bluuebunny/crossref_metadata_2025_split huggingface dataset:
Molecular and functional characterization of an octopamine receptor from honeybee (Apis mellifera) brain
Authors: Grohmann Lore , Blenau Wolfgang , Erber Joachim , Ebert Paul R. , Strünker Timo , Baumann Arnd 
Published: July 2003

AbstractBiogenic amines and their receptors regulate and modulate many physiological and behavioural processes in animals. In vertebrates, octopamine is only found in trace amounts and its function as a true neurotransmitter is unclear. In protostomes, however, octopamine can act as neurotransmitter, neuromodulator and neurohormone. In the honeybee, octopamine acts as a neuromodulator and is involved in learning and memory formation. The identification of potential octopamine receptors is decisive for an understanding of the cellular pathways involved in mediating the effects of octopamine. Here we report the cloning and functional characterization of the first octopamine receptor from the honeybee, Apis mellifera. The gene was isolated from a brain‐specific cDNA library. It encodes a protein most closely related to octopamine receptors from Drosophila melanogaster and Lymnea stagnalis. Signalling properties of the cloned receptor were studied in transiently transfected human embryonic kidney (HEK) 293 cells. Nanomolar to micromolar concentrations of octopamine induced oscillatory increases in the intracellular Ca2+ concentration. In contrast to octopamine, tyramine only elicited Ca2+ responses at micromolar concentrations. The gene is abundantly expressed in many somata of the honeybee brain, suggesting that this octopamine receptor is involved in the processing of sensory inputs, antennal motor outputs and higher‐order brain functions.
Neuronal HuD gene encoding a mRNA stability regulator is transcriptionally repressed by thyroid hormone
Authors: Cuadrado Ana , Navarro‐Yubero Cristina , Furneaux Henry , Muñoz Alberto 
Published: July 2003

AbstractMany genes governed by thyroid hormone (T3) lack binding sites for its receptor (TR) and are thought to be post‐transcriptionally regulated by T3. Here we demonstrate that the HuD gene, which encodes a neurone‐specific protein that binds to mRNA and modulates its stability, is regulated by T3. HuD RNA and protein expression were strongly up‐regulated in specific areas of the hypothyroid rat brain, and reduced by T3 in rat PC12 and mouse N2a cells containing appropriate TR levels. Furthermore, T3 inhibited the transcription of HuD in run‐on assays. Finally, HuD protein bound with high affinity to two sequences in acetylcholinesterase mRNA, and ectopic HuD expression increased its abundance in N2a cells. This is the first report of a gene encoding an mRNA stability regulator that is under T3 control. The results suggest that HuD may mediate some T3 effects by altering the half‐life of mRNAs for acetylcholinesterase and other genes.
Hyperphosphorylation and aggregation of tau in mice expressing normal human tau isoforms
Authors: Andorfer Cathy , Kress Yvonne , Espinoza Marisol , De Silva Rohan , Tucker Kerry L. , Barde Yves‐Alain , Duff Karen , Davies Peter 
Published: July 2003

AbstractNeurofibrillary tangles are composed of insoluble aggregates of the microtubule‐associated protein tau. In Alzheimer's disease the accumulation of neurofibrillary tangles occurs in the absence of tau mutations. Here we present mice that develop pathology from non‐mutant human tau, in the absence of other exogenous factors, including β‐amyloid. The pathology in these mice is Alzheimer‐like, with hyperphosphorylated tau accumulating as aggregated paired helical filaments. This pathologic tau accumulates in the cell bodies and dendrites of neurons in a spatiotemporally relevant distribution.
Relationship between myelin production and dopamine synthesis in the PKU mouse brain
Authors: Joseph Bernadin , Dyer Charissa A. 
Published: July 2003

