Influenza A H1N1/2009 Infection in Pediatric Solid Organ Transplant Recipients

The aim of this study was to describe the clinical characteristics of pandemic influenza A H1N1 infection. A retrospective study was performed in pediatric patients with solid organ transplantation and confirmed influenza A H1N1/2009 infection from June to December 2009, diagnosed in two Spanish teaching. Forty-nine patients were included. Pneumonia was diagnosed in 4 patients (8.2%), and 3 of them required respiratory support. There were no related deaths. Antiviral treatment within 48 hours was associated with a lower likelihood of pneumonia (0/38, 0%) than treatment started after 48 hours (4/11, 36.3%) (p&0.01).

Large scale purification of presynaptic plasma membranes from Torpedo marmorata electric organ

The presynaptic plasma membrane (PSPM) of cholinergic nerve terminals was purified from Torpedo electric organ using a large-scale procedure. Up to 500 g of frozen electric organ were fractioned in a single run, leading to the isolation of greater than 100 mg of PSPM proteins. The purity of the fraction is similar to that of the synaptosomal plasma membrane obtained after subfractionation of Torpedo synaptosomes as judged by its membrane-bound acetylcholinesterase activity, the number of Glycera convoluta neurotoxin binding sites, and the binding of two monoclonal antibodies directed against PSPM. The specificity of these antibodies for the PSPM is demonstrated by immunofluorescence microscopy.

Clinical pharmacokinetics of mycophenolic acid and its metabolites in solid organ transplant recipient

Mycophenolate mofetil (MMF), an ester prodrug of the immunosuppressant mycophenolic acid (MPA), is widely used for maintenance immunosuppressive therapy and prevention of renal allograft rejection in renal transplant recipients.MPA inhibits inosine monophosphate dehydrogenase (IMPDH), an enzyme involved in the “de novo” synthesis of purine nucleotides, thus suppressing both T-cell and B-cell proliferation. MPA shows a complex pharmacokinetics with considerable interand intra- patient by between- and within patient variabilities associated to MPA exposure. Several factors may contribute to it. The pharmacokinetic modeling according to the population pharmacokinetic approach with the non-linear mixed effects models has shown to be a powerful tool to describe the relationships between MMF doses and the MPA exposures and also to identify potential predictive patients’ demographic and clinical characteristics for dose tailoring during the post-transplant immunosuppresive treatment.

Clinical pharmacokinetics of mycophenolic acid and its metabolites in solid organ transplant recipient

Mycophenolate mofetil (MMF), an ester prodrug of the immunosuppressant mycophenolic acid (MPA), is widely used for maintenance immunosuppressive therapy and prevention of renal allograft rejection in renal transplant recipients.MPA inhibits inosine monophosphate dehydrogenase (IMPDH), an enzyme involved in the “de novo” synthesis of purine nucleotides, thus suppressing both T-cell and B-cell proliferation. MPA shows a complex pharmacokinetics with considerable interand intra- patient by between- and within patient variabilities associated to MPA exposure. Several factors may contribute to it. The pharmacokinetic modeling according to the population pharmacokinetic approach with the non-linear mixed effects models has shown to be a powerful tool to describe the relationships between MMF doses and the MPA exposures and also to identify potential predictive patients’ demographic and clinical characteristics for dose tailoring during the post-transplant immunosuppresive treatment.

Clinical pharmacokinetics of mycophenolic acid and its metabolites in solid organ transplant recipient

Mycophenolate mofetil (MMF), an ester prodrug of the immunosuppressant mycophenolic acid (MPA), is widely used for maintenance immunosuppressive therapy and prevention of renal allograft rejection in renal transplant recipients.MPA inhibits inosine monophosphate dehydrogenase (IMPDH), an enzyme involved in the “de novo” synthesis of purine nucleotides, thus suppressing both T-cell and B-cell proliferation. MPA shows a complex pharmacokinetics with considerable interand intra- patient by between- and within patient variabilities associated to MPA exposure. Several factors may contribute to it. The pharmacokinetic modeling according to the population pharmacokinetic approach with the non-linear mixed effects models has shown to be a powerful tool to describe the relationships between MMF doses and the MPA exposures and also to identify potential predictive patients’ demographic and clinical characteristics for dose tailoring during the post-transplant immunosuppresive treatment.

