In-silico studies of HMG-Co A reductase inhibitors present in fruits of Withania coagulans Dunal (Solanaceae)

Purpose: To evaluate the antihypercholesterolemic effect of chemical constituents of W. coagulans by determining inhibitory effect of the compounds against HMG-CoA reductase, using in-silico methods. Method: Docking simulations of twenty-one chemical constituents, found in the fruits of W. coagulans were performed against HMGCR(PDB ID: 2Q1L) using Molegro Virtual Docker software. The best docked poses were then selected, based on the docking score and amino acids involved in the interaction within the ligand and active site of protein. Results: Five compounds viz. Coagulin D (comp no. 11), Ergosta-5,25-diene-3β,24ε-diol (comp no. 13), Withacoagulin (comp no. 15), and Withaferin (comp no. 16), showed the highest MolDock scores. These compounds with highest docking score, also formed hydrogen bond interactions with His (752), Lys (692, 735), Asp (690), Glu (559) within the binding site of HMG-CoA reductase, thus, halting enzyme activity. Whereas, Withanolide D (comp no. 17) with high MolDock score did not show hydrogen bonding interactions. Conclusion: The high MolDock score and maximum binding with catalytic region of the enzyme indicate that compounds selected from the fruits of W. coagulans are potential blockers of HMG-CoA reductase. Thus, the compounds may be useful for the management of hypercholesterolemia, which untreated, often leads to coronary artery disease. Keywords: Withania coagulans, Coronary artery disease, HMG-CoA reductase, Molegro virtual docker, Hypercholesterolemia, In silico studie

Obscure Gastrointestinal Bleed from a Gastrointestinal Stromal Tumor in a Jejunal Diverticulum: A Rare Case Report

We present a case of small bowel diverticulum with gastrointestinal stromal tumor (GIST). This GIST in the diverticulum was confirmed by immunohistochemistry and was of low-grade malignant potential

BRICS: Is the Group Really Creating Impact?

In 2001, Jim O'Neill coined the acronym for Brazil, Russia, India and China as the largest emerging markets economies. He expected them to grow faster than the developed countries and to play an increasingly important role in the world. In 2009, BRIC countries held their first summit which in its 3rd summit turned into BRICS with the addition of South Africa. The BRICS now represent 3 billion people and a combined GDP of $16 trillion. The group is the third giant after the EU and the US. Analysts predict that the BRICS will overtake US in terms of GDP this year and the G7 by 2030. In the summit in July 2014, BRICS leaders have approved creating the BRICS New Development Bank which would fund long-term investment in infrastructure and more sustainable development. The economics projections show that till 2040, the BRICS is expected to rule the world market

Text stream to temporal network - A dynamic heartbeat graph to detect emerging events on twitter

© 2018, Springer International Publishing AG, part of Springer Nature. Huge mounds of data are generated every second on the Internet. People around the globe publish and share information related to real-world events they experience every day. This provides a valuable opportunity to analyze the content of this information to detect real-world happenings, however, it is quite challenging task. In this work, we propose a novel graph-based approach named the Dynamic Heartbeat Graph (DHG) that not only detects the events at an early stage, but also suppresses them in the upcoming adjacent data stream in order to highlight new emerging events. This characteristic makes the proposed method interesting and efficient in finding emerging events and related topics. The experiment results on real-world datasets (i.e. FA Cup Final and Super Tuesday 2012) show a considerable improvement in most cases, while time complexity remains very attractive

BER evaluation of post-meter PLC services in CENELEC-C band

Low voltage, in-home power-line communications (PLC) networks allow direct communication between smart meters (SM) and in-home devices (IHD). In order to minimize security issues, in many deployment scenarios transmission takes place only towards the IHD to display consumption data, with no backwards channel. As a result, channel estimation is difficult and it is necessary to use robust transmission techniques to mitigate the effect of the impulsive noise within the PLC channel. Performance of such system must be evaluated by taking into account realistic interference and channel models for a broad range of configurations. In this work we focus on performance in terms of bit error rate (BER) of a narrowband PLC (NB-PLC) operating in the CENELEC-C band (125–140 kHz) taking into account realistic noise models. Our system is based on binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) modulation

A rare case of primary midgut volvulus necessitating extensive bowel resection in an adult

A cause of acute intestinal obstruction in adults, midgut volvulus can be categorized into two types: primary type with no identifiable underlying cause, and secondary type that occurs in the presence of a predisposing condition such as, postoperative adhesions. Primary midgut volvulus can lead to bowel ischemia and necrosis, making an extensive bowel resection imminent. A potential consequence of bowel resection is short-bowel syndrome - a failure of digestion and absorption by the intestines, leading to malnutrition and other complications. As such, we report the diagnosis and management of primary midgut volvulus - a rare entity in adults - occurring in an adult patient

Enhanced Heartbeat Graph for emerging event detection on Twitter using time series networks

