Entity Profiles Research Articles

Preparedness of the entities for the IFRS for SMEs: an emerging country case

Purpose – The purpose of this paper is to determine the preparedness of the small- and medium-sized enterprises (SMEs) for the International Financial Reporting Standard (IFRS) for SMEs in Turkey; and to analyze the effect of several firm characteristics on such preparedness. Design/methodology/approach – The preparedness of the SMEs was determined via a questionnaire survey. The effect of several characteristics of the SMEs (i.e. size, age, independent auditing, internationality, and the existence of an accounting department) on their preparedness was examined by employing non-parametric tests and logistic regression. Findings – This study found that the preparedness of the SMEs for IFRS for SMEs is low in Turkey. Several firm characteristics including, size, independent auditing, and internationality have a significant impact on the preparedness of the SMEs. Research limitations/implications – This study has some implications for several parties, including national and international standard setting authorities, entities, managers, and accounting professionals. SMEs are one of the most important actors in the adoption process of the IFRS for SMEs. Their preparedness level for IFRS for SMEs will present important clues to sustain an effective and successful adoption process. The results of this study show the profile of entities which are prepared for IFRS for SMEs that will be useful for standard authorities and regulatory bodies. The findings of this study will also be useful for other emerging countries’ standard authorities because they will face similar problems in their adoption process. Originality/value – This research makes a significant contribution to the existing literature because there are only a few studies that analyze the preparedness for IFRS for SMEs, especially in emerging countries.

Human iPSC derived neurons recorded by MEA technology: A powerful tool for functional assessment of in vitro neuropharmacology and neurotoxicity

Event Abstract Back to Event Human iPSC derived neurons recorded by MEA technology: A powerful tool for functional assessment of in vitro neuropharmacology and neurotoxicity Dietmar Hess1*, Greg Luerman2 and Heribert Bohlen2 1 Axiogenesis, Germany 2 Axiogenesis, United States In vitro pharmacology profiling of new chemical entities during early phases of drug discovery has recently become an essential tool to predict clinical adverse effects. While for cardiac safety testing high technology platforms are available, specific in vitro neurotoxic panels are not, and in-vivo models are used instead. However, correlations between animal and human data are often weak; in addition,animal studies are expensive, ethically questionable and require large amounts of chemical compounds. In order to directly address human targets, we developed a 48-well platform based on the usage of human induced pluripotent stem-cell derived neurons. Compound related effects on the spontaneous activity of the Peri.4U neurons were assessed by performing field potential recordings using multiwell microelectrode array (MEA)- technology (Maestro System, Axion, Atlanta). When cultivated on the MEA chips, spontaneous activity of these neurons was recorded in 100% of the wells after a cultivation period of 3-4 days. Recordings with clear detectable burst-like activity indicating the presence and establishment of a functional neuronal network were chosen for testing neuropharmacological and neurotoxic compounds. Agonists and blockers of common neurotransmitter receptors as well as reference compounds with known neurotoxic potency were analyzed for their effect on neuronal behavior, thereby demonstrating the potency of this in vitro system for reliable detection and quantification of neuropharmacological and neurotoxic compound actions. Keywords: Neuropharmacology, Neurotoxicity, MEA, in vitro, IPSC-derived neurons Conference: MEA Meeting 2016 | 10th International Meeting on Substrate-Integrated Electrode Arrays, Reutlingen, Germany, 28 Jun - 1 Jul, 2016. Presentation Type: Poster Presentation Topic: MEA Meeting 2016 Citation: Hess D, Luerman G and Bohlen H (2016). Human iPSC derived neurons recorded by MEA technology: A powerful tool for functional assessment of in vitro neuropharmacology and neurotoxicity. Front. Neurosci. Conference Abstract: MEA Meeting 2016 | 10th International Meeting on Substrate-Integrated Electrode Arrays. doi: 10.3389/conf.fnins.2016.93.00032 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 22 Jun 2016; Published Online: 24 Jun 2016. * Correspondence: Dr. Dietmar Hess, Axiogenesis, Köln, Germany, dietmar.hess@axiogenesis.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Dietmar Hess Greg Luerman Heribert Bohlen Google Dietmar Hess Greg Luerman Heribert Bohlen Google Scholar Dietmar Hess Greg Luerman Heribert Bohlen PubMed Dietmar Hess Greg Luerman Heribert Bohlen Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Candidate Molecule Selection Based on In Silico Predicted ADMET Properties of 12 Indenoindole Derivatives

