Is Context-aware Reasoning = Case-based Reasoning?

The purpose of this paper is to explore the similarities and differences and then argue for the potential synergies between two methodologies, namely Context-aware Reasoning and Case-based Reasoning, that are amongst the tools which can be used for intelligent environment (IE) system development. Through a case study supported by a review of the literature, we argue that context awareness and case based reasoning are not equal and are complementary methodologies to solve a domain specific problem, rather, the IE development paradigm must build a cooperation between these two approaches to overcome the individual drawbacks and to maximise the success of the IE systems

Synthesis of tenascin and laminin beta2 chain in human bronchial epithelial cells is enhanced by cysteinyl leukotrienes via CysLT1 receptor

<p>Abstract</p> <p>Background</p> <p>Cysteinyl leukotrienes (CysLTs) are key mediators of asthma, but their role in the genesis of airway remodeling is insufficiently understood. Recent evidence suggests that increased expression of tenascin (Tn) and laminin (Ln) β2 chain is indicative of the remodeling activity in asthma, but represents also an example of deposition of extracellular matrix, which affects the airway wall compliance. We tested the hypothesis that CysLTs affect production of Tn and Ln β2 chain by human bronchial epithelial cells and elucidated, which of the CysLT receptors, CysLT₁or CysLT₂, mediate this effect.</p> <p>Methods</p> <p>Cultured BEAS-2B human bronchial epithelial cells were stimulated with leukotriene D₄(LTD₄) and E₄(LTE₄) and evaluated by immunocytochemistry, Western blotting, flow cytometry, and RT-PCR. CysLT receptors were differentially blocked with use of montelukast or BAY u9773.</p> <p>Results</p> <p>LTD₄and LTE₄significantly augmented the expression of Tn, whereas LTD₄, distinctly from LTE₄, was able to increase also the Ln β2 chain. Although the expression of CysLT₂prevailed over that of CysLT₁, the up-regulation of Tn and Ln β2 chain by CysLTs was completely blocked by the CysLT₁-selective antagonist montelukast with no difference between montelukast and the dual antagonist BAY u9773 for the inhibitory capacity.</p> <p>Conclusion</p> <p>These findings suggest that the CysLT-induced up-regulation of Tn and Ln β2 chain, an important epithelium-linked aspect of airway remodeling, is mediated predominantly by the CysLT₁receptor. The results provide a novel aspect to support the use of CysLT₁receptor antagonists in the anti-remodeling treatment of asthma.</p

A Wireless Health Outcomes Monitoring System (WHOMS): development and field testing with cancer patients using mobile phones

BACKGROUND: Health-Related Quality of Life assessment is widely used in clinical research, but rarely in clinical practice. Barriers including practical difficulties administering printed questionnaires have limited their use. Telehealth technology could reduce these barriers and encourage better doctor-patient interaction regarding patient symptoms and quality-of-life monitoring. The aim of this study was to develop a new system for transmitting patients' self-reported outcomes using mobile phones or the internet, and to test whether patients can and will use the system via a mobile phone. METHODS: We have developed a prototype of a Wireless Health Outcomes Monitoring System, which allows structured questionnaires to be sent to the patient by their medical management team. The patients' answers are directly sent to an authorised website immediately accessible by the medical team, and are displayed in a graphic format that highlights the patient's state of health. In the present study, 97 cancer inpatients were asked to complete a ten-item questionnaire. The questionnaire was delivered by display on a mobile phone, and was answered by the patients using the mobile phone keypad. RESULTS: Of the 97 patients, 56 (58%) attempted the questionnaire, and all of these 56 completed it. Only 6% of the total number of questions were left unanswered by patients. Forty-one (42%) patients refused to participate, mostly due to their lack of familiarity with mobile phone use. Compared with those who completed the questionnaire, patients who refused to participate were older, had fewer years of education and were less familiar with new communications technology (mobile phone calls, mobile phone SMS, internet, email). CONCLUSION: More than half of the patients self-completed the questionnaire using the mobile phone. This proportion may increase with the use of multichannel communications which can be incorporated into the system. The proportion may also increase if the patient's partner and/or family were able to assist the patient with using the technology. These preliminary results encourage further studies to identify specific diseases or circumstances where this system could be useful in patients' distance monitoring. Such a system is likely to detect patient suffering earlier, and to activate a well-timed intervention

