bluuebunny/crossref_metadata_2025_split huggingface dataset:
Expectancy, fear and pain in the prediction of chronic pain and disability: A prospective analysis
Authors: Boersma Katja , Linton Steven J. 
Published: October 2005

AbstractStudies with (sub) acute back pain patients show that negative expectancies predict pain and disability at a one‐year follow up. Yet, it is not clear how expectations relate to other factors in the development of chronic disability such as pain and fear. This study investigates the relationship between expectations, pain‐related fear and pain and studies how these variables are related to the development of chronic pain and disability. Subjects (N = 141) with back and/or neck pain (duration <1 year) were recruited via primary care. They completed measures on pain, expectancy, pain‐related fear (pain‐related negative affect and fear avoidance beliefs) and function. A one‐year follow up was conducted with regard to pain and function. It was found that pain, expectancy, pain‐related fear and function were strongly interrelated. In the cross‐sectional analyses negative expectancies were best explained by frequent pain and a belief in an underlying and serious medical problem. Prospectively, negative expectancy, negative affect and a belief that activity may result in (re) injury or increased pain, explained unique variance in both pain and function at one‐year follow up. In conclusion, expectancy, negative affect and fear avoidance beliefs are interrelated constructs that have predictive value for future pain and disability. Clinically, it can be helpful to inquire about beliefs, expectancy and distress as an indication of risk as well as to guide intervention. However, the strong interrelations between the variables call for precaution in treating them as if they were separate entities existing in reality.
Analysis and improvement of delivery operations at the San Francisco Public Library
Authors: Apte Uday M. , Mason Florence M. 
Published: October 2005

AbstractUrban public library systems have always transported and delivered library materials within their branch systems. In recent years, however, the introduction of internet‐based, online library catalog systems has allowed users to search the library's catalog, select and reserve a book or a video and have it delivered to the branch of their choice. Consequently, the demand for delivery services is increasing at rapid rate in large urban public libraries systems.Having experienced a similar growth in the demand for delivered items, the San Francisco Public Library (SFPL) commissioned a study to improve its delivery operations. Using operations management concepts, such as pre‐sorting of material to avoid double handling, cross docking to reduce cycle time of delivery, and workload balancing among delivery routes to effectively increase delivery capacity, the delivery operations were restructured. We developed optimization models for library delivery operations that specifically accounted for pre‐sorting, cross docking and route balancing. We also developed heuristics for solving these models and implemented them to redesign the delivery operations at SFPL.The redesigned delivery operations will reduce the cycle time and the cost of delivery by almost half. Furthermore, through balanced utilization of existing truck capacities, the delivery operations will be able to handle significantly larger delivery volume and thereby accommodate future delivery service growth without additional investments. The operations management concepts and techniques illustrated in this paper through the example of SFPL should prove to be useful to other urban, multi‐branch library systems as they deal with their delivery challenges.
The Stratigraphy and Fire History of the Kutai Peatlands, Kalimantan, Indonesia
Authors: Hope Geoffrey , Chokkalingam Unna , Anwar Syaiful 
Published: October 2005

AbstractThe equatorial peatlands of the Kutai lowland of eastern Kalimantan are generally 4–10 m in thickness but some sections exceed 16 m in depth. The deposition of peat commenced about 8000 yrs ago after shallow flooding of the basin by the Mahakam River. The earliest vegetation is aPandanusswamp which grades upwards to swamp forest dominated by dipterocarps. The peatland has expanded laterally and rivers have maintained narrow levee-channel tracks through the swamp, which has grown vertically in balance with river accretion. Historical fires are associated with extreme El Niño years of drought, but human agency is important. The fires of 1982–1983 and 1997–1998 burnt up to 85% of the vegetation on the peatland. Although charcoal analyses show that fire has occurred throughout the history of the peatland, it is rare in forests remote from rivers until the last 3000 years and only common within the last millennium. Fires are earlier and more frequent in sites accessible from waterways, and floodplains have been widely burnt down to water table or below, forming extensive lakes.
Intravenous IGF‐I receptor antisense reduces IGF‐IR expression and diminishes pressor responses to angiotensin II in conscious normotensive rats
Authors: Nguyen Tien Thuy , White Paul James 
Published: October 2005