AbstractPhenylketonuria is caused by specific mutations in the phenylalanine hydroxylase gene and is characterized by elevated blood phenylalanine levels, hypomyelination in forebrain structures, reduced dopamine levels, and cognitive difficulties. To determine whether brain tyrosine levels and/or myelination play a role in the up‐regulation of dopamine, phenylketonuric mice were placed on a low phenylalanine diet for 4 weeks and as blood phenylalanine levels dropped to normal, the relationships between phenylalanine, tyrosine, dopamine, myelin proteins, and axonal proteins in frontal cortex and striatum were determined using gas chromatography mass spectrometry, histology, and western blotting techniques. Blood phenylalanine rapidly decreased from an eight‐fold elevation to near control levels, and blood tyrosine gradually rose from about 50% to near normal values. In frontal cortex and striatum, phenylalanine levels dropped to 2‐ and 1.5‐fold elevations above control, respectively, and tyrosine levels increased but remained less than 70% of control in both structures. In frontal cortex, increases in dopamine and myelin basic protein occurred in a similar biphasic pattern, reaching near normal levels by week 4. In striatum, dopamine and MBP dramatically increased to near normal levels in the first week. Myelination was confirmed histologically and by western blot quantification of phosphorylated neurofilaments. In summary, our results showed: (i) an increase in dopamine despite low brain tyrosine levels and (ii) similar recovery patterns for myelination and dopamine. Since myelin/axonal interactions trigger signaling pathways that result in axonal maturation, we speculate that this interaction also may trigger signals that up‐regulate neurotransmitter synthesis.
Methods for optimizing antiviral combination therapies
Authors: Beerenwinkel Niko , Lengauer Thomas , Däumer Martin , Kaiser Rolf , Walter Hauke , Korn Klaus , Hoffmann Daniel , Selbig Joachim 
Published: July 2003

Abstract
Motivation: Despite some progress with antiretroviral combination therapies, therapeutic success in the management of HIV-infected patients is limited. The evolution of drug-resistant genetic variants in response to therapy plays a key role in treatment failure and finding a new potent drug combination after therapy failure is considered challenging.
Results: To estimate the activity of a drug combination against a particular viral strain, we develop a scoring function whose independent variables describe a set of antiviral agents and viral DNA sequences coding for the molecular targets of the respective drugs. The construction of this activity score involves (1) predicting phenotypic drug resistance from genotypes for each drug individually, (2) probabilistic modeling of predicted resistance values and integration into a score for drug combinations, and (3) searching through the mutational neighborhood of the considered strain in order to estimate activity on nearby mutants. For a clinical data set, we determine the optimal search depth and show that the scoring scheme is predictive of therapeutic outcome. Properties of the activity score and applications are discussed.
Contact: beerenwinkel@mpi-sb.mpg.de
*To whom correspondence should be addressed.
Keywords: HIV, antiretroviral therapy, drug resistance, SVM regression, therapy optimization, sequence space search.
Remote homology detection: a motif based approach
Authors: Ben-Hur Asa , Brutlag Douglas 
Published: July 2003

Abstract
Motivation: Remote homology detection is the problem of detecting homology in cases of low sequence similarity. It is a hard computational problem with no approach that works well in all cases.
Results: We present a method for detecting remote homology that is based on the presence of discrete sequence motifs. The motif content of a pair of sequences is used to define a similarity that is used as a kernel for a Support Vector Machine (SVM) classifier. We test the method on two remote homology detection tasks: prediction of a previously unseen SCOP family and prediction of an enzyme class given other enzymes that have a similar function on other substrates. We find that it performs significantly better than an SVM method that uses BLAST or Smith-Waterman similarity scores as features.
Availability: The software is available from the authors upon request.
Contact: asa.benhur@stanford.edu
Keywords: remote homology, discrete sequence motifs, sequence similarity, Support Vector Machines, kernel methods
*To whom correspondence should be addressed.
SNP and mutation discovery using base-specific
cleavage and MALDI-TOF mass spectrometry
Authors: Böcker Sebastian 
Published: July 2003