Automatic prediction of catalytic residues by modeling residue structural neighborhood

Background: Prediction of catalytic residues is a major step in characterizing the function of enzymes. In its simpler formulation, the problem can be cast into a binary classification task at the residue level, by predicting whether the residue is directly involved in the catalytic process. The task is quite hard also when structural information is available, due to the rather wide range of roles a functional residue can play and to the large imbalance between the number of catalytic and non-catalytic residues.Results: We developed an effective representation of structural information by modeling spherical regions around candidate residues, and extracting statistics on the properties of their content such as physico-chemical properties, atomic density, flexibility, presence of water molecules. We trained an SVM classifier combining our features with sequence-based information and previously developed 3D features, and compared its performance with the most recent state-of-the-art approaches on different benchmark datasets. We further analyzed the discriminant power of the information provided by the presence of heterogens in the residue neighborhood.Conclusions: Our structure-based method achieves consistent improvements on all tested datasets over both sequence-based and structure-based state-of-the-art approaches. Structural neighborhood information is shown to be responsible for such results, and predicting the presence of nearby heterogens seems to be a promising direction for further improvements.Journal ArticleResearch Support, N.I.H. Extramuralinfo:eu-repo/semantics/publishe

Search for rare quark-annihilation decays, B --> Ds(*) Phi

We report on searches for B- --> Ds- Phi and B- --> Ds*- Phi. In the context of the Standard Model, these decays are expected to be highly suppressed since they proceed through annihilation of the b and u-bar quarks in the B- meson. Our results are based on 234 million Upsilon(4S) --> B Bbar decays collected with the BABAR detector at SLAC. We find no evidence for these decays, and we set Bayesian 90% confidence level upper limits on the branching fractions BF(B- --> Ds- Phi) Ds*- Phi)<1.2x10^(-5). These results are consistent with Standard Model expectations.Comment: 8 pages, 3 postscript figues, submitted to Phys. Rev. D (Rapid Communications

HemeBIND: a novel method for heme binding residue prediction by combining structural and sequence information

<p>Abstract</p> <p>Background</p> <p>Accurate prediction of binding residues involved in the interactions between proteins and small ligands is one of the major challenges in structural bioinformatics. Heme is an essential and commonly used ligand that plays critical roles in electron transfer, catalysis, signal transduction and gene expression. Although much effort has been devoted to the development of various generic algorithms for ligand binding site prediction over the last decade, no algorithm has been specifically designed to complement experimental techniques for identification of heme binding residues. Consequently, an urgent need is to develop a computational method for recognizing these important residues.</p> <p>Results</p> <p>Here we introduced an efficient algorithm HemeBIND for predicting heme binding residues by integrating structural and sequence information. We systematically investigated the characteristics of binding interfaces based on a non-redundant dataset of heme-protein complexes. It was found that several sequence and structural attributes such as evolutionary conservation, solvent accessibility, depth and protrusion clearly illustrate the differences between heme binding and non-binding residues. These features can then be separately used or combined to build the structure-based classifiers using support vector machine (SVM). The results showed that the information contained in these features is largely complementary and their combination achieved the best performance. To further improve the performance, an attempt has been made to develop a post-processing procedure to reduce the number of false positives. In addition, we built a sequence-based classifier based on SVM and sequence profile as an alternative when only sequence information can be used. Finally, we employed a voting method to combine the outputs of structure-based and sequence-based classifiers, which demonstrated remarkably better performance than the individual classifier alone.</p> <p>Conclusions</p> <p>HemeBIND is the first specialized algorithm used to predict binding residues in protein structures for heme ligands. Extensive experiments indicated that both the structure-based and sequence-based methods have effectively identified heme binding residues while the complementary relationship between them can result in a significant improvement in prediction performance. The value of our method is highlighted through the development of HemeBIND web server that is freely accessible at <url>http://mleg.cse.sc.edu/hemeBIND/</url>.</p

