Entity Search Research Articles

NF-κB dependent anti-inflammatory activity of chlorojanerin isolated from Saussurea heteromalla

Medicinal plants have shown great promise as a source of novel drug compounds for the treatment of inflammatory disorders. In our search for new entities with anti-inflammatory potential, the extracts of the whole plant of Saussurea heteromalla (family-Asteraceae), collected from Himalayas, were evaluated in the high throughput screen for TNF-α and IL-6 inhibitors. The extract blocked TNF-α and IL-6 production in LPS stimulated THP-1 cells (human acute monocyte leukemia cell line) completely at 10 and 30μg/ml. The plant has been found as a new source of chlorojanerin, a guaianolide type of sesquiterpene lactone. Chlorojanerin was shown to be significantly effective in inhibiting TNF-α and IL-6 production in LPS-stimulated THP-1 cells (IC50=2.3±0.2μM and 1.8±0.7μM respectively). The compound also blocked TNF-α and IL-6 production from LPS-stimulated human monocytes (IC50=1.5±0.4 and 0.7±0.2μM respectively) and synovial cells from a patient with rheumatoid arthritis (IC50<0.03 and 0.5μM respectively). Transcriptional profiling of the LPS stimulated THP-1 cells revealed that chlorojanerin exerted its anti-inflammatory effect by inhibiting the expression of 8 genes involved in activating the transcription factor – NF-κB. Real time analysis of these genes validated the effect of chlorojanerin on the classical downstream targets of NF-κB. Thus, this study clearly delineated 8 genes which were specifically mitigated due to the effect of chlorojanerin on NF-κB induced signaling at the mRNA level. Further, chlorojanerin at 5μM also inhibited the binding of NF-κB in a GFP reporter assay system by 55.5% thus validating the microarray gene expression data. This work is a step towards the isolation and characterization of lead anti-inflammatory agents from the extract of Saussurea heteromalla, which can be developed into better therapeutic molecules targeted towards some specific inflammatory diseases.

Semantic and distributed entity search in the web of data

Both the growth and ubiquitous character of the Internet have had a profound effect on how we access and consume data and information. More recently, the Semantic Web, an extension of the current Web has come increasingly relevant due to its widespread adoption. The Web of Data (WoD) is an extension of the current web, where not only documents are interlinked by means of hyperlinks but also data in terms of predicates. Specifically, it describes objects, entities or "things" in terms of their attributes and their relationships, using RDF data (and often is used equivalently to Linked Data). Given its growth, there is a strong need for making this wealth of knowledge accessible by keyword search (the de-facto standard paradigm for accessing information online). The goal of this thesis is to provide new techniques for accessing this data, i.e., to leverage its full potential to end users. We therefore address the following four main issues: a) how can the Web of Data be searched by means of keyword search?, b) what sets apart search in the WoD from traditional web search?, c) how can these elements be used in a sound and effective way?, and d) How can the techniques be adapted to a distributed environment? To this end, we develop techniques for effectively searching WoD sources. We build upon and formalise existing entity modelling approaches within a generative language modelling framework, and compare them experimentally using standard test collections. We show that these models outperform the current state-of-the-art in terms of retrieval effectiveness, however, this is done at the cost of abandoning a large part of the semantics behind the data. We propose a novel entity model capable of preserving the semantics associated with entities, without sacrificing retrieval effectiveness. We further show how these approaches can be applied in the distributed context, both with low (federated search) and high numbers (Peer-to-peer or P2P) of independent repositories, collections, or nodes. The main contributions are as follows: We develop a hybrid approach to search in the Web of Data, using elements from traditional information retrieval and structured retrieval alike. We formalise our approaches in a language model setting. We discuss and analyse based on our empirical evaluation and provide insights into the entity search problem. .

In search for new chemical entities as adenosine receptor ligands: Development of agents based on benzo-γ-pyrone skeleton

A selected series of chromone carboxamides synthesized in our laboratory were evaluated by radioligand binding studies towards adenosine receptors. All the chromone-3-carboxamides (compounds 8–12) exhibit A2B receptor displacement percentage superior to 50%. The best results were obtained with phenolic substituents (compounds 9 and 12) in the position 3 of pyrone ring with a Ki value of 2890 and 1350 nM. In addition, the predicted ADME properties for the chromone carboxamides under study are in accordance with the general requirements for the drug discovery and development process and in turn they have potential to emerge as a drug candidate.In summary, N-phenylchromone-3-carboxamide may be proposed as a promising scaffold that can undergo optimization as a selective A2BAR antagonist given its lower affinity for A1AR and A2AAR. Accordingly, one can propose this new chromone class as a promising scaffold for tackling adenosine receptors, namely of A2B subtype.

