Aspect Based Opinion Mining & Sentiment Analysis

Opinion mining is a relatively new field that refers to the practice of collecting feedback in the form of online reviews and ratings left by users on various topics. Researchers are now able to monitor the states of consciousness of individuals in real-time because to this development. Just lately, a number of research papers for sentiment analysis were implemented, each of which was based on a unique categorization and ranking procedure. However, the amount of time necessary for the newline performing class has not decreased in any way. Sentiment Sensitivity newline word list SST was provided as a solution to the problem of function mismatch in the go-domain sentiment class across the source area and the target domain; however, achieving improved accuracy and identifying distributional similarities of words became less effective as time went on. Hidden Markov’s persistent development may be seen at the beginning. Cosine In order to achieve more effective and clean pre-processing, a method that is conceptually quite similar to HM-CPCS has been devised. The HM-CPCS methodology, which has recently been suggested, makes use of the POS tagger, a variant of which is based on the Hidden Markov algorithm. Evaluations are created using data from a wide variety of different domains. Similar to a newline, the tags that come before and after it compute the possibility of transitions and the existence of the term newline among the tags in order to increase capability. This is done in order to improve capability

Dynamic Classification of Sentiments from Restaurant Reviews Using Novel Fuzzy-Encoded LSTM

User reviews on social media have sparked a surge in interest in the application of sentiment analysis to provide feedback to the government, public and commercial sectors. Sentiment analysis, spam identification, sarcasm detection and news classification are just few of the uses of text mining. For many firms, classifying reviews based on user feelings is a significant and collaborative effort. In recent years, machine learning models and handcrafted features have been used to study text classification, however they have failed to produce encouraging results for short text categorization. Deep neural network based Long Short-Term Memory (LSTM) and Fuzzy logic model with incremental learning is suggested in this paper. On the basis of F1-score, accuracy, precision and recall, suggested model was tested on a large dataset of hotel reviews. This study is a categorization analysis of hotel review feelings provided by hotel customers. When word embedding is paired with LSTM, findings show that the suggested model outperforms current best-practice methods, with an accuracy 81.04%, precision 77.81%, recall 80.63% and F1-score 75.44%. The efficiency of the proposed model on any sort of review categorization job is demonstrated by these encouraging findings

ASSESSMENT, EVALUATION AND ANALYSIS OF THE MEDICATION ERRORS OF THE PATIENTS ADMITTED AT THE EMERGENCY DEPARTMENT OF A TERTIARY CARE TEACHING HOSPITAL OF A SOUTH INDIAN CITY

OBJECTIVE: The study was to assess, evaluate and analyze the medication errors of the patients admitted at the Emergency Department of a tertiary care teaching hospital.METHODS: The study was conducted for 6 months. Data was collected from the patients  admitted in the Emergency Department. The collected data was analyzed to identify medication errors and prescription errors in emergency unit in hospital by using drug information tools like Micromedex, Drug interaction checker, Stockley drug interaction text, BNF, Journals with good impact factor etc.RESULTS: A total of 200 patients were enrolled in the study according to the inclusion criteria and exclusion criteria in which 108 were males and 92 were females. 340 medication errors were obtained in 122 patients and 78 patients did not have any error. Medication errors were more commonly in the age group of 61-70 years (49%). In 340 medication errors, DDIs were the most (63.3%), followed by drug duplication (13.53%) and drugs given without indication (8.5%). In DDIs moderate interactions were the mostly seen error. On prescription analysis, drugs prescribed without strength (67.6%), omission error (16.4%), drugs prescribed without frequency (16%) was the most commonly seen. The most common pharmacological classification of drugs associated with medication errors were Antibiotics (25.6%), Anti-hypertensive drugs (13.65%) and Anti-platelet drugs (12.9%).CONCLUSION: Incidence of medication errors was mainly due to the use of Antibiotics. Due to the fast paced nature and overcrowding in ED, more number of prescription errors were obtained.   Â

Intra- and inter-operator reproducibility of automated cloud-based carotid lumen diameter ultrasound measurement