Abstract
Motivation: Single Nucleotide Polymorphisms (SNPs) are believed to contribute strongly to the genetic variability in living beings, in particular their disease or drug side effect predispositions. Mutation-induced sequence variations are playing an important role in the development of cancer, among others. From this, it is clear that SNP and mutation discovery is of great interest in today’s Life Sciences. Currently, such discovery is often performed utilizing electrophoresis-based Sanger Sequencing. Discovery of SNPs can also be performed by multiple sequence alignment of publicly available sequence data, but recent studies indicate that only a small percentage of SNPs can be discovered using this approach and, in particular, that SNPs with low frequency are often missed. Other SNP discovery methods only indicate the presence of a SNP in a sample region, but fail to resolve its characterization and localization.
Results: We present a method to discover mutations and SNPs using base-specific cleavage and mass spectrometry. An amplicon of known reference sequence with length usually between 100 and 1000 nt is amplified, transcribed, and cleaved using base-specific endonucleases such as RNAse A or T1. The resulting cleavage products (or fragments) are analyzed by MALDI-TOF mass spectrometry and, comparing the measured spectra with those predicted in-silico, the goal is to discover and pinpoint sequence variations of the sample sequence compared to the reference sequence. A time-efficient algorithm for discovering sequence variations is presented that enables fast analysis of such variations even if the sample sequence differs significantly from the reference sequence.
Contact: boecker@CeBiTec.uni-bielefeld.de
*Currently at AG Genome Informatics, Technische Fakultät, Universität Bielefeld, Germany.
Combining multiple microarray studies and modeling interstudy variation
Authors: Choi Jung Kyoon , Yu Ungsik , Kim Sangsoo , Yoo Ook Joon 
Published: July 2003

Abstract
We have established a method for systematic integration of multiple microarray datasets. The method was applied to two different sets of cancer profiling studies. The change of gene expression in cancer was expressed as ’ effect size’, a standardized index measuring the magnitude of a treatment or covariate effect. The effect sizes were combined to obtain the estimate of the overall mean. The statistical significance was determined by a permutation test extended to multiple datasets. It was shown that the data integration promotes the discovery of small but consistent expression changes with increased sensitivity and reliability. The effect size methods provided the efficient modeling framework for addressing interstudy variation as well. Based on the result of homogeneity tests, a fixed effects model was adopted for one set of datasets that had been created in controlled experimental conditions. By contrast, a random effects model was shown to be appropriate for the other set of datasets that had been published by independent groups. We also developed an alternative modeling procedure based on a Bayesian approach, which would offer flexibility and robustness compared to the classical procedure.
Contact: jkchoi@kaist.ac.kr
Keywords: microarray, meta-analysis, effect size, Bayesian meta-analysis
*To whom correspondence should be addressed.
Combining NLP and probabilistic categorisation for
document and term selection for Swiss-Prot medical annotation
Authors: Dobrokhotov Pavel B. , Goutte Cyril , Veuthey Anne-Lise , Gaussier Eric 
Published: July 2003

Abstract
Motivation: Searching relevant publications for manual database annotation is a tedious task. In this paper, we apply a combination of Natural Language Processing (NLP) and probabilistic classification to re-rank documents returned by PubMed according to their relevance to Swiss-Prot annotation, and to identify significant terms in the documents.
Results: With a Probabilistic Latent Categoriser (PLC) we obtained 69% recall and 59% precision for relevant documents in a representative query. As the PLC technique provides the relative contribution of each term to the final document score, we used the Kullback-Leibler symmetric divergence to determine the most discriminating words for Swiss-Prot medical annotation. This information should allow curators to understand classification results better. It also has great value for fine-tuning the linguistic pre-processing of documents, which in turn can improve the overall classifier performance.
Availability: The medical annotation dataset is available from the authors upon request
Contact: Pavel.Dobrokhotov@isb-sib.ch; Cyril.Goutte@xrce.xerox.com
*To whom correspondence should be addressed.
Protein structure prediction via combinatorial assembly of sub-structural units
Authors: Inbar Yuval , Benyamini Hadar , Nussinov Ruth , Wolfson Haim J. 
Published: July 2003