For considering future in vivo assays, it is necessary to investigate pharmacokinetic and toxicity profile of new chemical entities to select the best candidate(s) for further evaluations. Physicochemical parameters and ADMET (Absorption, Distribution, Metabolism, Elimination and Toxicity) properties of 12 indenoindole derivatives – identified as potent inhibitors of the ABCG2 protein - were predicted in silico with the Molinspiration and the ACD/Percepta softwares. The evaluation of mutagenicity and carcinogenicity was achieved by using the QSAR Toolbox software. Based on the exercise, i) two phenolic derivatives should not be metabolically activated by CYP enzymes according to the QSAR Toolbox software leading to a lower mutagenic risk, ii) compounds 2b, 2c could be excluded from further studies because of clastogenic risks and again compound 2c for a relatively low oral bioavailability, iii) one compound for its blood toxicity and five because for their pulmonary toxicity. Finally, six out of the 12 derivatives (1a, 1b, 2a, 2d, 2e and 2g), were predicted, in terms of ADMET properties, to be good candidates for further in vivo investigations.

Latent entity space: a novel retrieval approach for entity-bearing queries

Analysis on Web search query logs has revealed that there is a large portion of entity-bearing queries, reflecting the increasing demand of users on retrieving relevant information about entities such as persons, organizations, products, etc. In the meantime, significant progress has been made in Web-scale information extraction, which enables efficient entity extraction from free text. Since an entity is expected to capture the semantic content of documents and queries more accurately than a term, it would be interesting to study whether leveraging the information about entities can improve the retrieval accuracy for entity-bearing queries. In this paper, we propose a novel retrieval approach, i.e., latent entity space (LES), which models the relevance by leveraging entity profiles to represent semantic content of documents and queries. In the LES, each entity corresponds to one dimension, representing one semantic relevance aspect. We propose a formal probabilistic framework to model the relevance in the high-dimensional entity space. Experimental results over TREC collections show that the proposed LES approach is effective in capturing latent semantic content and can significantly improve the search accuracy of several state-of-the-art retrieval models for entity-bearing queries.

Making Transporter Models for Drug-Drug Interaction Prediction Mobile.

The past decade has seen increased numbers of studies publishing ligand-based computational models for drug transporters. Although they generally use small experimental data sets, these models can provide insights into structure-activity relationships for the transporter. In addition, such models have helped to identify new compounds as substrates or inhibitors of transporters of interest. We recently proposed that many transporters are promiscuous and may require profiling of new chemical entities against multiple substrates for a specific transporter. Furthermore, it should be noted that virtually all of the published ligand-based transporter models are only accessible to those involved in creating them and, consequently, are rarely shared effectively. One way to surmount this is to make models shareable or more accessible. The development of mobile apps that can access such models is highlighted here. These apps can be used to predict ligand interactions with transporters using Bayesian algorithms. We used recently published transporter data sets (MATE1, MATE2K, OCT2, OCTN2, ASBT, and NTCP) to build preliminary models in a commercial tool and in open software that can deliver the model in a mobile app. In addition, several transporter data sets extracted from the ChEMBL database were used to illustrate how such public data and models can be shared. Predicting drug-drug interactions for various transporters using computational models is potentially within reach of anyone with an iPhone or iPad. Such tools could help prioritize which substrates should be used for in vivo drug-drug interaction testing and enable open sharing of models.

Analysis of Bridge Anaphora Across Novel

The paper describes the importance of bridge anaphora relations in the novel Quo Vadis in order to implement a recognition tool for bridging. Moreover, this paper presents a set of conventions of annotations for 11 bridge relations as a result of manually annotations made by a team of trained students in Computational Linguistics. We proposed Weka, a collection of machine learning algorithms for data mining who can be applied directly to a dataset. The method can be extended to any kind of texts, which aim to help linguistics, teachers, and readers in general, who are motivated to understand the entity's profile.

Simultaneous Screening of Activities of Five Cytochrome P450 and Four Uridine 5'-Diphospho-glucuronosyltransferase Enzymes in Human Liver Microsomes Using Cocktail Incubation and Liquid Chromatography-Tandem Mass Spectrometry.

