International Journal on Recent and Innovation Trends in Computing and Communication A Review Paper on Tweet segmentation and its Application to Named Entity Recognition

Abstract-Twitter has become one of the most important communication channels with its ability providing the most up-to-date and newsworthy information. Considering wide use of twitter as the source of information, reaching an interesting tweet for user among a bunch of tweets is challenging. A huge amount of tweets sent per day by hundred millions of users, information overload is inevitable. For extracting information in large volume of tweets, Named Entity Recognition (NER), methods on formal texts. However, many applications in Information Retrieval (IR) and Natural Language Processing (NLP) suffer severely from the noisy and short nature of tweets. In this paper, we propose a novel framework for tweet segmentation in a batch mode, called HybridSeg by splitting tweets into meaningful segments, the semantic or context information is well preserved and easily extracted by the downstream applications. HybridSeg finds the optimal segmentation of a tweet by maximizing the sum of the stickiness scores of its candidate segments. The stickiness score considers the probability of a segment being a phrase in English (i.e., global context) and the probability of a segment being a phrase within the batch of tweets (i.e., local context). For the latter, we propose and evaluate two models to derive local context by considering the linguistic features and term-dependency in a batch of tweets, respectively. HybridSeg is also designed to iteratively learn from confident segments as pseudo feedback. As an application, we show that high accuracy is achieved in named entity recognition by applying segment-based part-ofspeech (POS) tagging

Mitochondrial-Targeted Curcuminoids: A Strategy to Enhance Bioavailability and Anticancer Efficacy of Curcumin

<div><p>Although the anti-cancer effects of curcumin has been shown in various cancer cell types, in vitro, pre-clinical and clinical studies showed only a limited efficacy, even at high doses. This is presumably due to low bioavailability in both plasma and tissues, particularly due to poor intracellular accumulation. A variety of methods have been developed to achieve the selective targeting of drugs to cells and mitochondrion. We used a novel approach by conjugation of curcumin to lipophilic triphenylphosphonium (TPP) cation to facilitate delivery of curcumin to mitochondria. TPP is selectively taken up by mitochondria driven by the membrane potential by several hundred folds. In this study, three mitocurcuminoids (mitocurcuminoids-1, 2, and 3) were successfully synthesized by tagging TPP to curcumin at different positions. ESI-MS analysis showed significantly higher uptake of the mitocurcuminoids in mitochondria as compared to curcumin in MCF-7 breast cancer cells. All three mitocurcuminoids exhibited significant cytotoxicity to MCF-7, MDA-MB-231, SKNSH, DU-145, and HeLa cancer cells with minimal effect on normal mammary epithelial cells (MCF-10A). The IC₅₀ was much lower for mitocurcuminoids when compared to curcumin. The mitocurcuminoids induced significant ROS generation, a drop in ΔØm, cell-cycle arrest and apoptosis. They inhibited Akt and STAT3 phosphorylation and increased ERK phosphorylation. Mitocurcuminoids also showed upregulation of pro-apoptotic BNIP3 expression. In conclusion, the results of this study indicated that mitocurcuminoids show substantial promise for further development as a potential agent for the treatment of various cancers.</p></div