25 research outputs found

    Tunneling Lifetime of the ttc/VIp Conformer of Glycine in Low-Temperature Matrices

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    Conformer ttc/VIp of glycine and glycine-N,N,O-d(3) has been prepared in low-temperature Ar, Kr, Xe, and N-2 matrices by near-infrared (NIR) laser irradiation of the first OH stretching overtone of conformer ttt/Ip. Glycine (and glycine-N,N,O-d(3)) ttc/VIp was found to convert back to ttt/Ip in the dark by hydrogen-atom tunneling. The observed half-lives of ttc/VIp in Ar, Kr, and Xe matrices at 12 K were 4.4 +/- 1 s (50.0 +/- 1 h), 4.0 +/- 1 s (48.0 +/- 1 h), and 2.8 +/- 1 s (99.3 +/- 2 h), respectively. In correspondence with the observation for the cis-to-trans conversion of formic and acetic acid, the tunneling half-life of glycine ttc/VIp in a N-2 matrix is more than 3 orders of magnitude longer (6.69 X 10(3) and 1.33 X 10(4) s for two different sites) than in noble gas matrices due to complex formation with the host molecules. The present results are important to understand the lack of experimental observation of some computationally predicted conformers of glycine and other amino acids

    Development and validation of a composite disease activity score for juvenile idiopathic arthritis

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    Objective. To develop and validate a composite disease activity score for juvenile idiopathic arthritis (JIA), the Juvenile Arthritis Disease Activity Score (JADAS). Methods. The JADAS includes 4 measures: physician global assessment of disease activity, parent/patient global assessment of well-being, active joint count, and erythrocyte sedimentation rate. These variables are part of the American College of Rheumatology (ACR) Pediatric 30 (Pedi 30), Pedi 50, and Pedi 70 criteria for improvement. Validation analyses were conducted on >4,500 patients and included assessment of construct validity, discriminant validity, and responsiveness to change. Three versions of the JADAS were tested based on 71-joint (range 0 \u2013101), 27-joint (range 0 \u201357), or 10-joint (range 0 \u2013 40) counts. Statistical performances of the JADAS were compared with those of 2 rheumatoid arthritis composite scores, the Disease Activity Score in 28 joints (DAS28) and the Clinical Disease Activity Index (CDAI). Results. The JADAS demonstrated good construct validity, yielding strong correlations with JIA activity measures not included in the score and moderate correlations with the Childhood Health Assessment Questionnaire. Correlations obtained for the 3 JADAS versions were comparable, but superior to those yielded by the DAS28 and CDAI. The area under the curve of the JADAS predicted long-term disease outcome, measured as radiographic progression over 3 years. In 2 clinical trials, the JADAS discriminated well between ACR Pedi 30, Pedi 50, and Pedi 70 response and revealed strong responsiveness to clinical change. Conclusion. The JADAS was found to be a valid instrument for assessment of disease activity in JIA and is potentially applicable in standard clinical care, observational studies, and clinical trials

    Watson–Crick and Sugar-Edge Base Pairing of Cytosine in the Gas Phase: UV and Infrared Spectra of Cytosine·2-Pyridone

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    While keto-amino cytosine is the dominant species in aqueous solution, spectroscopic studies in molecular beams and in noble gas matrices show that other cytosine tautomers prevail in apolar environments. Each of these offers two or three H-bonding sites (Watson–Crick, wobble, sugar-edge). The mass- and isomer-specific S1 ← S0 vibronic spectra of cytosine·2-pyridone (Cyt·2PY) and 1-methylcytosine·2PY are measured using UV laser resonant two-photon ionization (R2PI), UV/UV depletion, and IR depletion spectroscopy. The UV spectra of the Watson–Crick and sugar-edge isomers of Cyt·2PY are separated using UV/UV spectral hole-burning. Five different isomers of Cyt·2PY are observed in a supersonic beam. We show that the Watson–Crick and sugar-edge dimers of keto-amino cytosine with 2PY are the most abundant in the beam, although keto-amino-cytosine is only the third most abundant tautomer in the gas phase. We identify the different isomers by combining three different diagnostic tools: (1) methylation of the cytosine N1–H group prevents formation of both the sugar-edge and wobble isomers and gives the Watson–Crick isomer exclusively. (2) The calculated ground state binding and dissociation energies, relative gas-phase abundances, excitation and the ionization energies are in agreement with the assignment of the dominant Cyt·2PY isomers to the Watson–Crick and sugar-edge complexes of keto-amino cytosine. (3) The comparison of calculated ground state vibrational frequencies to the experimental IR spectra in the carbonyl stretch and NH/OH/CH stretch ranges strengthen this identification