Animal models of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD), which encompasses both chronic bronchitis and emphysema, is one of the most common respiratory conditions of adults in the developed world. Despite the high prevalence and enormous cost to healthcare and society, COPD has received scant attention in comparison to other respiratory conditions such as asthma and lung cancer. It is often thought of as a self-inflicted disease. But not all people who smoke develop COPD and not all patients with COPD are smokers. The causes of COPD are different. Its pathogenesis is complex. There are very few effective treatments. Therefore, there is an urgent need to improve present therapy by drugs with new modes of actions. In contrast to many human diseases, chronic bronchitis and emphysema occur seldom in the animal world. Therefore, we have to mimic some characteristic features of these diseases in animals. For this reason, a wide variety of animal models have been developed and are employed in the search for new chemical entities for the treatment of COPD. In the present paper, the experimental models of COPD are critically reviewed.

Query modeling for entity search based on terms, categories, and examples

Users often search for entities instead of documents, and in this setting, are willing to provide extra input, in addition to a series of query terms, such as category information and example entities. We propose a general probabilistic framework for entity search to evaluate and provide insights in the many ways of using these types of input for query modeling. We focus on the use of category information and show the advantage of a category-based representation over a term-based representation, and also demonstrate the effectiveness of category-based expansion using example entities. Our best performing model shows very competitive performance on the INEX-XER entity ranking and list completion tasks.

Vitomir Šunjić and Michael J. Parnham: Signposts to chiral drugs: organic synthesis in action

This relatively slim volume will be of interest to those working in synthetic organic chemistry, particularly in the medicinal chemistry area, and having as their aim the discovery of new drug entities for the pharmaceutical industries. It is co-written by an academic (VS), having considerable experience of teaching and research in synthetic organic chemistry allied to medicinal chemistry, and a pharmacologist (MJP) who has extensive experience of research and development involving a variety of therapeutic agents (including anti-inflammatory drugs) in an industrial context. In an introductory chapter, the authors present an overview of the challenges facing organic synthesis in the search for new drug entities and point out the importance of chiral synthesis in the design of molecules able to bind to three dimensional biological target sites, recognising that almost 70% of the top 200 marketed drugs are optically pure. The remainder of the book provides 15 self-contained chapters, each focusing on a specific chiral drug structure, describing its therapeutic profile in terms of its biological target and then presenting a detailed discussion of synthetic approaches to the molecule, the creation of chiral sites and chiral separation techniques. In some cases, retrosynthetic pathways are discussed in relation to potential synthetic strategies and the use of modern reagents, homogeneous catalytic processes and the all-important scaling-up considerations, are highlighted. The range of examples chosen covers a very wide range of therapeutic areas, including anti-inflammatory and anticancer drugs, hypertension and blood lipid control, the treatment of type 2 diabetes, HIV-1, depression and anxiety, antibacterial and anti-asthmatic agents, anti-histamines and even the common household aid (-)-Menthol. Also included is a chapter on 3-amino-1,4benzodiazepines and their potential in the treatment of Alzheimer’s disease. At the end of the book, there is also a useful summary of synthetic methods and concepts that are developed in the individual chapters, together with a useful index. The standard of presentation is very high, with many clearly presented reaction schemes, and each chapter has a comprehensive list of references to the specific area.

Vitomir Šunjić and Michael J. Parnham, “Signposts to chiral drugs: organic synthesis in action”

This relatively slim volume will be of interest to those working in synthetic organic chemistry, particularly in the medicinal chemistry area, and having as their aim the discovery of new drug entities for the pharmaceutical industries. It is co-written by an academic (VS), having considerable experience of teaching and research in synthetic organic chemistry allied to medicinal chemistry, and a pharmacologist (MJP) who has extensive experience of research and development involving a variety of therapeutic agents (including anti-inflammatory drugs) in an industrial context. In an introductory chapter, the authors present an overview of the challenges facing organic synthesis in the search for new drug entities and point out the importance of chiral synthesis in the design of molecules able to bind to three dimensional biological target sites, recognising that almost 70% of the top 200 marketed drugs are optically pure. The remainder of the book provides 15 self-contained chapters, each focusing on a specific chiral drug structure, describing its therapeutic profile in terms of its biological target and then presenting a detailed discussion of synthetic approaches to the molecule, the creation of chiral sites and chiral separation techniques. In some cases, retrosynthetic pathways are discussed in relation to potential synthetic strategies and the use of modern reagents, homogeneous catalytic processes and the all-important scaling-up considerations, are highlighted. The range of examples chosen covers a very wide range of therapeutic areas, including anti-inflammatory and anticancer drugs, hypertension and blood lipid control, the treatment of type 2 diabetes, HIV-1, depression and anxiety, antibacterial and anti-asthmatic agents, anti-histamines and even the common household aid (-)-Menthol. Also included is a chapter on 3-amino-1,4benzodiazepines and their potential in the treatment of Alzheimer’s disease. At the end of the book, there is also a useful summary of synthetic methods and concepts that are developed in the individual chapters, together with a useful index. The standard of presentation is very high, with many clearly presented reaction schemes, and each chapter has a comprehensive list of references to the specific area.