Cytochrome P450 (P450) and uridine 5'-diphospho-glucuronosyltransferase (UGT) are major metabolizing enzymes in the biotransformation of most drugs. Altered P450 and UGT activities are a potential cause of adverse drug-drug interaction. A method for the simultaneous evaluation of the activities of five P450s (CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A) and four UGTs (UGT1A1, UGT1A4, UGT1A9, and UGT2B7) was developed using in vitro cocktail incubation and tandem mass spectrometry. The nine probe substrates used in this assay were phenacetin (CYP1A2), diclofenac (CYP2C9), S-mephenytoin (CYP2C19), dextromethorphan (CYP2D6), midazolam (CYP3A), 7-ethyl-10-hydroxy-camptothecin (SN-38) (UGT1A1), trifluoperazine (UGT1A4), mycophenolic acid (UGT1A9), and naloxone (UGT2B7). This new method involves incubation of two cocktail doses and single cassette analysis. The two cocktail doses and the concentration of each probe substrate in vitro were determined to minimize mutual drug interactions among substrates. Cocktail A comprised phenacetin, diclofenac, S-mephenytoin, dextromethorphan, and midazolam, whereas cocktail B comprised SN-38, trifluoperazine, mycophenolic acid, and naloxone. In the incubation study of these cocktails, the reaction mixtures were pooled and simultaneously analyzed using liquid chromatography-tandem mass spectrometry. The method was validated by comparing inhibition data obtained from the incubation of each probe substrate alone with data from the cocktail method. The IC50 values obtained in both cocktail and individual incubations were in agreement with values previously reported in the literature. This cocktail method offers a rapid and robust way to simultaneously evaluate phase I and II enzyme inhibition profiles of many new chemical entities. This new method will also be useful in the drug discovery process and for advancing the mechanistic understanding of drug interactions.

Preference-aware integration of temporal data

A complete description of an entity is rarely contained in a single data source, but rather, it is often distributed across different data sources. Applications based on personal electronic health records, sentiment analysis, and financial records all illustrate that significant value can be derived from integrated, consistent, and queryable profiles of entities from different sources. Even more so, such integrated profiles are considerably enhanced if temporal information from different sources is carefully accounted for. We develop a simple and yet versatile operator, called prawn, that is typically called as a final step of an entity integration workflow. Prawn is capable of consistently integrating and resolving temporal conflicts in data that may contain multiple dimensions of time based on a set of preference rules specified by a user (hence the name prawn for preference-aware union ). In the event that not all conflicts can be resolved through preferences, one can enumerate each possible consistent interpretation of the result returned by prawn at a given time point through a polynomial-delay algorithm. In addition to providing algorithms for implementing prawn, we study and establish several desirable properties of prawn. First, prawn produces the same temporally integrated outcome, modulo representation of time, regardless of the order in which data sources are integrated. Second, prawn can be customized to integrate temporal data for different applications by specifying application-specific preference rules. Third, we show experimentally that our implementation of prawn is feasible on both "small" and "big" data platforms in that it is efficient in both storage and execution time. Finally, we demonstrate a fundamental advantage of prawn: we illustrate that standard query languages can be immediately used to pose useful temporal queries over the integrated and resolved entity repository.

Decentralized group formation

Abstract Imagine a network of entities, being it replica servers aiming to minimize the probability of data loss, players of online team-based games and tournaments, or companies that look into co-branding opportunities. The objective of each entity in any of these scenarios is to find a few suitable partners to help them achieve a shared goal: replication of the data for fault tolerance, winning the game, successful marketing campaign. All information attainable by the entities is limited to the profiles of other entities that can be used to assess the pairwise fitness. How can they create teams without help of any centralized component and without going into each other’s way? We propose a decentralized algorithm that helps nodes in the network to form groups of a specific size. The protocol works by finding an approximation of a weighted k-clique matching of the underlying graph of assessments. We discuss the basic version of the protocol, and explain how dissemination via gossiping helps in improving its scalability. We evaluate its performance through extensive simulations.

Meta-Blocking: Taking Entity Resolutionto the Next Level

Entity Resolution is an inherently quadratic task that typically scales to large data collections through blocking. In the context of highly heterogeneous information spaces, blocking methods rely on redundancy in order to ensure high effectiveness at the cost of lower efficiency (i.e., more comparisons). This effect is partially ameliorated by coarse-grained block processing techniques that discard entire blocks either a-priori or during the resolution process. In this paper, we introduce meta-blocking as a generic procedure that intervenes between the creation and the processing of blocks, transforming an initial set of blocks into a new one with substantially fewer comparisons and equally high effectiveness. In essence, meta-blocking aims at extracting the most similar pairs of entities by leveraging the information that is encapsulated in the block-to-entity relationships. To this end, it first builds an abstract graph representation of the original set of blocks, with the nodes corresponding to entity profiles and the edges connecting the co-occurring ones. During the creation of this structure all redundant comparisons are discarded, while the superfluous ones can be removed by pruning of the edges with the lowest weight. We analytically examine both procedures, proposing a multitude of edge weighting schemes, graph pruning algorithms as well as pruning criteria. Our approaches are schema-agnostic, thus accommodating any type of blocks. We evaluate their performance through a thorough experimental study over three large-scale, real-world data sets, with the outcomes verifying significant efficiency enhancements at a negligible cost in effectiveness.