Abstract
Following the hierarchical nature of protein folding, we propose a three-stage scheme for the prediction of a protein structure from its sequence. First, the sequence is cut to fragments that are each assigned a structure. Second, the assigned structures are combinatorially assembled to form the overall 3D organization. Third, highly ranked predicted arrangements are completed and refined. This work focuses on the second stage of this scheme: the combinatorial assembly. We present CombDock, a combinatorial docking algorithm. CombDock gets an ordered set of protein sub-structures and predicts the inter-contacts that define their overall organization. We reduce the combinatorial assembly to a graph-theory problem, and give a heuristic polynomial solution to this computationally hard problem. We applied CombDock to various examples of structural units of two types: protein domains and building blocks, which are relatively stable sub-structures of domains. Moreover, we tested CombDock using increasingly distorted input, where the native structural units were replaced by similarly folded units extracted from homologous proteins and, in the more difficult cases, from globally unrelated proteins. The algorithm is robust, showing low sensitivity to input distortion. This suggests that CombDock is a useful tool in protein structure prediction that may be applied to large target proteins.
Supplementary information: More tables and figures are available at www.cs.tau.ac.il/~inbaryuv/combdock/
Contact: inbaryuv@tau.ac.il
Keywords: structure prediction, multiple docking, hierarchical model, combinatorial assembly.
*To whom correspondence should be addressed.
Talisman—rapid application development for the grid
Authors: Oinn Thomas M. 
Published: July 2003

Abstract
In order to make use of the emerging grid and network services offered by various institutes and mandated by many current research projects, some kind of user accessible client is required. In contrast with attempts to build generic workbenches, Talisman is designed to allow a bioinformatics expert to rapidly build custom applications, immediately visible using standard web technology, for users who wish to concentrate on the biology of their problem rather than the informatics aspects. As a component of the MyGrid project, it is intended to allow access to arbitrary resources, including but not limited to relational, object and flat file data sources, analysis programs and grid based storage, tracking and distributed annotation systems.
Contact: tmo@ebi.ac.uk
Using hidden Markov models to analyze gene expression time course data
Authors: Schliep Alexander , Schönhuth Alexander , Steinhoff Christine 
Published: July 2003

Abstract
Motivation: Cellular processes cause changes over time. Observing and measuring those changes over time allows insights into the how and why of regulation. The experimental platform for doing the appropriate large-scale experiments to obtain time-courses of expression levels is provided by microarray technology. However, the proper way of analyzing the resulting time course data is still very much an issue under investigation. The inherent time dependencies in the data suggest that clustering techniques which reflect those dependencies yield improved performance.
Results: We propose to use Hidden Markov Models (HMMs) to account for the horizontal dependencies along the time axis in time course data and to cope with the prevalent errors and missing values. The HMMs are used within a model-based clustering framework. We are given a number of clusters, each represented by one Hidden Markov Model from a finite collection encompassing typical qualitative behavior. Then, our method finds in an iterative procedure cluster models and an assignment of data points to these models that maximizes the joint likelihood of clustering and models.
Partially supervised learning—adding groups of labeled data to the initial collection of clusters—is supported. A graphical user interface allows quering an expression profile dataset for time course similar to a prototype graphically defined as a sequence of levels and durations. We also propose a heuristic approach to automate determination of the number of clusters.
We evaluate the method on published yeast cell cycle and fibroblasts serum response datasets, and compare them, with favorable results, to the autoregressive curves method.
Availability: The software is freely available at http://algorithmics.molgen.mpg.de/ghmm
Contact: schliep@molgen.mpg.de
Keywords: Gene Expression, time course, model-based clustering, Hidden Markov Models
*To whom correspondence should be addressed.
Gene structure-based splice variant deconvolution using a microarry platform
Authors: Wang Hui , Hubbell Earl , Hu Jing-shan , Mei Gangwu , Cline Melissa , Lu Gang , Clark Tyson , Siani-Rose Michael A. , Ares Manuel , Kulp David C. , Haussler David 
Published: July 2003

Abstract
Motivation: Alternative splicing allows a single gene to generate multiple mRNAs, which can be translated into functionally and structurally diverse proteins. One gene can have multiple variants coexisting at different concentrations. Estimating the relative abundance of each variant is important for the study of underlying biological function. Microarrays are standard tools that measure gene expression. But most design and analysis has not accounted for splice variants. Thus splice variant-specific chip designs and analysis algorithms are needed for accurate gene expression profiling.
Results: Inspired by Li and Wong (2001), we developed a gene structure-based algorithm to determine the relative abundance of known splice variants. Probe intensities are modeled across multiple experiments using gene structures as constraints. Model parameters are obtained through a maximum likelihood estimation (MLE) process/framework. The algorithm produces the relative concentration of each variant, as well as an affinity term associated with each probe. Validation of the algorithm is performed by a set of controlled spike experiments as well as endogenous tissue samples using a human splice variant array.
Contact: hui_wang@affymetrix.com
*To whom correspondence should be addressed.
Duties to Stakeholders Amidst Pressures from Shareholders: Lessons from an Advisory Panel on Transplant Policy
Authors: Mongoven Ann M. 
Published: July 2003