Background: Common carotid artery lumen diameter (LD) ultrasound measurement systems are either manual or semi-automated and lack reproducibility and variability studies. This pilot study presents an automated and cloud-based LD measurements software system (AtheroCloud) and evaluates its: (i) intra/inter-operator reproducibility and (ii) intra/inter-observer variability. Methods: 100 patients (83 M, mean age: 68 ± 11 years), IRB approved, consisted of L/R CCA artery (200 ultrasound images), acquired using a 7.5-MHz linear transducer. The intra/inter-operator reproducibility was verified using three operator's readings. Near-wall and far carotid wall borders were manually traced by two observers for intra/inter-observer variability analysis. Results: The mean coefficient of correlation (CC) for intra- and inter-operator reproducibility between all the three automated reading pairs were: 0.99 (P < 0.0001) and 0.97 (P < 0.0001), respectively. The mean CC for intra- and inter-observer variability between both the manual reading pairs were 0.98 (P < 0.0001) and 0.98 (P < 0.0001), respectively. The Figure-of-Merit between the mean of the three automated readings against the four manuals were 98.32%, 99.50%, 98.94% and 98.49%, respectively. Conclusions: The AtheroCloud LD measurement system showed high intra/inter-operator reproducibility hence can be adapted for vascular screening mode or pharmaceutical clinical trial mode

Synthesis and evaluation of analgesic, anti-asthmatic activity of (E)-1-(8-hydroxyquinolin-7-yl)-3-phenylprop-2-en-1 ones

Abstract Seventeen (E)-1-(8-hydroxyquinolin-7-yl)-3-phenylprop-2-en-1 one derivatives were synthesized via aldol condensation of substituted benzaldehydes with quinoline chalcones starting from 8-hydroxy quinoline. Molecular docking studies were performed on COX-2 protein for analgesic activity and PDE 4 enzyme for anti-asthmatic activity. Docking studies for analgesic activity reveal that the compounds 2 , 4 , 12 , 14 , and 15 showed significant interaction in terms of hydrogen bonding, hydrophobic attachment and van der Waal interaction with COX-2. The docking studies and pharmacological screening indicate that substitution of hydroxyl and conjugated ketone groups on the aldehyde ring and the quinoline ring accelerates analgesia with better binding to active site. Eddy's hot plate method was used to evaluate analgesic activity of the synthesized compounds. Compounds showed a substantial increase in reaction time when compared with standard pentazocin. Compounds 2 , 4 , 7 , 9 and 13 showed significant binding interactions with PDE 4 enzyme and hence were selected for evaluation of anti-asthmatic activity using the goat tracheal chain method. Studies reveal that substitution of the methoxy group at 4th & 5th positions for compounds 2 , 4 & 7 leads to significant percentage inhibition of histamine induced contraction. The synthesized compounds are thus found to be potent as analgesic and anti-asthmatic agents

Ayurvedic paradigm for COVID-19 prophylaxis and management strategies

25-36The prophylactic and therapeutic potential of traditional systems of medicine like Ayurveda has not being explored to its maximum in the search for effective solutions to the COVID-19 crisis. The present work is an attempt to strategize the strength of Ayurveda in the prophylaxis and management of COVID-19 as a standalone system or integrated with conventional medicine. The restorative protocols for COVID-19 may be planned on the line of management principles described for infectious diseases, epidemics, fever, and respiratory ailments in Ayurveda with single herb and formulations having proven immunomodulatory and anti-viral properties. The way forward is to adopt an integrative approach by taking leads from Ayurveda and incorporating it into the action strategy to fight this pandemic

Double-Stranded RNA Attenuates the Barrier Function of Human Pulmonary Artery Endothelial Cells

