1,095 research outputs found

    A Multicriteria Decision Analysis Comparing Pharmacotherapy for Chronic Neuropathic Pain, Including Cannabinoids and Cannabis-Based Medical Products

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    BACKGROUND: Pharmacological management of chronic neuropathic pain (CNP) still represents a major clinical challenge. Collective harnessing of both the scientific evidence base and clinical experience (of clinicians and patients) can play a key role in informing treatment pathways and contribute to the debate on specific treatments (e.g., cannabinoids). A group of expert clinicians (pain specialists and psychiatrists), scientists, and patient representatives convened to assess the relative benefit–safety balance of 12 pharmacological treatments, including orally administered cannabinoids/cannabis-based medicinal products, for the treatment of CNP in adults. METHODS: A decision conference provided the process of creating a multicriteria decision analysis (MCDA) model, in which the group collectively scored the drugs on 17 effect criteria relevant to benefits and safety and then weighted the criteria for their clinical relevance. FINDINGS: Cannabis-based medicinal products consisting of tetrahydrocannabinol/cannabidiol (THC/CBD), in a 1:1 ratio, achieved the highest overall score, 79 (out of 100), followed by CBD dominant at 75, then THC dominant at 72. Duloxetine and the gabapentinoids scored in the 60s, amitriptyline, tramadol, and ibuprofen in the 50s, methadone and oxycodone in the 40s, and morphine and fentanyl in the 30s. Sensitivity analyses showed that even if the pain reduction and quality-of-life scores for THC/CBD and THC are halved, their benefit–safety balances remain better than those of the noncannabinoid drugs. INTERPRETATION: The benefit–safety profiles for cannabinoids were higher than for other commonly used medications for CNP largely because they contribute more to quality of life and have a more favorable side effect profile. The results also reflect the shortcomings of alternative pharmacological treatments with respect to safety and mitigation of neuropathic pain symptoms. Further high-quality clinical trials and systematic comprehensive capture of clinical experience with cannabinoids is warranted. These results demonstrate once again the complexity and multimodal mechanisms underlying the clinical experience and impact of chronic pain

    Phosphorylated c-Src in the nucleus is associated with improved patient outcome in ER-positive breast cancer

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    Elevated c-Src protein expression has been shown in breast cancer and <i>in vitro</i> evidence suggests a role in endocrine resistance. To investigate whether c-Src is involved in endocrine resistance, we examined the expression of both total and activated c-Src in human breast cancer specimens from a cohort of oestrogen receptor (ER)-positive tamoxifen-treated breast cancer patients. Tissue microarray technology was employed to analyse 262 tumour specimens taken before tamoxifen treatment. Immunohistochemistry using total c-Src and activated c-Src antibodies was performed. Kaplan–Meier survival curves were constructed and log-rank test were performed. High level of nuclear activated Src was significantly associated with improved overall survival (<i>P</i>=0.047) and lower recurrence rates on tamoxifen (<i>P</i>=0.02). Improved patient outcome was only seen with activated Src in the nucleus. Nuclear activated Src expression was significantly associated with node-negative disease and a lower NPI (<i>P</i><0.05). On subgroup analysis, only ER-positive/progesterone receptor (PgR)-positive tumours were associated with improved survival (<i>P</i>=0.004). This shows that c-Src activity is increased in breast cancer and that activated Src within the nucleus of ER-positive tumours predicts an improved outcome. In ER/PgR-positive disease, activated Src kinase does not appear to be involved in <i>de novo</i> endocrine resistance. Further study is required in ER-negative breast cancer as this may represent a cohort in which it is associated with poor outcome

    Rescaling quality of life values from discrete choice experiments for use as QALYs: a cautionary tale

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    Background: Researchers are increasingly investigating the potential for ordinal tasks such as ranking and discrete choice experiments to estimate QALY health state values. However, the assumptions of random utility theory, which underpin the statistical models used to provide these estimates, have received insufficient attention. In particular, the assumptions made about the decisions between living states and the death state are not satisfied, at least for some people. Estimated values are likely to be incorrectly anchored with respect to death (zero) in such circumstances. Methods: Data from the Investigating Choice Experiments for the preferences of older people CAPability instrument (ICECAP) valuation exercise were analysed. The values (previously anchored to the worst possible state) were rescaled using an ordinal model proposed previously to estimate QALY-like values. Bootstrapping was conducted to vary artificially the proportion of people who conformed to the conventional random utility model underpinning the analyses. Results: Only 26% of respondents conformed unequivocally to the assumptions of conventional random utility theory. At least 14% of respondents unequivocally violated the assumptions. Varying the relative proportions of conforming respondents in sensitivity analyses led to large changes in the estimated QALY values, particularly for lower-valued states. As a result these values could be either positive (considered to be better than death) or negative (considered to be worse than death). Conclusion: Use of a statistical model such as conditional (multinomial) regression to anchor quality of life values from ordinal data to death is inappropriate in the presence of respondents who do not conform to the assumptions of conventional random utility theory. This is clearest when estimating values for that group of respondents observed in valuation samples who refuse to consider any living state to be worse than death: in such circumstances the model cannot be estimated. Only a valuation task requiring respondents to make choices in which both length and quality of life vary can produce estimates that properly reflect the preferences of all respondents

    2D-Qsar for 450 types of amino acid induction peptides with a novel substructure pair descriptor having wider scope

