prolonged animal survival. Intracranial tumors treated with uncomplexed miR-148a and miR-31 antagomirs exhibited reduced proliferation, stem cell depletion, and normalized tumor vasculature. Growth-promoting functions of these two miRNAs were, in part, mediated by the common target, the factor inhibiting hypoxia-inducible factor 1 (FIH1), and the downstream pathways involving hypoxia-inducible factor HIF1α and Notch signaling. Therefore, miR-31 and miR-148a regulate glioma growth by maintaining tumor stem cells and their niche, and providing the tumor a way to activate angiogenesis even in a normoxic environment. This is the first study that demonstrates intratumoral uptake and growth-inhibiting effects of uncomplexed antagomirs in orthotopic glioma.