Entity Type Disambiguation in User Queries

Searching for information about individual entities such as persons, locations, events, is an important activity in Internet search today, and is in its core a very semantic-oriented task. Several ways for accessing such information exist, but for locating entity-specific information, search engines are the most commonly used approach. In this context, keyword queries are the primary means of retrieving information about a specific entity. We believe that an important first step of performing such a task is to understand what type of entity the user is looking for. We call this process Entity Type Disambiguation. In this paper, we present a Naive Bayesian Model for entity type disambiguation that explores our assumption that an entity type can be inferred from the attributes a user specifies in a search query. The model has been applied to queries provided by a large sample of participants in an experiment performing an entity search task. The beneficial impact of this approach for the development of new search systems is discussed.

Recent Progress on the Identification of Metabotropic Glutamate 4 Receptor Ligands and Their Potential Utility as CNS Therapeutics

This Review describes recent activity in the advancement of ligands for the metabotropic glutamate 4 receptor subtype and their potential utility as central nervous system (CNS) therapeutics. Until recently, there was a paucity of compounds with suitable selectivity and druglike properties to elucidate the value of this target. The search for selective entities has led several groups to the investigation of allosteric modulators as a path to optimization of potential ligands. Recent efforts, discussed here, have afforded a variety of derivatives with improvements in potency, solubility, and pharmacokinetic properties that garner support for continued investigation and optimization.

Traditional medicine: past, present and future research and development prospects and integration in the National Health System of Cameroon.

Traditional medicine refers to health practices, approaches, knowledge and beliefs incorporating plant, animal and mineral based medicines, spiritual therapies, manual techniques and exercises, applied singularly or in combination to treat, diagnose and prevent illnesses or maintain well-being. In the last decade traditional medicine has become very popular in Cameroon, partly due to the long unsustainable economic situation in the country. The high cost of drugs and increase in drug resistance to common diseases like malaria, bacteria infections and other sexually transmitted diseases has caused the therapeutic approach to alternative traditional medicine as an option for concerted search for new chemical entities (NCE). The World Health Organisation (WHO) in collaboration with the Cameroon Government has put in place a strategic platform for the practice and development of TM in Cameroon. This platform aims at harmonizing the traditional medicine practice in the country, create a synergy between TM and modern medicine and to institutionalize a more harmonized integrated TM practices by the year 2012 in Cameroon. An overview of the practice of TM past, present and future perspectives that underpins the role in sustainable poverty alleviation has been discussed. This study gives an insight into the strategic plan and road map set up by the Government of Cameroon for the organisational framework and research platform for the practice and development of TM, and the global partnership involving the management of TM in the country.

Information search and retrieval in microblogs

Modern information retrieval (IR) has come to terms with numerous new media in efforts to help people find information in increasingly diverse settings. Among these new media are so-called microblogs. A microblog is a stream of text that is written by an author over time. It comprises many very brief updates that are presented to the microblog's readers in reverse-chronological order. Today, the service called Twitter is the most popular microblogging platform. Although microblogging is increasingly popular, methods for organizing and providing access to microblog data are still new. This review offers an introduction to the problems that face researchers and developers of IR systems in microblog settings. After an overview of microblogs and the behavior surrounding them, the review describes established problems in microblog retrieval, such as entity search and sentiment analysis, and modeling abstractions, such as authority and quality. The review also treats user-created metadata that often appear in microblogs. Because the problem of microblog search is so new, the review concludes with a discussion of particularly pressing research issues yet to be studied in the field. © 2011 Wiley Periodicals, Inc.