MOLECULAR (RE-)CLASSIFICATION OF CNS-PRIMITIVE NEUROECTODERMAL TUMORS

BACKGROUND: According to the current WHO classification of CNS tumors, childhood CNS primitive neuro-ectodermal tumors (CNS-PNETs; WHO °IV) are poorly differentiated embryonal tumors with early onset and aggressive clinical behavior. Histological diagnosis can be complicated by morphological heterogeneity and divergent differentiation. Recent studies suggest the existence of molecular subgroups of CNS-PNETs sharing biological characteristics with other childhood CNS tumors. Here, we aimed at a comprehensive molecular characterization of CNS-PNETs and compared our results to profiles of other brain tumor entities in order to define the biological nature of tumors diagnosed as CNS-PNETs. METHODS: A collection of 211 fresh-frozen or paraffin-embedded tumor samples with an institutional diagnosis “CNS-PNET” was profiled for genome-wide DNA methylation patterns and copy-number alterations, complemented by transcriptomic profiling of a subset (n = 71). (Epi-)genetic profiles of CNS-PNETs were compared to those of >3000 other childhood brain tumors including embryonal, astrocytic, and ependymal entities, and their respective molecular subgroups. We screened selected groups of tumors for recurrent mutations and expression of established molecular markers. RESULTS: DNA methylation and gene expression profiles showed a clear segregation of pediatric brain tumors by histological entities and molecular subgroups. Interestingly, CNS-PNET profiles showed a significant overlap with various well-defined entities, including AT/RT, ETMR, high-grade glioma, medulloblastoma, and ependymoma. When screening CNS-PNETs with profiles highly resembling other entities, hallmark genetic alterations of these, such as amplification of 19q13.42, mutations in IDH1 or H3F3A, or mutations/deletions of the SMARCB1 locus, were frequently detected. Also, established protein markers, such as INI-1, LIN28A, and OLIG2, confirmed the reclassification of these CNS-PNETs. Strikingly, a subset (∼25%) of CNS-PNETs which could not be reclassified segregated into 3-4 distinct molecular subgroups, each with its own characteristic pattern of copy-number aberrations, DNA-methylation and gene expression. Currently, whole genome and RNA-sequencing of these distinct subgroups of CNS-PNETs is ongoing to reveal their underlying genetics. CONCLUSIONS: The correct classification of CNS-PNETs remains challenging. Based on the detection of recurrent genetic aberrations, many cases can be reliably re-classified, indicating that a significant proportion of CNS-PNETs may comprise a variety of other tumor subtypes. These findings suggest that the use of established and novel subgroups markers is needed in order to assist the histopathological evaluation of these tumors. In addition, we have identified a number of true CNS-PNET subtypes and are currently analyzing them in more detail in order to elucidate the genetics of these distinct groups. SECONDARY CATEGORY: Tumor Biology.

ISO/IEC JTC1 SC7 WG24 – ISO/IEC 29110 – Systems and Software Engineering – Life Cycle Profiles for Very Small Entities (VSEs)

INSIGHTVolume 17, Issue 1 p. 12-15 Special Feature ISO/IEC JTC1 SC7 WG24 – ISO/IEC 29110 – Systems and Software Engineering – Life Cycle Profiles for Very Small Entities (VSEs) Ken Ptack, Ken Ptack ken.ptack@incose.org Search for more papers by this author Ken Ptack, Ken Ptack ken.ptack@incose.org Search for more papers by this author First published: 23 June 2015 https://doi.org/10.1002/inst.201417112Citations: 1AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Citing Literature Volume17, Issue1April 2014Pages 12-15 RelatedInformation

