Women of the beat generation : la traducción de una obra poética coral

Comentario a la traducción por encargo del libro WOTBG, centrado en las muestras de obra poética de las distintas autoras y la necesidad de conservar sus similitudes y sus diferéncias.

The automatic selection of ventilation parameters during the initial phase of mechanical ventilation.

OBJECTIVE: To test a method that allows automatic set-up of the ventilator controls at the onset of ventilation. DESIGN: Prospective randomized crossover study. SETTING: ICUs in one adult and one children's hospital in Switzerland. PATIENTS: Thirty intubated stable, critically ill patients (20 adults and 10 children). INTERVENTIONS: The patients were ventilated during two 20-min periods using a modified Hamilton AMADEUS ventilator. During the control period the ventilator settings were chosen immediately prior to the study. During the other period individual settings were automatically determined by the ventilatior (AutoInit). MEASUREMENTS AND RESULTS: Pressure, flow, and instantaneous CO2 concentration were measured at the airway opening. From these measurements, series dead space (V(DS)), expiratory time constant (RC), tidal volume (VT, total respiratory frequency (f(tot), minute ventilation (MV), and maximal and mean airway pressure (Paw, max and Paw, mean) were calculated. Arterial blood gases were analyzed at the end of each period. Paw, max was significantly less with the AutoInit ventilator settings while f(tot) was significantly greater (P < 0.05). The other values were not statistically significant. CONCLUSIONS: The AutoInit ventilator settings, which were automatically derived, were acceptable for all patients for a period of 20 min and were not found to be inferior to the control ventilator settings. This makes the AutoInit method potentially useful as an automatic start-up procedure for mechanical ventilation.

Controlled dynamic generation of standard 1,6-hexamethylene diisocyanate aerosols

A procedure for the dynamic generation of 1,6-hexamethylene diisocyanate (HDI) aerosol atmospheres of 70 micrograms m-3 (0.01 ppm) to 1.75 mg m-3 (0.25 ppm), based on the precise control of the evaporation of pure liquid HDI and subsequent dilution with air, was developed. The apparatus consisted of a home-made glass nebulizer coupled with a separation stage to exclude non-respirable droplets (greater than 10 microns). The aerosol concentrations were achieved by passing air through the nebulizer at 1.5-4.5 l. min-1 to generate dynamically 0.01-0.25 ppm of diisocyanate in an experimental chamber of 8.55 m3. The distribution of the liquid aerosol was established with an optical counter and the diisocyanate concentration was determined from samples collected in impingers by a high-pressure liquid chromatographic method. The atmospheres generated were suitable for the evaluation both of sampling procedures full scale, and of analytical methods: at 140 micrograms m-3 (0.02 ppm) they remained stable for 15-min provocation tests in clinical asthma, as verified by breath-zone sampling of exposed patients.

Violence against adolescents: an analysis based on the categories gender and generation

Exploratory and descriptive study based on quantitative and qualitative methods that analyze the phenomenon of violence against adolescents based on gender and generational categories. The data source was reports of violence from the Curitiba Protection Network from 2010 to 2012 and semi-structured interviews with 16 sheltered adolescents. Quantitative data were analyzed using SPSS software version 20.0 and the qualitative data were subjected to content analysis. The adolescents were victims of violence in the household and outside of the family environment, as victims or viewers of violence. The violence was experienced at home, mostly toward girls, with marked overtones of gender violence. More than indicating the magnitude of the issue, this study can give information to help qualify the assistance given to victimized people and address how to face this issue.

Enhanced generation of specific tumor-reactive CTL in vitro by selected Melan-A/MART-1 immunodominant peptide analogues.

The Melan-A/MART-1 gene, which is expressed by normal melanocytes as well as by most fresh melanoma samples and melanoma cell lines, codes for Ags recognized by tumor-reactive CTL. HLA-A*0201-restricted Melan-A-specific CTL recognize primarily the Melan-A(27-35) (AAGIGILTV) and the Melan-A(26-35) (EAAGIGILTV) peptides. The sequences of these two peptides are not necessarily optimal as far as binding to HLA-A*0201 is concerned, since both lack one of the dominant anchor amino acid residues (leucine or methionine) at position 2. In this study we introduced single amino acid substitutions in either one of the two natural peptide sequences with the aim of improving peptide binding to HLA-A*0201 and/or recognition by specific CTL. Surprisingly, analogues of the Melan-A(27-35) peptide, which bound more efficiently than the natural nonapeptide to HLA-A*0201, were poorly recognized by tumor-reactive CTL. In contrast, among the Melan-A(26-35) peptide analogues tested, the peptide ELAGIGILTV was not only able to display stable binding to HLA-A2.1 but was also recognized more efficiently than the natural peptide by two short-term cultured tumor-infiltrated lymph node cell cultures as well as by five of five tumor-reactive CTL clones. Moreover, in vitro generation of tumor-reactive CTL by stimulation of PBMC from HLA-A*0201 melanoma patients with this particular peptide analogue was much more efficient than that observed with either one of the two natural peptides. These results suggest that the Melan-A(26-35) peptide analogue ELAGIGILTV may be more immunogenic than the natural peptides in HLA-A*0201 melanoma patients and should thus be considered as a candidate for future peptide-based vaccine trials.

An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

Discrete devaluations and multiple equilibria in a first generation model of currency crises

The first generation models of currency crises have often been criticized because they predict that, in the absence of very large triggering shocks, currency attacks should be predictable and lead to small devaluations. This paper shows that these features of first generation models are not robust to the inclusion of private information. In particular, this paper analyzes a generalization of the Krugman-Flood-Garber (KFG) model, which relaxes the assumption that all consumers are perfectly informed about the level of fundamentals. In this environment, the KFG equilibrium of zero devaluation is only one of many possible equilibria. In all the other equilibria, the lack of perfect information delays the attack on the currency past the point at which the shadow exchange rate equals the peg, giving rise to unpredictable and discrete devaluations.

