963 research outputs found

    DNA methylation at the mu-1 opioid receptor gene (OPRM1) promoter predicts preoperative, acute, and chronic postsurgical pain after spine fusion.

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    INTRODUCTION:The perioperative pain experience shows great interindividual variability and is difficult to predict. The mu-1 opioid receptor gene (OPRM1) is known to play an important role in opioid-pain pathways. Since deoxyribonucleic acid (DNA) methylation is a potent repressor of gene expression, DNA methylation was evaluated at the OPRM1 promoter, as a predictor of preoperative, acute, and chronic postsurgical pain (CPSP). METHODS:A prospective observational cohort study was conducted in 133 adolescents with idiopathic scoliosis undergoing spine fusion under standard protocols. Data regarding pain, opioid consumption, anxiety, and catastrophizing (using validated questionnaires) were collected before and 2-3 months postsurgery. Outcomes evaluated were preoperative pain, acute postoperative pain (area under curve [AUC] for pain scores over 48 hours), and CPSP (numerical rating scale >3/10 at 2-3 months postsurgery). Blood samples collected preoperatively were analyzed for DNA methylation by pyrosequencing of 22 CpG sites at the OPRM1 gene promoter. The association of each pain outcome with the methylation percentage of each CpG site was assessed using multivariable regression, adjusting for significant (P<0.05) nongenetic variables. RESULTS:Majority (83%) of the patients reported no pain preoperatively, while CPSP occurred in 36% of the subjects (44/121). Regression on dichotomized preoperative pain outcome showed association with methylation at six CpG sites (1, 3, 4, 9, 11, and 17) (P<0.05). Methylation at CpG sites 4, 17, and 18 was associated with higher AUC after adjusting for opioid consumption and preoperative pain score (P<0.05). After adjusting for postoperative opioid consumption and preoperative pain score, methylation at CpG sites 13 and 22 was associated with CPSP (P<0.05). DISCUSSION:Novel CPSP biomarkers were identified in an active regulatory region of the OPRM1 gene that binds multiple transcription factors. Inhibition of binding by DNA methylation potentially decreases the OPRM1 gene expression, leading to a decreased response to endogenous and exogenous opioids, and an increased pain experience

    The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective

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    Data augmentation (DA) is a powerful workhorse for bolstering performance in modern machine learning. Specific augmentations like translations and scaling in computer vision are traditionally believed to improve generalization by generating new (artificial) data from the same distribution. However, this traditional viewpoint does not explain the success of prevalent augmentations in modern machine learning (e.g. randomized masking, cutout, mixup), that greatly alter the training data distribution. In this work, we develop a new theoretical framework to characterize the impact of a general class of DA on underparameterized and overparameterized linear model generalization. Our framework reveals that DA induces implicit spectral regularization through a combination of two distinct effects: a) manipulating the relative proportion of eigenvalues of the data covariance matrix in a training-data-dependent manner, and b) uniformly boosting the entire spectrum of the data covariance matrix through ridge regression. These effects, when applied to popular augmentations, give rise to a wide variety of phenomena, including discrepancies in generalization between over-parameterized and under-parameterized regimes and differences between regression and classification tasks. Our framework highlights the nuanced and sometimes surprising impacts of DA on generalization, and serves as a testbed for novel augmentation design.Comment: 72 pages, 8 figure

    Paediatric and adult bronchiectasis: monitoring, cross-infection, role of multi-disciplinary teams and self-management plans

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    Bronchiectasis is a chronic lung disease associated with structurally abnormal bronchi; clinically manifested by a persistent wet/productive cough, airway infections and recurrent exacerbations. Early identification and treatment of acute exacerbations is an integral part of monitoring and annual review, in both adults and children, to minimise further damage due to infection and inflammation. Common modalities used to monitor disease progression include clinical signs and symptoms, frequency of exacerbations and/or number of hospital admissions, lung function (FEV1 %predicted), imaging (radiological severity of disease) and sputum microbiology (chronic infection with P. aeruginosa). There is good evidence that these monitoring tools can be used to accurately assess severity of disease and predict prognosis in terms of mortality and future hospitalisation. Other tools that are currently used in research settings such as health-related quality of life questionnaires, magnetic resonance imaging and lung clearance index can be burdensome and require additional expertise or resource, which limits their use in clinical practice. Studies have demonstrated that cross-infection, especially with P. aeruginosa between patients with bronchiectasis is possible but infrequent. This should not limit participation of patients in group activities such as pulmonary rehabilitation, and simple infection control measures should be carried out to limit the risk of cross-transmission. A multi-disciplinary approach to care which includes respiratory physicians, chest physiotherapists, nurse specialists and other allied health professionals are vital in providing holistic care. Patient education and personalised self-management plans are also important despite limited evidence it improves quality of life or frequency of exacerbations

    Data Security Using Tree Traversal

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    we all know that presently in 21st century one of the most emerging problem is Data Security. There is no guarantee that the data we have sent may be hacked by any Hacker or the data we have sent may reach correctly to the receiver or not. So many data security techniques have been emerged from past 2 to 3 years. But still we need a best technique to protect the data from third parties. Cryptography is an art of scrambling the data in order to provide security and confidentiality. Cryptography is being used in order for the securely transmission of the data. This paper provides a new idea for Data encryption and decryption in order to provide security for data

    Allele-specific suppression of the temperature sensitivity of fitA/fitB mutants of Escherichia coli by a new mutation (fitC4): isolation, characterization and its implications in transcription control

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    The temperature sensitive transcription defective mutant of Escherichia coli originallycalled fitA76 has been shown to harbour two missense mutations namelypheS5 and fit95. In order to obtain a suppressor offitA76, possibly mapping inrpoD locus, a Ts+ derivative (JV4) was isolated from afitA76 mutant. It was found that JV4 neither harbours the lesions present in the original fitA 76 nor a suppressor that maps in or nearrpoD. We show that JV4 harbours a modified form offitA76 (designatedfitA76*) together with its suppressor. The results presented here indicate that thefit95 lesion is intact in the fitA 76* mutant and the modification should be at the position of pheS5. Based on the cotransduction of the suppressor mutation and/or its wild type allelewith pps, aroD andzdj-3124::Tn10 kan we have mapped its location to 39.01 min on theE. coli chromosome. We tentatively designate the locus defined by this new extragenic suppressoras fitC and the suppressor allele asfitC4. While fitC4 could suppress the Ts phenotype of fitA76* present in JV4, it fails to suppress the Ts phenotype of the original fitA76 mutant (harbouringpheS5 and fit95). AlsofitC4 could suppress the Ts phenotype of a strain harbouringonly pheS5. Interestingly, thefitC4 Ts phenotype could also be suppressed byfit95. The pattern of decay of pulse labelled RNA in the strains harbouring fitC4 and the fitA76* resembles that of the original fitA76 mutant implying a transcription defect similar to that offitA76 in both these mutants. The implications of these findings with special reference to transcription control by Fit factors in vivo are discussed
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