Given the variety of cardiovascular effects of insulin‐like growth factor‐I (IGF‐I), we investigated the effects of a functional deficit in IGF‐I signalling in the conscious rat cardiovascular system using intravenous IGF‐I receptor antisense (AS, 0.5 nmol) treatment.
Insulin‐like growth factor‐I receptor (IGF‐IR) immunoreactivity was reduced in IGF‐IR AS‐treated tail arteries. Western immunoblot analysis demonstrated a decrease in cardiac IGF‐IR in IGF‐IR AS‐treated rats; treatment reduced the expression of IGF‐IR to 83±6% of that in samples from vehicle‐treated rats, compared to 99±3% for a control, full‐mismatch oligonucleotide (MM‐18) or 100% (vehicle).
IGF‐IR AS treatment had no effect on resting blood pressure during the 14‐day treatment period.
Pressor responses (as measured by increase in systolic arterial pressure) to angiotensin II (AngII) gradually decreased over 2 weeks treatment with IGF‐IR AS (5 × 0.5 nmol per intravenous injection, 2 weeks), and were significantly reduced at treatment day 14 compared to day 7 (2.7‐fold rightward shift). IGF‐IR AS treatment caused a significant rightward shift in the angiotensin II (AngII) dose–response compared to both vehicle and full‐mismatch treated rats (4.0‐fold shift compared to vehicle, P<0.01, n=6–14).
There was a significant decrease in cardiac angiotensin II type 1 receptor (AT1R) expression in AS‐treated rats compared to vehicle‐treated rats; cardiac AT1R was decreased to 80±6% in comparison to 100%. AT1R immunoreactivity was also reduced in IGF‐IR AS‐treated tail arteries.
IGF‐IR AS treatment resulted in structural changes in both the heart and aortae, with small but significant differences observed between left ventricle/bodyweight ratios of AS and both vehicle‐ and MM‐18‐treated rats (n=8, P<0.05). Aortic cross‐sectional areas of AS‐treated rats were significantly lower than MM‐18‐ and vehicle‐treated rats (27.4±5.7% reduction of vehicle‐treated samples, n=8, P<0.01).
The results of this study suggest that an induced loss of IGF‐IR, while not affecting resting blood pressure, has a predominantly inhibitory effect on vascular response to vasoconstrictor agents including angiotensin II. This may occur through downstream effects on AT1R expression, via modulation of the expression of receptors for other vasoactive signalling molecules, or via changes in myocyte proliferation.

British Journal of Pharmacology (2005) 146, 935–941. doi:10.1038/sj.bjp.0706378
Role of the PKC/CPI‐17 pathway in enhanced contractile responses of mesenteric arteries from diabetic rats to α‐adrenoceptor stimulation
Authors: Mueed Irem , Zhang Lili , MacLeod Kathleen M 
Published: October 2005

Protein kinase C (PKC) may contribute to enhanced contractile responses of arteries from streptozotocin‐diabetic rats to stimulation of G‐protein coupled receptors. This was investigated by comparing the effects of PKC inhibitors on contractile responses of mesenteric arteries from diabetic and age‐matched control rats to noradrenaline (NA) and endothelin‐1 (ET‐1). The effects of NA and ET‐1 on the distribution of three isoforms of PKC implicated in contraction were also determined. In addition, the effect of NA on phosphorylation of CPI‐17, a substrate for PKC, was investigated.
Contractile responses of endothelium‐denuded arteries from diabetic rats to NA were enhanced, but were normalized by PKC inhibition. In contrast, contractile responses to ET‐1 were not significantly different, and were blocked to a similar extent by PKC inhibition, in arteries from control and diabetic rats.
NA produced only a small increase in particulate levels of PKCɛ in control arteries (to 125±8% of levels in untreated arteries), but a significant increase in particulate PKCα (to 190±22%) and a much greater increase in particulate PKCɛ (to 230±19%) in arteries from diabetic rats. ET‐1 increased particulate PKCα and ɛ to a similar extent in arteries from control and diabetic rats.
NA significantly enhanced CPI‐17 phosphorylation from a basal level of 22±10 to 71±7% of total in arteries from diabetic rats, and this was prevented by PKC inhibition. NA had no detectable effect on CPI‐17 phosphorylation in arteries from control rats.
These data suggest that NA‐induced activation of PKC and CPI‐17, its downstream target, is selectively enhanced in arteries from diabetic rats, and mediates the enhanced contractile responses to this agonist.