Circulating RNA may result from excessive cell damage or acute viral infection and can interact with vascular endothelial cells. Despite the obvious clinical implications associated with the presence of circulating RNA, its pathological effects on endothelial cells and the governing molecular mechanisms are still not fully elucidated. We analyzed the effects of double stranded RNA on primary human pulmonary artery endothelial cells (hPAECs). The effect of natural and synthetic double-stranded RNA (dsRNA) on hPAECs was investigated using trans-endothelial electric resistance, molecule trafficking, calcium (Ca2+) homeostasis, gene expression and proliferation studies. Furthermore, the morphology and mechanical changes of the cells caused by synthetic dsRNA was followed by in-situ atomic force microscopy, by vascular-endothelial cadherin and F-actin staining. Our results indicated that exposure of hPAECs to synthetic dsRNA led to functional deficits. This was reflected by morphological and mechanical changes and an increase in the permeability of the endothelial monolayer. hPAECs treated with synthetic dsRNA accumulated in the G1 phase of the cell cycle. Additionally, the proliferation rate of the cells in the presence of synthetic dsRNA was significantly decreased. Furthermore, we found that natural and synthetic dsRNA modulated Ca2+ signaling in hPAECs by inhibiting the sarco-endoplasmic Ca2+-ATPase (SERCA) which is involved in the regulation of the intracellular Ca2+ homeostasis and thus cell growth. Even upon synthetic dsRNA stimulation silencing of SERCA3 preserved the endothelial monolayer integrity. Our data identify novel mechanisms by which dsRNA can disrupt endothelial barrier function and these may be relevant in inflammatory processes

Nf-κb Inhibition Rescues Cardiac Function By Remodeling Calcium Genes In A Duchenne Muscular Dystrophy Model

Duchenne muscular dystrophy (DMD) is a neuromuscular disorder causing progressive muscle degeneration. Although cardiomyopathy is a leading mortality cause in DMD patients, the mechanisms underlying heart failure are not well understood. Previously, we showed that NF-κB exacerbates DMD skeletal muscle pathology by promoting inflammation and impairing new muscle growth. Here, we show that NF-κB is activated in murine dystrophic (mdx) hearts, and that cardiomyocyte ablation of NF-κB rescues cardiac function. This physiological improvement is associated with a signature of upregulated calcium genes, coinciding with global enrichment of permissive H3K27 acetylation chromatin marks and depletion of the transcriptional repressors CCCTC-binding factor, SIN3 transcription regulator family member A, and histone deacetylase 1. In this respect, in DMD hearts, NF-κB acts differently from its established role as a transcriptional activator, instead promoting global changes in the chromatin landscape to regulate calcium genes and cardiac function

A Protective Role for ELR+ Chemokines during Acute Viral Encephalomyelitis

The functional role of ELR-positive CXC chemokines in host defense during acute viral-induced encephalomyelitis was determined. Inoculation of the neurotropic JHM strain of mouse hepatitis virus (JHMV) into the central nervous system (CNS) of mice resulted in the rapid mobilization of PMNs expressing the chemokine receptor CXCR2 into the blood. Migration of PMNs to the CNS coincided with increased expression of transcripts specific for the CXCR2 ELR-positive chemokine ligands CXCL1, CXCL2, and CXCL5 within the brain. Treatment of JHMV-infected mice with anti-CXCR2 blocking antibody reduced PMN trafficking into the CNS by >95%, dampened MMP-9 activity, and abrogated blood-brain-barrier (BBB) breakdown. Correspondingly, CXCR2 neutralization resulted in diminished infiltration of virus-specific T cells, an inability to control viral replication within the brain, and 100% mortality. Blocking CXCR2 signaling did not impair the generation of virus-specific T cells, indicating that CXCR2 is not required to tailor anti-JHMV T cell responses. Evaluation of mice in which CXCR2 is genetically silenced (CXCR2−/− mice) confirmed that PMNs neither expressed CXCR2 nor migrated in response to ligands CXCL1, CXCL2, or CXCL5 in an in vitro chemotaxis assay. Moreover, JHMV infection of CXCR2−/− mice resulted in an approximate 60% reduction of PMN migration into the CNS, yet these mice survived infection and controlled viral replication within the brain. Treatment of JHMV-infected CXCR2−/− mice with anti-CXCR2 antibody did not modulate PMN migration nor alter viral clearance or mortality, indicating the existence of compensatory mechanisms that facilitate sufficient migration of PMNs into the CNS in the absence of CXCR2. Collectively, these findings highlight a previously unappreciated role for ELR-positive chemokines in enhancing host defense during acute viral infections of the CNS