Clinical pharmacokinetics of mycophenolic acid and its metabolites in solid organ transplant recipient

Mycophenolate mofetil (MMF), an ester prodrug of the immunosuppressant mycophenolic acid (MPA), is widely used for maintenance immunosuppressive therapy and prevention of renal allograft rejection in renal transplant recipients.MPA inhibits inosine monophosphate dehydrogenase (IMPDH), an enzyme involved in the “de novo” synthesis of purine nucleotides, thus suppressing both T-cell and B-cell proliferation. MPA shows a complex pharmacokinetics with considerable interand intra- patient by between- and within patient variabilities associated to MPA exposure. Several factors may contribute to it. The pharmacokinetic modeling according to the population pharmacokinetic approach with the non-linear mixed effects models has shown to be a powerful tool to describe the relationships between MMF doses and the MPA exposures and also to identify potential predictive patients’ demographic and clinical characteristics for dose tailoring during the post-transplant immunosuppresive treatment.

Clinical pharmacokinetics of mycophenolic acid and its metabolites in solid organ transplant recipient

Mycophenolate mofetil (MMF), an ester prodrug of the immunosuppressant mycophenolic acid (MPA), is widely used for maintenance immunosuppressive therapy and prevention of renal allograft rejection in renal transplant recipients.MPA inhibits inosine monophosphate dehydrogenase (IMPDH), an enzyme involved in the “de novo” synthesis of purine nucleotides, thus suppressing both T-cell and B-cell proliferation. MPA shows a complex pharmacokinetics with considerable interand intra- patient by between- and within patient variabilities associated to MPA exposure. Several factors may contribute to it. The pharmacokinetic modeling according to the population pharmacokinetic approach with the non-linear mixed effects models has shown to be a powerful tool to describe the relationships between MMF doses and the MPA exposures and also to identify potential predictive patients’ demographic and clinical characteristics for dose tailoring during the post-transplant immunosuppresive treatment.

An approach to predicting bowing control parameter contours in violin performance

We present a machine learning approach to modeling bowing control parametercontours in violin performance. Using accurate sensing techniqueswe obtain relevant timbre-related bowing control parameters such as bowtransversal velocity, bow pressing force, and bow-bridge distance of eachperformed note. Each performed note is represented by a curve parametervector and a number of note classes are defined. The principal componentsof the data represented by the set of curve parameter vectors are obtainedfor each class. Once curve parameter vectors are expressed in the new spacedefined by the principal components, we train a model based on inductivelogic programming, able to predict curve parameter vectors used for renderingbowing controls. We evaluate the prediction results and show the potentialof the model by predicting bowing control parameter contours from anannotated input score.

Statistical modeling of bowing control applied to violin sound synthesis

Excitation-continuous music instrument control patterns are often not explicitly represented in current sound synthesis techniques when applied to automatic performance. Both physical model-based and sample-based synthesis paradigmswould benefit from a flexible and accurate instrument control model, enabling the improvement of naturalness and realism. Wepresent a framework for modeling bowing control parameters inviolin performance. Nearly non-intrusive sensing techniques allow for accurate acquisition of relevant timbre-related bowing control parameter signals.We model the temporal contour of bow velocity, bow pressing force, and bow-bridge distance as sequences of short Bézier cubic curve segments. Considering different articulations, dynamics, and performance contexts, a number of note classes are defined. Contours of bowing parameters in a performance database are analyzed at note-level by following a predefined grammar that dictates characteristics of curve segment sequences for each of the classes in consideration. As a result, contour analysis of bowing parameters of each note yields an optimal representation vector that is sufficient for reconstructing original contours with significant fidelity. From the resulting representation vectors, we construct a statistical model based on Gaussian mixtures suitable for both the analysis and synthesis of bowing parameter contours. By using the estimated models, synthetic contours can be generated through a bow planning algorithm able to reproduce possible constraints caused by the finite length of the bow. Rendered contours are successfully used in two preliminary synthesis frameworks: digital waveguide-based bowed stringphysical modeling and sample-based spectral-domain synthesis.