British Journal of Pharmacology (2005) 146, 972–982. doi:10.1038/sj.bjp.0706398
Inhibition of RhoA/Rho kinase pathway is involved in the beneficial effect of sildenafil on pulmonary hypertension
Authors: Guilluy Christophe , Sauzeau Vincent , Rolli‐Derkinderen Malvyne , Guérin Patrice , Sagan Christine , Pacaud Pierre , Loirand Gervaise 
Published: October 2005

Inhibition of the type 5 phosphodiesterase and inhibition of Rho kinase are both effective in reducing pulmonary hypertension (PH). Here we investigate whether Rho kinase inhibition is involved in the beneficial effect of the type 5 phosphodiesterase inhibitor sildenafil on PH.Chronic hypoxia‐induced PH in rats is associated with an increase in RhoA activity in pulmonary artery that was maximal after 2 days (10.7±0.9‐fold increase,n=6,P<0.001). The activity of Rho kinase assessed by measuring the level of myosin phosphatase target subunit 1 (MYPT1) phosphorylation was also increased (5.7±0.8‐fold over control,n=8).Chronic fasudil (30 mg kg−1 day−1; 14 days) and sildenafil (25 mg kg−1 day−1; 14 days) treatments reduced PH and pulmonary cardiovascular remodelling, and inhibited the MYPT1 phosphorylation in pulmonary artery from hypoxic rats by 82.3±3% (n=4) and by 76.6±2% (n=4), respectively.The inhibitory effect of sildenafil (10 μM) on MYPT1 phosphorylation was demonstrated by the loss of actin stress fibres in vascular smooth muscle cells. However,in vitrokinase assays indicated that sildenafil had no direct inhibitory action on Rho kinase activity.Sildenafil treatment induced increased RhoA phosphorylation and association to its cytosolic inhibitory protein, guanine dissociation inhibitor (GDI) in pulmonary artery.We propose that sildenafil inhibits RhoA/Rho kinase‐dependent functions in pulmonary artery through enhanced RhoA phosphorylation and cytosolic sequestration by GDI. The inhibition of intracellular events downstream of RhoA thus participates in the beneficial effect of sildenafil on PH.British Journal of Pharmacology(2005)146, 1010–1018. doi:10.1038/sj.bjp.0706408
Plant cannabinoids: a neglected pharmacological treasure trove
Authors: Mechoulam Raphael 
Published: October 2005

Most of the cannabinoids in Cannabis sativa L. have not been fully evaluated for their pharmacological activity. A publication in this issue presents evidence that a plant cannabinoid, Δ9‐tetrahydrocannabivarin is a potent antagonist of anandamide, a major endogenous cannabinoid. It seems possible that many of the non‐psychoactive constituents of this plant will be of biological interest.British Journal of Pharmacology (2005) 146, 913–915. doi:10.1038/sj.bjp.0706415
The crucial role of metal ions in neurodegeneration: the basis for a promising therapeutic strategy
Authors: Gaeta Alessandra , Hider Robert C 
Published: October 2005

The variety of factors and events involved in neurodegeneration renders the subject a major challenge. Neurodegenerative disorders include a number of different pathological conditions, which share similar critical metabolic processes, such as protein aggregation and oxidative stress, both of which are associated with the involvement of metal ions. In this review, Alzheimer's disease, Parkinson's disease and prion disease are discussed, with the aim of identifying common trends underlying these devastating neurological conditions. Chelation therapy could be a valuable therapeutic approach, since metals are considered to be a pharmacological target for the rationale design of new therapeutic agents directed towards the treatment of neurodegeneration.British Journal of Pharmacology (2005) 146, 1041–1059. doi:10.1038/sj.bjp.0706416
Predicting post-synaptic activity in proteins with data mining
Authors: Pappa Gisele L. , Baines Anthony J. , Freitas Alex A. 
Published: October 2005

