Multimodal Emotion Classification

Most NLP and Computer Vision tasks are limited to scarcity of labelled data. In social media emotion classification and other related tasks, hashtags have been used as indicators to label data. With the rapid increase in emoji usage of social media, emojis are used as an additional feature for major social NLP tasks. However, this is less explored in case of multimedia posts on social media where posts are composed of both image and text. At the same time, w.e have seen a surge in the interest to incorporate domain knowledge to improve machine understanding of text. In this paper, we investigate whether domain knowledge for emoji can improve the accuracy of emotion classification task. We exploit the importance of different modalities from social media post for emotion classification task using state-of-the-art deep learning architectures. Our experiments demonstrate that the three modalities (text, emoji and images) encode different information to express emotion and therefore can complement each other. Our results also demonstrate that emoji sense depends on the textual context, and emoji combined with text encodes better information than considered separately. The highest accuracy of 71.98% is achieved with a training data of 550k posts

OPEN VERIFICATION CLOUD DATA USING ABE SCHEME

The idea of deniability arises from indisputable proven fact that coercers cannot show the forecasted evidence is wrong and for that reason don't have any motive to refuse the best evidence. This method attempts to obstruct coercion efforts as coercers realize that their attempts are ineffective. We make use of this idea to make sure that providers of cloud storage can provide audit-free storage services. The majority of the method of deniable file encryption offers the problems with understanding error including method of designed understanding. Within our work we offer a effective file encryption plan of cloud storage that enables the providers of cloud storage to create convincing false user methods for defend user privacy. We employ highlights of attribute basis file encryption for securing of understanding that's stored inside the sorts of proper-grained access control additionally to deniable file encryption to postpone outdoors auditing. Our suggested plan will grant users to get capable of offer fake secrets that appear genuine to exterior coercers

Small Molecule Inhibitor of CBFbeta-RUNX Binding for RUNX Transcription Factor Driven Cancers

Transcription factors have traditionally been viewed with skepticism as viable drug targets, but they offer the potential for completely novel mechanisms of action that could more effectively address the stem cell like properties, such as self-renewal and chemo-resistance, that lead to the failure of traditional chemotherapy approaches. Core binding factor is a heterodimeric transcription factor comprised of one of 3 RUNX proteins (RUNX1-3) and a CBFbeta binding partner. CBFbeta enhances DNA binding of RUNX subunits by relieving auto-inhibition. Both RUNX1 and CBFbeta are frequently mutated in human leukemia. More recently, RUNX proteins have been shown to be key players in epithelial cancers, suggesting the targeting of this pathway could have broad utility. In order to test this, we developed small molecules which bind to CBFbeta and inhibit its binding to RUNX. Treatment with these inhibitors reduces binding of RUNX1 to target genes, alters the expression of RUNX1 target genes, and impacts cell survival and differentiation. These inhibitors show efficacy against leukemia cells as well as basal-like (triple-negative) breast cancer cells. These inhibitors provide effective tools to probe the utility of targeting RUNX transcription factor function in other cancers

Predicting Early Indicators of Cognitive Decline From Verbal Utterances

Dementia is a group of irreversible, chronic, and progressive neurodegenerative disorders resulting in impaired memory, communication, and thought processes. In recent years, clinical research advances in brain aging have focused on the earliest clinically detectable stage of incipient dementia, commonly known as mild cognitive impairment (MCI). Currently, these disorders are diagnosed using a manual analysis of neuropsychological examinations. We measure the feasibility of using the linguistic characteristics of verbal utterances elicited during neuropsychological exams of elderly subjects to distinguish between elderly control groups, people with MCI, people diagnosed with possible Alzheimer\u27s disease (AD), and probable AD. We investigated the performance of both theory-driven psycholinguistic features and data-driven contextual language embeddings in identifying different clinically diagnosed groups. Our experiments show that a combination of contextual and psycholinguistic features extracted by a Support Vector Machine improved distinguishing the verbal utterances of elderly controls, people with MCI, possible AD, and probable AD. This is the first work to identify four clinical diagnosis groups of dementia in a highly imbalanced dataset. Our work shows that machine learning algorithms built on contextual and psycholinguistic features can learn the linguistic biomarkers from verbal utterances and assist clinical diagnosis of different stages and types of dementia, even with limited data

A small-molecule inhibitor of the aberrant transcription factor CBFβ-SMMHC delays leukemia in mice

This is the author’s version of the work. It is posted here by permission of the AAAS for personal use, not for redistribution. The definitive version was published in Science on 2015 February 13; 347(6223): 779–784, DOI: 10.1126/science.aaa0314.Acute myeloid leukemia (AML) is the most common form of adult leukemia. The transcription factor fusion CBFβ-SMMHC (core binding factor β and the smooth-muscle myosin heavy chain), expressed in AML with the chromosome inversion inv(16)(p13q22), outcompetes wild-type CBFβ for binding to the transcription factor RUNX1, deregulates RUNX1 activity in hematopoiesis, and induces AML. Current inv(16) AML treatment with nonselective cytotoxic chemotherapy results in a good initial response but limited long-term survival. Here, we report the development of a protein-protein interaction inhibitor, AI-10-49, that selectively binds to CBFβ-SMMHC and disrupts its binding to RUNX1. AI-10-49 restores RUNX1 transcriptional activity, displays favorable pharmacokinetics, and delays leukemia progression in mice. Treatment of primary inv(16) AML patient blasts with AI-10-49 triggers selective cell death. These data suggest that direct inhibition of the oncogenic CBFβ-SMMHC fusion protein may be an effective therapeutic approach for inv(16) AML, and they provide support for transcription factor targeted therapy in other cancers

Strictinin, a novel ROR1-inhibitor, represses triple negative breast cancer survival and migration via modulation of PI3K/AKT/GSK3ß activity.

Triple Negative Breast Cancer (TNBC), the most aggressive subtype of breast cancer, is characterized by the absence of hormone receptors usually targeted by hormone therapies like Tamoxifen. Because therapy success and survival rates for TNBC lag far behind other breast cancer subtypes, there is significant interest in developing novel anti-TNBC agents that can target TNBC specifically, with minimal effects on non-malignant tissue. To this aim, our study describes the anti-TNBC effect of strictinin, an ellagitanin previously isolated from Myrothamnus flabellifolius. Using various in silico and molecular techniques, we characterized the mechanism of action of strictinin in TNBC. Our results suggest strictinin interacts strongly with Receptor Tyrosine Kinase Orphan like 1 (ROR1). ROR1 is an oncofetal receptor highly expressed during development but not in normal adult tissue. It is highly expressed in several human malignancies however, owing to its numerous pro-tumor functions. Via its interaction and inhibition of ROR1, strictinin reduced AKT phosphorylation on ser-473, inhibiting downstream phosphorylation and inhibition of GSK3β. The reduction in AKT phosphorylation also correlated with decreased cell survival and activation of the caspase-mediated intrinsic apoptotic cascade. Strictinin treatment also repressed cell migration and invasion in a beta-catenin independent manner, presumably via the reactivated GSK3ß\u27s repressing effect on microtubule polymerization and focal adhesion turnover. This could be of potential therapeutic interest considering heightened interest in ROR1 and other receptor tyrosine kinases as targets for development of anti-cancer agents. Further studies are needed to validate these findings in other ROR1-expressing malignancies but also in more systemic models of TNBC. Our findings do however underline the potential of strictinin and other ROR1-targeting agents as therapeutic tools to reduce TNBC proliferation, survival and motility