AbstractThe distinction between stakeholders and shareholders frequently employed in business ethics can illuminate challenges faced by a bioethics advisory panel. I use the distinction to reflect back on the work of an advisory panel on which I served, a panel on US transplant policy. The panel hearings were akin to a shareholders’ meeting, with many stakeholders absent. In addition to ‘hearing out’ the shareholders who were present, the panel had duties to absent stakeholders to insure their interests were included in public discussion. While panel efforts to include stakeholder perspectives rightfully framed its report, such duties should have framed its operating procedures more robustly. The stakeholder/shareholder distinction also offers a critical prism on the actual evolution of organ allocation policy, which the panel failed to influence. Current policy embodies a compromise among shareholders that obscures major stakeholder interests. This results in under‐attention to likely medical benefit of transplant, compared to other allocation criteria. Recognition of duties to stakeholders amidst pressures of shareholders complicates the notion of ‘consensus’ for an advisory panel. Consensus framed on terms defined only by shareholders, not stakeholders, may be an inadequate measure of public interest.
Further Evidence on PPP Adjustment Speeds: the Case of Effective Real Exchange Rates and the EMS*
Authors: Paya Ivan , Venetis Ioannis A. , Peel David A. 
Published: July 2003

AbstractTwo different approaches intend to resolve the ‘puzzling’ slow convergence to purchasing power parity (PPP) reported in the literature [seeRogoff (1996),Journal of Economic Literature, Vol. 34.] On the one hand, there are models that consider a non‐linear adjustment of real exchange rate to PPP induced by transaction costs. Such costs imply the presence of a certain transaction band where adjustment is too costly to be undertaken. On the other hand, there are models that relax the ‘classical’ PPP assumption of constant equilibrium real exchange rates. A prominent theory put together byBalassa (1964,Journal of Political Economy, Vol. 72)andSamuelson (1964Review of Economics and Statistics, Vol. 46), the BS effect, suggests that a non‐constant real exchange rate equilibrium is induced by different productivity growth rates between countries. This paper reconciles those two approaches by considering an exponential smooth transition‐in‐deviation non‐linear adjustment mechanism towards non‐constant equilibrium real exchange rates within the EMS (European Monetary System) and effective rates. The equilibrium is proxied, in a theoretically appealing manner, using deterministic trends and the relative price of non‐tradables to proxy for BS effects. The empirical results provide further support for the hypothesis that real exchange rates are well described by symmetric, nonlinear processes. Furthermore, the half‐life of shocks in such models is found to be dramatically shorter than that obtained in linear models.
Regional Foreign Direct Investment and Wage Spillovers: Plant Level Evidence from the UK Electronics Industry*
Authors: Driffield Nigel , Girma Sourafel 
Published: July 2003

AbstractThis paper examines the extent to which foreign investment in the UK generates wage spillovers in the domestic sector of the economy using a simultaneous dynamic panel data model and focusing on the electronics sector, possibly the most ‘globalized’ sector of UK manufacturing. It finds evidence that the higher wages paid by foreign firms cause wages in the domestic sector to be bid up. This phenomenon is, however, largely confined to the region where foreign direct investment takes place.
Explaining Firms’ Export Behaviour: R&D, Spillovers and the Destination Market*
Authors: Barrios Salvador , Görg Holger , Strobl Eric 
Published: July 2003

AbstractWe examine the importance of a firm's own R&D activity and intra‐sectoral spillovers on the decision to export and the export intensity using firm level panel data for Spain for the period 1990–98. Own R&D activity is found to be an important determinant of export activity. There is little evidence to suggest that Spanish firms benefit from spillovers of the exporting activity of others. However, there is evidence that R&D spillovers exert positive effects on firms’ export ratios. We find a larger marginal impact of R&D spillovers on export intensity of firms exporting to other OECD countries than those exporting to non‐OECD nations.