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    <p>Abstract</p> <p>Background</p> <p>Quantitative structure-activity relationships (QSAR) analysis of peptides is helpful for designing various types of drugs such as kinase inhibitor or antigen. Capturing various properties of peptides is essential for analyzing two-dimensional QSAR. A descriptor of peptides is an important element for capturing properties. The atom pair holographic (APH) code is designed for the description of peptides and it represents peptides as the combination of thirty-six types of key atoms and their intermediate binding between two key atoms.</p> <p>Results</p> <p>The substructure pair descriptor (SPAD) represents peptides as the combination of forty-nine types of key substructures and the sequence of amino acid residues between two substructures. The size of the key substructures is larger and the length of the sequence is longer than traditional descriptors. Similarity searches on C5a inhibitor data set and kinase inhibitor data set showed that order of inhibitors become three times higher by representing peptides with SPAD, respectively. Comparing scope of each descriptor shows that SPAD captures different properties from APH.</p> <p>Conclusion</p> <p>QSAR/QSPR for peptides is helpful for designing various types of drugs such as kinase inhibitor and antigen. SPAD is a novel and powerful descriptor for various types of peptides. Accuracy of QSAR/QSPR becomes higher by describing peptides with SPAD.</p

    Parity-Violating Electron Scattering from 4He and the Strange Electric Form Factor of the Nucleon

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    We have measured the parity-violating electroweak asymmetry in the elastic scattering of polarized electrons from ^4He at an average scattering angle = 5.7 degrees and a four-momentum transfer Q^2 = 0.091 GeV^2. From these data, for the first time, the strange electric form factor of the nucleon G^s_E can be isolated. The measured asymmetry of A_PV = (6.72 +/- 0.84 (stat) +/- 0.21 (syst) parts per million yields a value of G^s_E = -0.038 +/- 0.042 (stat) +/- 0.010 (syst), consistent with zero

    Cardiac MR Elastography: Comparison with left ventricular pressure measurement

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    Purpose of the Study: To compare magnetic resonance elastography (MRE) with ventricular pressure changes in an animal model. Methods: Three pigs of different cardiac physiology (weight, 25 to 53 kg; heart rate, 61 to 93 bpm; left ventricular [LV] end-diastolic volume, 35 to 70 ml) were subjected to invasive LV pressure measurement by catheter and noninvasive cardiac MRE. Cardiac MRE was performed in a short-axis view of the heart and applying a 48.3-Hz shear-wave stimulus. Relative changes in LV-shear wave amplitudes during the cardiac cycle were analyzed. Correlation coefficients between wave amplitudes and LV pressure as well as between wave amplitudes and LV diameter were determined. Results: A relationship between MRE and LV pressure was observed in all three animals (R-square [greater than or equal to] 0.76). No correlation was observed between MRE and LV diameter (R-square [less than or equal to] 0.15). Instead, shear wave amplitudes decreased 102 +/- 58 ms earlier than LV diameters at systole and amplitudes increased 175 +/- 40 ms before LV dilatation at diastole. Amplitude ratios between diastole and systole ranged from 2.0 to 2.8, corresponding to LV pressure differences of 60 to 73 mmHg. Conclusion: Externally induced shear waves provide information reflecting intraventricular pressure changes which, if substantiated in further experiments, has potential to make cardiac MRE a unique noninvasive imaging modality for measuring pressure-volume function of the heart

    A Computational Method for Prediction of Excretory Proteins and Application to Identification of Gastric Cancer Markers in Urine

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    A novel computational method for prediction of proteins excreted into urine is presented. The method is based on the identification of a list of distinguishing features between proteins found in the urine of healthy people and proteins deemed not to be urine excretory. These features are used to train a classifier to distinguish the two classes of proteins. When used in conjunction with information of which proteins are differentially expressed in diseased tissues of a specific type versus control tissues, this method can be used to predict potential urine markers for the disease. Here we report the detailed algorithm of this method and an application to identification of urine markers for gastric cancer. The performance of the trained classifier on 163 proteins was experimentally validated using antibody arrays, achieving >80% true positive rate. By applying the classifier on differentially expressed genes in gastric cancer vs normal gastric tissues, it was found that endothelial lipase (EL) was substantially suppressed in the urine samples of 21 gastric cancer patients versus 21 healthy individuals. Overall, we have demonstrated that our predictor for urine excretory proteins is highly effective and could potentially serve as a powerful tool in searches for disease biomarkers in urine in general

    Characterisation of a Desmosterol Reductase Involved in Phytosterol Dealkylation in the Silkworm, Bombyx mori

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    Most species of invertebrate animals cannot synthesise sterols de novo and many that feed on plants dealkylate phytosterols (mostly C29 and C28) yielding cholesterol (C27). The final step of this dealkylation pathway involves desmosterol reductase (DHCR24)-catalysed reduction of desmosterol to cholesterol. We now report the molecular characterisation in the silkworm, Bombyx mori, of such a desmosterol reductase involved in production of cholesterol from phytosterol, rather than in de novo synthesis of cholesterol. Phylogenomic analysis of putative desmosterol reductases revealed the occurrence of various clades that allowed for the identification of a strong reductase candidate gene in Bombyx mori (BGIBMGA 005735). Following PCR-based cloning of the cDNA (1.6 kb) and its heterologous expression in Saccharomyces cerevisae, the recombinant protein catalysed reduction of desmosterol to cholesterol in an NADH- and FAD- dependent reaction
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