Related entity finding by unified probabilistic models

Both the WWW research community and industry have shown increasing interests in not just finding relevant documents, but specific objects or entities to satisfy more sophisticated user information needs. TREC launched an Entity Track in 2009 to investigate the task of related entity finding. This paper proposes two novel probabilistic models to integrate several components into a unified modeling process. In particular, the type matching component can characterize the degree of matching between the expected entity type that is inferred from query and the candidate entity type that is inferred from entity profile. Another important component can incorporate prior knowledge about entities into the retrieval process. The main difference of the two models is that the second model explicitly considers the effect of source entity while the first one does not. A comprehensive set of experiments were conducted on the TREC Entity Track testbeds from 2009 to 2011 with careful design to show the contributions of individual components. The results demonstrate that both the type matching component and the entity prior modeling component can effectively boost the entity retrieval performance. Furthermore, the second model performs better than the first one in all the settings, indicating the benefits of explicitly modeling source entity in related entity finding. Both models generate better or competitive results than the state-of-the-art results in the TREC REF tasks. In addition, the proposed unified probabilistic approach is applied to the TREC Entity List Completion task and also demonstrates good performance.

Intermolecular interaction of voriconazole analogues with model membrane by DSC and NMR, and their antifungal activity using NMR based metabolic profiling

The development of novel antifungal agents with high susceptibility and increased potency can be achieved by increasing their overall lipophilicity. To enhance the lipophilicity of voriconazole, a second generation azole antifungal agent, we have synthesized its carboxylic acid ester analogues, namely p-methoxybenzoate (Vpmb), toluate (Vtol), benzoate (Vbz) and p-nitrobenzoate (Vpnb). The intermolecular interactions of these analogues with model membrane have been investigated using nuclear magnetic resonance (NMR) and differential scanning calorimetric (DSC) techniques. The results indicate varying degree of changes in the membrane bilayer’s structural architecture and physico-chemical characteristics which possibly can be correlated with the antifungal effects via fungal membrane. Rapid metabolite profiling of chemical entities using cell preparations is one of the most important steps in drug discovery. We have evaluated the effect of synthesized analogues on Candida albicans. The method involves real time 1H NMR measurement of intact cells monitoring NMR signals from fungal metabolites which gives Metabolic End Point (MEP). This is then compared with Minimum Inhibitory Concentration (MIC) determined using conventional methods. Results indicate that one of the synthesized analogues, Vpmb shows reasonably good activity.

From MoProSoft Level 2 to ISO/IEC 29110 Basic Profile: Bridging the Gap

The spread of the interest and the need for process reference models, specifically for small and medium software development organizations, has been a catalyst for generating ISO/IEC 29110 Software Engineering — Lifecycle profiles for Very Small Entities. Based on the Mexican standard NMX-I-059-NYCE-2005, better known as MoProSoft, ISO/IEC 29110 is the first international standard specifically designed for very small entities.Thanks to the COMPETISOFT Project and MoProSoft, the background knowledge and models adoption experience have been introduced in Latin America. In Mexico more than 300 organizations have been evaluated in NMX-I-059-NYCE-2005, in 2009 MoProSoft became a national standard in Peru, while COMPETISOFT included the experience and viewpoints of 13 countries and 23 research groups of the region. As a whole, it gives small software development organizations in the region an advantage in adopting an international standard.This paper clarifies the gap between ISO/IEC 29110 and MoProSoft level 2. As a result of a theoretical and practical review both standards have been mapped defining the coverage level between processes, considering the defined tasks, work products and roles. Several recommendations have been suggested to bridge the gap between these standards. Finally, the effort needed to adopt the Basic Profile of the new international standard starting from the Mexican standard has been estimated. The results have been extended to also consider organizations that adopted COMPETISOFT as their process reference model.

Whole genome profiling and other high throughput technologies in lymphoid neoplasms—current contributions and future hopes

The development of high throughput technologies based on the knowledge of the human genome has opened the possibility to search for global genomic alterations in tumors responsible for their development and progression that may have important clinical implications. One of the major applications of this genomic knowledge has been the design of different types of microarray platforms for the analysis of DNA alterations and gene expression profiling (GEP). The main contributions of the DNA studies in lymphoid neoplasms include the definition of relatively characteristic genomic profiles for specific disease entities, the demonstration of common chromosomal alterations across entities, the identification of genes and pathways targeted by the altered chromosomal regions, and the identification of chromosomal alterations with prognostic implications. RNA GEP studies in these tumors have enhanced the molecular characterization of known entities and facilitated the recognition of new subtypes and categories of lymphoid neoplasms, the identification of new biomarkers and prognostic models, and the detection of oncogenic pathways with potential implications for targeted therapies. The recent development of the next generation sequencing (NGS) technologies and its application in lymphoid neoplasms already have provided an initial view of the complex landscape of somatic mutations in these tumors and some findings with important functional and clinical implications. This review addresses the major contributions and limitations of the microarray technologies in the understanding of lymphoid neoplasms and discusses how this knowledge may be transferred into the clinics. The initial results of the NGS studies are also presented.