Gesture sampling for instrumental sound synthesis: violin bowing as a case study

This paper presents a framework in which samples of bowing gesture parameters are retrieved and concatenated from a database of violin performances by attending to an annotated input score. Resulting bowing parameter signals are then used to synthesize sound by means of both a digital waveguide violin physical model, and an spectral-domainadditive synthesizer.

Statistical modeling of violin bowing parameter contours

We present a framework for modeling right-hand gestures in bowed-string instrument playing, applied to violin. Nearly non-intrusive sensing techniques allow for accurate acquisition of relevant timbre-related bowing gesture parameter cues. We model the temporal contour of bow transversal velocity, bow pressing force, and bow-bridge distance as sequences of short segments, in particular B´ezier cubic curve segments. Considering different articulations, dynamics, andcontexts, a number of note classes is defined. Gesture parameter contours of a performance database are analyzed at note-level by following a predefined grammar that dictatescharacteristics of curve segment sequences for each of the classes into consideration. Based on dynamic programming, gesture parameter contour analysis provides an optimal curve parameter vector for each note. The informationpresent in such parameter vector is enough for reconstructing original gesture parameter contours with significant fidelity. From the resulting representation vectors, weconstruct a statistical model based on Gaussian mixtures, suitable for both analysis and synthesis of bowing gesture parameter contours. We show the potential of the modelby synthesizing bowing gesture parameter contours from an annotated input score. Finally, we point out promising applicationsand developments.

Common Variants of TLR1 Associate with Organ Dysfunction and Sustained Pro- Inflammatory Responses during Sepsis

Background: Toll-like receptors (TLRs) are critical components for host pathogen recognition and variants in genes participating in this response influence susceptibility to infections. Recently, TLR1 gene polymorphisms have been found correlated with whole blood hyper-inflammatory responses to pathogen-associated molecules and associated with sepsis-associated multiorgan dysfunction and acute lung injury (ALI). We examined the association of common variants of TLR1 gene with sepsis-derived complications in an independent study and with serum levels for four inflammatory biomarker among septic patients. Methodology/Principal Findings: Seven tagging single nucleotide polymorphisms of the TLR1 gene were genotyped in samples from a prospective multicenter case-only study of patients with severe sepsis admitted into a network of intensive care units followed for disease severity. Interleukin (IL)-1 b, IL-6, IL-10, and C-reactive protein (CRP) serum levels were measured at study entry, at 48 h and at 7th day. Alleles -7202G and 248Ser, and the 248Ser-602Ile haplotype were associated with circulatory dysfunction among severe septic patients (0.001<=p <= 0.022), and with reduced IL-10 (0.012<= p <=0.047) and elevated CRP (0.011<= p <=0.036) serum levels during the first week of sepsis development. Additionally, the -7202GG genotype was found to be associated with hospital mortality (p =0.017) and ALI (p =0.050) in a combined analysis with European Americans, suggesting common risk effects among studies Conclusions/Significance: These results partially replicate and extend previous findings, supporting that variants of TLR1 gene are determinants of severe complications during sepsis.

Bowing the violin : a case study for auditory-motor pattern modelling in the context of music performance

This project addresses methodological and technological challenges in the development of multi-modal data acquisition and analysis methods for the representation of instrumental playing technique in music performance through auditory-motor patterning models. The case study is violin playing: a multi-modal database of violin performances has been constructed by recording different musicians while playing short exercises on different violins. The exercise set and recording protocol have been designed to sample the space defined by dynamics (from piano to forte) and tone (from sul tasto to sul ponticello), for each bow stroke type being played on each of the four strings (three different pitches per string) at two different tempi. The data, containing audio, video, and motion capture streams, has been processed and segmented to facilitate upcoming analyses. From the acquired motion data, the positions of the instrument string ends and the bow hair ribbon ends are tracked and processed to obtain a number of bowing descriptors suited for a detailed description and analysis of the bow motion patterns taking place during performance. Likewise, a number of sound perceptual attributes are computed from the audio streams. Besides the methodology and the implementation of a number of data acquisition tools, this project introduces preliminary results from analyzing bowing technique on a multi-modal violin performance database that is unique in its class. A further contribution of this project is the data itself, which will be made available to the scientific community through the repovizz platform.