Abstract
Summary: The bioinformatics problem being addressed in this paper is to predict whether or not a protein has post-synaptic activity. This problem is of great intrinsic interest because proteins with post-synaptic activities are connected with functioning of the nervous system. Indeed, many proteins having post-synaptic activity have been functionally characterized by biochemical, immunological and proteomic exercises. They represent a wide variety of proteins with functions in extracellular signal reception and propagation through intracellular apparatuses, cell adhesion molecules and scaffolding proteins that link them in a web. The challenge is to automatically discover features of the primary sequences of proteins that typically occur in proteins with post-synaptic activity but rarely (or never) occur in proteins without post-synaptic activity, and vice-versa. In this context, we used data mining to automatically discover classification rules that predict whether or not a protein has post-synaptic activity. The discovered rules were analysed with respect to their predictive accuracy (generalization ability) and with respect to their interestingness to biologists (in the sense of representing novel, unexpected knowledge).
Contact: A.A.Freitas@kent.ac.uk
Fast protein classification with multiple networks
Authors: Tsuda Koji , Shin HyunJung , Schölkopf Bernhard 
Published: October 2005

Abstract
Motivation: Support vector machines (SVMs) have been successfully used to classify proteins into functional categories. Recently, to integrate multiple data sources, a semidefinite programming (SDP) based SVM method was introduced. In SDP/SVM, multiple kernel matrices corresponding to each of data sources are combined with weights obtained by solving an SDP. However, when trying to apply SDP/SVM to large problems, the computational cost can become prohibitive, since both converting the data to a kernel matrix for the SVM and solving the SDP are time and memory demanding. Another application-specific drawback arises when some of the data sources are protein networks. A common method of converting the network to a kernel matrix is the diffusion kernel method, which has time complexity of O(n3), and produces a dense matrix of size n × n.
Results: We propose an efficient method of protein classification using multiple protein networks. Available protein networks, such as a physical interaction network or a metabolic network, can be directly incorporated. Vectorial data can also be incorporated after conversion into a network by means of neighbor point connection. Similar to the SDP/SVM method, the combination weights are obtained by convex optimization. Due to the sparsity of network edges, the computation time is nearly linear in the number of edges of the combined network. Additionally, the combination weights provide information useful for discarding noisy or irrelevant networks. Experiments on function prediction of 3588 yeast proteins show promising results: the computation time is enormously reduced, while the accuracy is still comparable to the SDP/SVM method.
Availability: Software and data will be available on request.
Contact: shin@tuebingen.mpg.de
Evaluating the usefulness of protein structure models for molecular replacement
Authors: Giorgetti Alejandro , Raimondo Domenico , Miele Adriana Erica , Tramontano Anna 
Published: October 2005

Abstract
Motivation: We investigate the relationship between the quality of models of protein structure and their usefulness as search models in molecular replacement, a widely used method to experimentally determine protein structures by X-ray crystallography.
Results: We used the available models submitted to the Critical Assessment of Techniques for Protein Structure Prediction to verify in which cases they can be automatically used as search templates for molecular replacement. Our results show that there is a correlation between the quality of the models and their suitability for molecular replacement but that the traditional method of relying on sequence identity between the model and the template used to build it is not diagnostic for the success of the procedure.
Availability: Additional data are available at http://cassandra.bio.uniroma1.it/mr-results-casp.html
Contact: anna.tramontano@uniroma1.it
Prediction of regulatory modules comprising microRNAs and target genes
Authors: Yoon Sungroh , De Micheli Giovanni 
Published: October 2005