    TAUTOMERS OF CYTOSINE AND THEIR EXCITED ELECTRONIC STATES: A MATRIX ISOLATION SPECTROSCOPIC AND QUANTUM CHEMICAL STUDY

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    Author Institution: Laboratory of Molecular Spectroscopy, Institute of Chemistry, Eotvos Lorand University, Pf. 32, Budapest, H-1518, Hungary; Laboratory of Theoretical Chemistry, Institute of Chemistry, Eotvos Lorand University, Pf. 32, Budapest, H-1518, HungaryWe have measured the IR and UV spectra of cytosine in a low-temperature argon matrix. An attempt was made to determine the tautomeric ratios existing in the matrix, making use of the matrix-isolation IR spectrum and computed IR intensities of the tautomers in a least squares fitting procedure. The mole fractions are about 0.22 for oxo(-amino) form, 0.26 and 0.44 for the two rotamers, respectively, of the hydroxy(-amino) form and 0.08 for the (oxo-)imino tautomer. These ratios were then used to simulate the matrix-isolation UV spectrum as a composite of the individual spectra, the latter calculated \emph{ab initio} at high levels of electron correlation theory. The agreement between simulated and experimental UV spectra seems satisfactory. This indicates that, in contrast to the solid state and solution spectra described up to now by the oxo(-amino) form alone, the reproduction of the matrix-isolation UV spectrum needs at least the hydroxy(-amino) and oxo(-amino) forms, and probably also the (oxo-)imino form

    Agreement between multi-dimensional and renal-specific response criteria in patients with juvenile systemic lupus erythematosus

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    Investigation of expert rule bases, logistic regression, and non-linear machine learning techniques for predicting response to antiretroviral treatment

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    Background: The extreme flexibility of the HIV type-1 (HIV-1) genome makes it challenging to build the ideal antiretroviral treatment regimen. Interpretation of HIV-1 genotypic drug resistance is evolving from rule-based systems guided by expert opinion to data-driven engines developed through machine learning methods. Methods: The aim of the study was to investigate linear and non-linear statistical learning models for classifying short-term virological outcome of antiretroviral treatment. To optimize the model, different feature selection methods were considered. Robust extra-sample error estimation and different loss functions were used to assess model performance. The results were compared with widely used rule-based genotypic interpretation systems (Stanford HIVdb, Rega and ANRS). Results: A set of 3,143 treatment change episodes were extracted from the EuResist database. The dataset included patient demographics, treatment history and viral genotypes. A logistic regression model using high order interaction variables performed better than rulebased genotypic interpretation systems (accuracy 75.63% versus 71.74–73.89%, area under the receiver operating characteristic curve [AUC] 0.76 versus 0.68–0.70) and was equivalent to a random forest model (accuracy 76.16%, AUC 0.77). However, when rule-based genotypic interpretation systems were coupled with additional patient attributes, and the combination was provided as input to the logistic regression model, the performance increased significantly, becoming comparable to the fully data-driven methods. Conclusions: Patient-derived supplementary features significantly improved the accuracy of the prediction of response to treatment, both with rule-based and datadriven interpretation systems. Fully data-driven models derived from large-scale data sources show promise as antiretroviral treatment decision support tools
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