© 2019 Elsevier Ltd With increasing popularity of social media, Twitter has become one of the leading platforms to report events in real-time. Detecting events from Twitter stream requires complex techniques. Event-related trending topics consist of a group of words which successfully detect and identify events. Event detection techniques must be scalable and robust, so that they can deal with the huge volume and noise associated with social media. Existing event detection methods mostly rely on burstiness, mainly the frequency of words and their co-occurrences. However, burstiness sometimes dominates other relevant details in the data which could be equally significant. Besides, the topological and temporal relationships in the data are often ignored. In this work, we propose a novel graph-based approach, called the Enhanced Heartbeat Graph (EHG), which detects events efficiently. EHG suppresses dominating topics in the subsequent data stream, after their first detection. Experimental results on three real-world datasets (i.e., Football Association Challenge Cup Final, Super Tuesday, and the US Election 2012) show superior performance of the proposed approach in comparison to the state-of-the-art techniques

Smoking behaviour among young doctors of a tertiary care hospital in North India

Background:Tobacco use is one of the biggest public health threats the world has ever faced. There are more than one billion smokers in the world. Almost half of the world's children breathe air polluted by tobacco. Aim of current study was to study the smoking trends among young doctors in a tertiary care institute in north India.Methods:A descriptive observational cross-sectional epidemiological study was conducted among 250 doctors of a tertiary care Hospital in Jammu & Kashmir (Sheri Kashmir Institute of Medical Sciences, SKIMS) during the two months of February-March, 2014. The predesigned tool adopted during data collection was a questionnaire that was developed at the institute with the assistance from the faculty members and other experts.Results:Among 250 participants, (20%) were smokers; among smokers, (76%) were regular smokers and (24%) were occasional smokers. Majority of smokers were in the age group of 21-30 years (80%) & started smoking between 11-20 years (70%). All of them were male (100%). No significant difference was observed among urban and rural students. Among smokers, majority (60%) was in the practice of smoking for last 6 months to 1 year and 26% smoked for <6 months; & (14%) smoked for more than 5 years .It was found more than half of the responding (60%) students used to smoke 5-9 cigarettes per day; 14% is <5 and 26% consumed 10 or more per day .Among smokers, peer pressure was found in 80% cases. (χ2 = 107, P <0.001). Among smokers, almost 20% had other addiction and among non-smokers only 5% had .Effect of parental smoking  was significantly higher in smokers than non-smoker (χ2 = 66.2, P <0.001) .It was seen that peer pressure was the most important risk factor (60%) of initiation of smoking habit followed by parental influence (20%). Majority (78.4%) had no intention to quit in the next 6 months. Lack of Incentive (36.36%) and Addiction (27.27%) were the main reasons for not quitting.Conclusion:We need to create more awareness regarding hazards of smoking in general population especially in medical students, and afterwards provide psychological and pharmacological support for those who intend to quit, as medical students can themselves become a tool to fight this hazard at all levels.

Increased occurrence of hypothyroidism among pregnant women during the first trimester and its correlation with anti-thyroid peroxidase antibody (anti-TPO) and gestational diabetes mellitus in Chattagram region, Bangladesh

Background: The present study was aimed at investigating the prevalence of hypothyroidism in pregnant women in their first trimester in Chattagram, an iodine-sufficient area in Bangladesh. We also studied whether hypothyroidism in pregnancy has any correlation with high titres of anti-thyroid peroxidase (anti-TPO) antibodies and the occurrence of gestational diabetes mellitus.Methods: Our study included 100 pregnant women at their first antenatal checkup based on certain preselected criteria in two tertiary care hospitals in Chattogram. The levels of serum TSH, FT4, and anti-TPO were estimated to detect thyroid function from the collected blood sample. The oral glucose tolerance test was carried out between 24 and 28 weeks of gestational age. A standard predesigned proforma was used to record a detailed patient history and the findings of general physical examinations.Results: According to our results, thyroid disorder and GDM affect 19% and 13% of total pregnancies, respectively. Among TD patients, subclinical hypothyroidism (SCH) prevails the most (11%). The majority of the hypothyroid patients with a high titre of anti-TPO positivity (11%) indicate an autoimmune etiology (p&lt;0.001). Furthermore, a statistically significant relationship (p&lt;0.01) was established between hypothyroidism and GDM. No demographic data was observed to affect GDM and hypothyroidism.Conclusion: Thyroid disorders affect one in every six pregnant women in the southern part of Bangladesh. Moreover, hypothyroid pregnant women were found to be highly susceptible to GDM. Euthyroid women with a high titre of anti-TPO during their gestation should be closely monitored for the development of hypothyroidism and GDM

What’s Happening Around the World? A Survey and Framework on Event Detection Techniques on Twitter

© 2019, Springer Nature B.V. In the last few years, Twitter has become a popular platform for sharing opinions, experiences, news, and views in real-time. Twitter presents an interesting opportunity for detecting events happening around the world. The content (tweets) published on Twitter are short and pose diverse challenges for detecting and interpreting event-related information. This article provides insights into ongoing research and helps in understanding recent research trends and techniques used for event detection using Twitter data. We classify techniques and methodologies according to event types, orientation of content, event detection tasks, their evaluation, and common practices. We highlight the limitations of existing techniques and accordingly propose solutions to address the shortcomings. We propose a framework called EDoT based on the research trends, common practices, and techniques used for detecting events on Twitter. EDoT can serve as a guideline for developing event detection methods, especially for researchers who are new in this area. We also describe and compare data collection techniques, the effectiveness and shortcomings of various Twitter and non-Twitter-based features, and discuss various evaluation measures and benchmarking methodologies. Finally, we discuss the trends, limitations, and future directions for detecting events on Twitter