Abstract
Motivation: MicroRNAs (miRNAs) are small endogenous RNAs that can play important regulatory roles via the RNA-interference pathway by targeting mRNAs for cleavage or translational repression. We propose a computational method to predict miRNA regulatory modules (MRMs) or groups of miRNAs and target genes that are believed to participate cooperatively in post-transcriptional gene regulation.
Results: We tested our method with the human genes and miRNAs, predicting 431 MRMs. We analyze a module with genes: BTG2, WT1, PPM1D, PAK7 and RAB9B, and miRNAs: miR-15a and miR-16. Review of the literature and annotation with Gene Ontology terms reveal that the roles of these genes can indeed be closely related in specific biological processes, such as gene regulation involved in breast, renal and prostate cancers. Furthermore, it has been reported that miR-15a and miR-16 are deleted together in certain types of cancer, suggesting a possible connection between these miRNAs and cancers. Given that most known functionalities of miRNAs are related to negative gene regulation, extending our approach and exploiting the insight thus obtained may provide clues to achieving practical accuracy in the reverse-engineering of gene regulatory networks.
Availability: A list of predicted modules is available from the authors upon request.
Contact: sryoon@stanford.edu
Computational discovery of transcriptional regulatory rules
Authors: Pham Tho Hoan , Clemente José Carlos , Satou Kenji , Ho Tu Bao 
Published: October 2005

Abstract
Motivation: Even in a simple organism like yeast Saccharomyces cerevisiae, transcription is an extremely complex process. The expression of sets of genes can be turned on or off by the binding of specific transcription factors to the promoter regions of genes. Experimental and computational approaches have been proposed to establish mappings of DNA-binding locations of transcription factors. However, although location data obtained from experimental methods are noisy owing to imperfections in the measuring methods, computational approaches suffer from over-prediction problems owing to the short length of the sequence motifs bound by the transcription factors. Also, these interactions are usually environment-dependent: many regulators only bind to the promoter region of genes under specific environmental conditions. Even more, the presence of regulators at a promoter region indicates binding but not necessarily function: the regulator may act positively, negatively or not act at all. Therefore, identifying true and functional interactions between transcription factors and genes in specific environment conditions and describing the relationship between them are still open problems.
Results: We developed a method that combines expression data with genomic location information to discover (1) relevant transcription factors from the set of potential transcription factors of a target gene; and (2) the relationship between the expression behavior of a target gene and that of its relevant transcription factors. Our method is based on rule induction, a machine learning technique that can efficiently deal with noisy domains. When applied to genomic location data with a confidence criterion relaxed to P-value = 0.005, and three different expression datasets of yeast S.cerevisiae, we obtained a set of regulatory rules describing the relationship between the expression behavior of a specific target gene and that of its relevant transcription factors. The resulting rules provide strong evidence of true positive gene-regulator interactions, as well as of protein–protein interactions that could serve to identify transcription complexes.
Availability: Supplementary files are available from http://www.jaist.ac.jp/~h-pham/regulatory-rules
Contact: h-pham@jaist.ac.jp
Identifying active transcription factors and kinases from expression data using pathway queries
Authors: Sohler Florian , Zimmer Ralf 
Published: October 2005

Abstract
Motivation: Although progress has been made identifying regulatory relationships from expression data in general, only few methods have focused on detecting biological mechanisms like active pathways using a single measurement. This is of particular importance when only few measurements are available, e.g. if special cell types or conditions are under investigation. Here we present a method to test user specified hypotheses (pathway queries) on expression data where prior knowledge is given in the form of networks and functional annotations. Based on this method, we develop a scoring function to identify active transcription factors or kinases, thus making a first step toward explaining the measured expression data.
Results: We apply the algorithm to the Rosetta Yeast Compendium dataset, finding that in many cases the results are in concordance with biological knowledge. We were able to confirm that transcription factors and to a lesser degree, kinases identified by our method play an important role in the biological processes affected by the respective knockouts. Furthermore, we show that correlation of inferred activities can provide evidence for a physical interaction or cooperation of transcription factors where correlation of plain expression data fails to do so.
Contact: florian.sohler@bio.ifi.lmu.de