The Role of Natural Products in the Discovery of New Drug Candidates for the Treatment of Neurodegenerative Disorders I: Parkinsons Disease

Neurodegenerative disorders such as Parkinson's disease (PD), Alzheimer's disease (AD), Huntington's disease (HD) and amyotrophic lateral sclerosis (ALS) are currently incurable pathologies with huge social and economic impacts closely related to the increasing of life expectancy in modern times. Although the clinical and neuropathological aspects of these debilitating disorders are distinct, they share a pattern of neurodegeneration in anatomically or functionally related regions. For each disease, presently available treatments only address symptoms and do not alter the course or progression of the underlying diseases. In this context, the search for new effective chemical entities, capable of acting on diverse biochemical targets, with new mechanisms of action and low toxicity are genuine challenges to research groups and the pharmaceutical industry. This medical need has led to the reemerging of modern natural products chemistry that has yielded sophisticated and complex new lead molecules for drug discovery and development. In this review we discuss some of the main contributions of the natural products chemistry that covers multiple and varied plant species. Advances in the discovery of active constituents of plants, herbs, and extracts prescribed by traditional medicine practices for the treatment of senile neurodegenerative disorders, especially for PD, in the period after the 2000s is reviewed. The most important contributions from the 1990s are also discussed. The review also focuses on the pharmacological mechanisms of action that might underlie the purported beneficial improvements in memory and cognition, neurovascular function, and in neuroprotection. It is concluded that natural product chemistry brings tremendous diversity and historical precedent to a huge area of unmet medical need.

Real-Time Search for Real-World Entities: A Survey

We are observing an increasing trend of connecting embedded sensors and sensor networks to the Internet and publishing their output on the Web. We believe that this development is a precursor of a Web of Things, which gives real-world objects and places a Web presence that not only contains a static description of these entities, but also their real-time state. Just as document searches have become one of the most popular services on the Web, we argue that the search for real-world entities (i.e., people, places, and things) will become equally important. However, in contrast to the mostly static documents on the current Web, the state of real-world entities as captured by sensors is highly dynamic. Thus, searching for real-world entities with a certain state is a challenging problem. In this paper, we define the underlying problem, outline the design space of possible solutions, and survey relevant existing approaches by classifying them according to their design space. We also present a case study of a real-world search engine called Dyser designed by the authors.

A Fluorescence Anisotropy Assay for the Muscarinic M1 G-protein-Coupled Receptor

In the search for new chemical entities that interact with G-proteincoupled receptors (GPCRs), assays that quantify efficacy and affinity are employed. Traditional methods for measuring affinity involve radiolabeled ligands. To address the need for homogeneous biochemical fluorescent assays to characterize orthosteric ligand affinity and dissociation rates, we have developed a fluorescence anisotropy (FA) assay for the muscarinic M1 receptor that can be conducted in a 384-well plate. We used membranes from a muscarinic M1 cell line optimized for high-throughput functional assays and the previously characterized fluorescent antagonist BODIPY FL pirenzepine. The affinities of reference compounds were determined in the competitive FA assay and compared with those obtained with a competitive filter-based radioligand-binding assay using [(3)H] N-methylscopolamine. The IC(50) values produced from the FA assay were well-correlated with the radioligand-binding K(i) values (R(2) = 0.98). The dissociation of the BODIPY FL pirenzepine was readily monitored in real time using the FA assay and was sensitive to the presence of the allosteric modulator gallamine. This M1 FA assay offers advantages over traditional radioligandbinding assays as it eliminates radioactivity while allowing investigation of orthosteric or allosteric muscarinic M1 ligands in a homogeneous format.

Introduction to Search 2009

Search is like the blind men and the elephant. The story goes that four blind men approached an elephant. By touching the hide, trunk, tail and legs each thought of the elephant as an entirely different animal. From the hide we can conclude that search is a contextual process where searchers must aimlessly feel around until they either accidentally find what they want or give up. From the trunk we can conclude that search should be like a fire hose where we flood the searchers with content, overwhelming them. The tail? From this perspective search is seen as the infamous “long tail” wherein searchers are fed minuscule tidbits of esoterica, leaving them curious, but famished.And those feeling the legs would conclude that we should stomp the content into submission, pulverizing until it is unrecognizable.