Specificity of Transmembrane Protein Palmitoylation in Yeast

Many proteins are modified after their synthesis, by the addition of a lipid molecule to one or more cysteine residues, through a thioester bond. This modification is called S-acylation, and more commonly palmitoylation. This reaction is carried out by a family of enzymes, called palmitoyltransferases (PATs), characterized by the presence of a conserved 50- aminoacids domain called “Asp-His-His-Cys- Cysteine Rich Domain” (DHHC-CRD). There are 7 members of this family in the yeast Saccharomyces cerevisiae, and each of these proteins is thought to be responsible for the palmitoylation of a subset of substrates. Substrate specificity of PATs, however, is not yet fully understood. Several yeast PATs seem to have overlapping specificity, and it has been proposed that the machinery responsible for palmitoylating peripheral membrane proteins in mammalian cells, lacks specificity altogether

An astrocyte-dependent mechanism for neuronal rhythmogenesis

Communication between neurons rests on their capacity to change their firing pattern to encode different messages. For several vital functions, such as respiration and mastication, neurons need to generate a rhythmic firing pattern. Here we show in the rat trigeminal sensori-motor circuit for mastication that this ability depends on regulation of the extracellular Ca2+ concentration ([Ca2+]e) by astrocytes. In this circuit, astrocytes respond to sensory stimuli that induce neuronal rhythmic activity, and their blockade with a Ca2+ chelator prevents neurons from generating a rhythmic bursting pattern. This ability is restored by adding S100b, an astrocytic Ca2+-binding protein, to the extracellular space, while application of an anti-S100b antibody prevents generation of rhythmic activity. These results indicate that astrocytes regulate a fundamental neuronal property: the capacity to change firing pattern. These findings may have broad implications for many other neural networks whose functions depend on the generation of rhythmic activity

A population-based study of tumor gene expression and risk of breast cancer death among lymph node-negative patients

INTRODUCTION: The Oncotype DX assay was recently reported to predict risk for distant recurrence among a clinical trial population of tamoxifen-treated patients with lymph node-negative, estrogen receptor (ER)-positive breast cancer. To confirm and extend these findings, we evaluated the performance of this 21-gene assay among node-negative patients from a community hospital setting. METHODS: A case-control study was conducted among 4,964 Kaiser Permanente patients diagnosed with node-negative invasive breast cancer from 1985 to 1994 and not treated with adjuvant chemotherapy. Cases (n = 220) were patients who died from breast cancer. Controls (n = 570) were breast cancer patients who were individually matched to cases with respect to age, race, adjuvant tamoxifen, medical facility and diagnosis year, and were alive at the date of death of their matched case. Using an RT-PCR assay, archived tumor tissues were analyzed for expression levels of 16 cancer-related and five reference genes, and a summary risk score (the Recurrence Score) was calculated for each patient. Conditional logistic regression methods were used to estimate the association between risk of breast cancer death and Recurrence Score. RESULTS: After adjusting for tumor size and grade, the Recurrence Score was associated with risk of breast cancer death in ER-positive, tamoxifen-treated and -untreated patients (P = 0.003 and P = 0.03, respectively). At 10 years, the risks for breast cancer death in ER-positive, tamoxifen-treated patients were 2.8% (95% confidence interval [CI] 1.7–3.9%), 10.7% (95% CI 6.3–14.9%), and 15.5% (95% CI 7.6–22.8%) for those in the low, intermediate and high risk Recurrence Score groups, respectively. They were 6.2% (95% CI 4.5–7.9%), 17.8% (95% CI 11.8–23.3%), and 19.9% (95% CI 14.2–25.2%) for ER-positive patients not treated with tamoxifen. In both the tamoxifen-treated and -untreated groups, approximately 50% of patients had low risk Recurrence Score values. CONCLUSION: In this large, population-based study of lymph node-negative patients not treated with chemotherapy, the Recurrence Score was strongly associated with risk of breast cancer death among ER-positive, tamoxifen-treated and -untreated patients