Determination of Cremophor EL in Rat Plasma by LC-MS/MS: Application to a Pharmacokinetic Study

A rapid sensitive, and selective pseudo MRM based method for the determination of Cremophor EL (CrEL) in rat plasma was developed using Liquid chromatography/Tandem mass spectrometry (LC-MS/MS). The analytes were detected using atmospheric pressure chemical ionization (APCI) tandem mass spectrometry. Plasma concentrations of CrEL were quantified after administration through oral and intravenous routes in male sprague dawley rats at a dose of 0.26 g/kg. The standard curve was linear (0.9982) over the concentration range of 2.10 to 2100.00 μg/mL. The lower limit of quantitation for CrEL was 2.10 μg/mL using 50 μL plasma. The coefficient of variation and relative error for inter and intra assay at three QC levels were 1.23 to 8.87 and -12.08 to 4.10 respectively. CrEL has poor oral bioavailability with mean absolute bioavailability of 2.32%. CrEL plasma concentration profiles after oral and intravenous dosing were without spiky concentration levels. Spiky plasma concentration profiles for new chemical entities (NCEs) are a common phenomenon in drug discovery, which could be due to entrohepatic circulation, sample handling errors. A novel proposal was conveyed to the scientific community, where formulation vehicle can be analysed as qualifier in the analysis of NCEs to address the spiky profiles.

Translationale Forschung und Diagnostik beim Lungenkarzinom

Lung cancer is the most common malignant disease leading to death worldwide. Histologically, it is broadly subcategorized into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), with the latter mainly consisting of the major entities adenocarcinoma and squamous cell carcinoma. However, molecular profiling of various lung cancer entities has revealed major molecular differences within distinct histological tumor entities, resulting in the integration of molecular alterations in the subclassification of lung cancers. These findings can only estimate the genetic complexity of lung tumors. Large scale molecular profiling has the potential to identify novel diagnostic, prognostic and predictive markers as well as therapeutic targets. Importantly, this recently arising categorization of lung carcinomas can be regarded as an example for the characterization of malignomas of other organ systems. The pioneer model for this molecular subcategorization is the classification of malignant lymphomas.

QSPR in Oral Bioavailability: Specificity or Integrality?

During the last decade the technological advances in drug discovery changed the absorption, distribution, metabolism, excretion and toxicity (ADMET) profiles of New Chemical Entities (NCEs). Among ADMET processes, absorption plays an important role in the research and development of more effective orally administered drugs. Although significant progress has been made in in vitro, in situ and in vivo experimental determinations of absorption, the development of in silico methodologies has emerged as a cheaper and fast alternative to predict them. Even though several in silico models have been described in the literature to predict oral bioavailability and related properties, the prediction accuracy and their potential use is still limited. The low precision and high variability of data, the lack of a complete experimental and theoretical validation of in silico approach, and above all, the multi-factorial nature of the oral absorption term, make the development of predictive in silico models a thorny task. The present review discusses several important advances regarding the QSPR approaches used in the development of predictive oral bioavailability models. The importance of fixing the problem associated with data resource, as well as improving the reliability of in silico results is highlighted. Optimization of individual properties along the absorption process must be integrated in a multi-objective scenario for studying oral bioavailability behavior in the early drug discovery and development.

System Design on 3D Entity Non-Destructive Measurement Method

It discusses the measurement principle and the system design of 3D non-destructive measurement method for the homogeneous entity. The measurement project and its operating process is discussed. The basic operation principle and components of this measurement device are pointed out. It included the digitized minute entity cells and the delaminated measuring method for product profiles based on liquid. It is based on Archimedes' principle and lever principle and gravity moment, combined the equations of the gravity moment and the equations of the center of gravity, the 3D coordinate values of every minute entity cell in different layers can be reckon by computer. By inputting the 3D coordinate values of the product into the related CAD software system, the 3D model could be obtained. The principles, the system software were introduced in details about the measurement system of the homogeneous entity profiles. Proved through principium experiment, the system satisfies the request of the measuring precision. The measurement system is effective and feasible.