Indigenous traditional medicine: in vitro anti-giardial activity of plants used in the treatment of diarrhea

The ethnopharmacology for treatment of parasitic infections facilitates and directs the search for new chemical entities. In this direction, this study evaluated the cytotoxicity in vitro, against trophozoites of Giardia lamblia, of aqueous extracts of leaves Achyrocline satureioides (Lam.) DC., barks of Eugenia uniflora L., aerial parts of Foeniculum vulgare Miller, and barks of Psidium guajava L. These plants are traditionally used for the treatment of diarrhea by the indigenous population Mbyá-Guarani, located at the Lomba do Pinheiro, Porto Alegre, Rio Grande do Sul, Brazil. The in vitro susceptibility qualitative analysis of G. lamblia to aqueous extracts was performed in serial dilutions from 2.5 to 0.02 mg/mL. Results revealed the minimal inhibitory concentrations: 0.313 mg/mL for A. satureioides and E. uniflora, 0.02 mg/mL for P. guajava, and F. vulgare did not present any cytotoxic effect. Quantitative assays of viable trophozoites, showed that A. satureioides presented the highest cytotoxic effect (93.5%), followed by P. guajava (82.2%), and E. uniflora (67.3%). Indigenous Guarani use mainly A. satureioides for the treatment of diarrhea, revealing the conformity with results obtained in vitro. Bioguided assays are necessary to identify the compounds responsible for the activity of the aqueous extract of A. satureioides.

Concordance-based entity-oriented search

We consider the problem of finding relevant named entities in response to a search query over a given text corpus. Entity search can readily be used to augment conventional web search engines for a variety of applications. We use entity concordance documents to generate lists of relevant entities for arbitrary text queries. To assess the significance of entity search, we analyzed the AOL dataset of 36 million web search queries with respect to two different sets of entities: namely (a) 2.3 million distinct entities extracted from a news text corpus and (b) 2.9 million Wikipedia article titles. The results clearly indicate that search engines should be aware of entities, for under various criteria of matching between 18-39% of all web search queries can be recognized as specifically searching for entities, while 73-87% of all queries contain entities. Our entity search engine creates a concordance document for each entity, consisting of all the sentences in the corpus containing that entity. We then index and search these documents using open-source search software. This gives a ranked list of entities as the result of search. Visit http://www.textmap.com for a demonstration of our entity search engine over a large news corpus. In the case where the query is a named entity, we evaluate the performance of our system by comparing the results of our search engine to the list of entities that have highest statistical juxtaposition scores with the queried entity. Juxtaposition score is a measure of how strongly two entities are related in terms of a probabilistic upper bound. The results show excellent performance, particularly over well-characterized classes of entities such as people.

PlasmoID: A P. falciparum Information Discovery Tool

Plasmodium falciparum is the parasite responsible for more than 90% of deaths that occur due to malaria. Organization and mining of 'omic' (genomic, proteomic, transcriptomic, interactomic) data can improve our understanding of P. falciparum biology and help in the fight against malaria. PlasmoID (Plasmodium Information Discovery) is a tool developed for the dynamic exploration of the parasite's 'omic' landscape. Diverse computational and curated P. falciparum protein-protein interaction datasets, as well as binary relationships involving protein-small molecule entities, manually curated protein-protein relationships derived from the published literature and protein-protein interactions based on metabolic pathways are included in the PlasmoID database. The graphical user interface is designed as a plug-in to Cytoscape, an open-source network visualization tool. Important features of this plug-in include a synchronized tabular representation of any network loaded on the canvas, ability to find the shortest path between a pair of nodes in the database, search and expansion of entities from the database, and the ability to add new entities to the database through the interface. Malaria researchers can now seamlessly interrogate heterogeneous 'omic' datasets as well as add proprietary data to generate and visualize P. falciparum pathway and cell process network models. PlasmoID can be downloaded from http://pfalciparum.atc.tcs.com/PlasmoID.

Structural characterization of flavonoid glycosides by multi‐stage mass spectrometry

Flavonoids are secondary plant metabolites of great structural variety and high medicinal significance. The search for new chemical entities and the quality control of flavonoid containing natural products require easy-to-use but reliable and robust analytical methodologies. For structural elucidation of flavonoids and their glycosides, nuclear magnetic resonance (NMR) and mass spectroscopy (MS) are the generally used techniques. In phytochemical analyses, however, high amounts of flavonoids are difficult to isolate for NMR, thus low sample volume requiring MS based methods are emerging. This review summarizes and compares currently available methods for structural elucidation of flavonoids by LC-MS and LC-MS(n), and focuses on the identification options of unknown flavonoid glycosides in complex samples (e.g., plant extracts) with the emphasis on the differentiation of isomeric compounds.

The first year at the large hadron collider

The Large Hadron Collider (LHC) offers unprecedented opportunities to study in detail interactions in the unexplored energy range around 1 TeV, where new physical phenomena undoubtedly exist. The luminosity expected in the first year of LHC operation will make it possible to thoroughly tune and calibrate physical facilities, clear up characteristics of the main, most intense processes, and search for new entities, such as the Higgs boson, light supersymmetric particles, and new heavy gauge bosons, with a sensitivity high enough to allow their observation.