Development of a Selective Peptide Macrocycle Inhibitor of Coagulation Factor XII toward the Generation of a Safe Antithrombotic Therapy.

Inhibition of coagulation factor XII (FXII) activity represents an attractive approach for the treatment and prevention of thrombotic diseases. The few existing FXII inhibitors suffer from low selectivity. Using phage display combined to rational design, we developed a potent inhibitor of FXII with more than 100-fold selectivity over related proteases. The highly selective peptide macrocycle is a promising candidate for the control of FXII activity in antithrombotic therapy and a valuable tool in hematology research.

Composition of electricity generation portfolios, pivotal dynamics and market prices

We use a simulation model to study how the diversification of electricity generation portfoliosinfluences wholesale prices. We find that technological diversification generally leads to lower market prices but that the relationship is mediated by the supply to demand ratio. In each demand case there is a threshold where pivotal dynamics change. Pivotal dynamics pre- and post-threshold are the cause of non-linearities in the influence of diversification on market prices. The findings are robust to our choice of behavioural parameters and match close-form solutions where those are available.

Automatic classification of MR scans in Alzheimer's disease.

To be diagnostically useful, structural MRI must reliably distinguish Alzheimer's disease (AD) from normal aging in individual scans. Recent advances in statistical learning theory have led to the application of support vector machines to MRI for detection of a variety of disease states. The aims of this study were to assess how successfully support vector machines assigned individual diagnoses and to determine whether data-sets combined from multiple scanners and different centres could be used to obtain effective classification of scans. We used linear support vector machines to classify the grey matter segment of T1-weighted MR scans from pathologically proven AD patients and cognitively normal elderly individuals obtained from two centres with different scanning equipment. Because the clinical diagnosis of mild AD is difficult we also tested the ability of support vector machines to differentiate control scans from patients without post-mortem confirmation. Finally we sought to use these methods to differentiate scans between patients suffering from AD from those with frontotemporal lobar degeneration. Up to 96% of pathologically verified AD patients were correctly classified using whole brain images. Data from different centres were successfully combined achieving comparable results from the separate analyses. Importantly, data from one centre could be used to train a support vector machine to accurately differentiate AD and normal ageing scans obtained from another centre with different subjects and different scanner equipment. Patients with mild, clinically probable AD and age/sex matched controls were correctly separated in 89% of cases which is compatible with published diagnosis rates in the best clinical centres. This method correctly assigned 89% of patients with post-mortem confirmed diagnosis of either AD or frontotemporal lobar degeneration to their respective group. Our study leads to three conclusions: Firstly, support vector machines successfully separate patients with AD from healthy aging subjects. Secondly, they perform well in the differential diagnosis of two different forms of dementia. Thirdly, the method is robust and can be generalized across different centres. This suggests an important role for computer based diagnostic image analysis for clinical practice.

Generation of the primary hair follicle pattern.

Hair follicles are spaced apart from one another at regular intervals through the skin. Although follicles are predominantly epidermal structures, classical tissue recombination experiments indicated that the underlying dermis defines their location during development. Although many molecules involved in hair follicle formation have been identified, the molecular interactions that determine the emergent property of pattern formation have remained elusive. We have used embryonic skin cultures to dissect signaling responses and patterning outcomes as the skin spatially organizes itself. We find that ectodysplasin receptor (Edar)-bone morphogenetic protein (BMP) signaling and transcriptional interactions are central to generation of the primary hair follicle pattern, with restriction of responsiveness, rather than localization of an inducing ligand, being the key driver in this process. The crux of this patterning mechanism is rapid Edar-positive feedback in the epidermis coupled with induction of dermal BMP4/7. The BMPs in turn repress epidermal Edar and hence follicle fate. Edar activation also induces connective tissue growth factor, an inhibitor of BMP signaling, allowing BMP action only at a distance from their site of synthesis. Consistent with this model, transgenic hyperactivation of Edar signaling leads to widespread overproduction of hair follicles. This Edar-BMP activation-inhibition mechanism appears to operate alongside a labile prepattern, suggesting that Edar-mediated stabilization of beta-catenin active foci is a key event in determining definitive follicle locations.

SwissParam: a fast force field generation tool for small organic molecules.

The drug discovery process has been deeply transformed recently by the use of computational ligand-based or structure-based methods, helping the lead compounds identification and optimization, and finally the delivery of new drug candidates more quickly and at lower cost. Structure-based computational methods for drug discovery mainly involve ligand-protein docking and rapid binding free energy estimation, both of which require force field parameterization for many drug candidates. Here, we present a fast force field generation tool, called SwissParam, able to generate, for arbitrary small organic molecule, topologies, and parameters based on the Merck molecular force field, but in a functional form that is compatible with the CHARMM force field. Output files can be used with CHARMM or GROMACS. The topologies and parameters generated by SwissParam are used by the docking software EADock2 and EADock DSS to describe the small molecules to be docked, whereas the protein is described by the CHARMM force field, and allow them to reach success rates ranging from 56 to 78%. We have also developed a rapid binding free energy estimation approach, using SwissParam for ligands and CHARMM22/27 for proteins, which requires only a short minimization to reproduce the experimental binding free energy of 214 ligand-protein complexes involving 62 different proteins, with a standard error of 2.0 kcal mol(-1), and a correlation coefficient of 0.74. Together, these results demonstrate the relevance of using SwissParam topologies and parameters to describe small organic molecules in computer-aided drug design applications, together with a CHARMM22/27 description of the target protein. SwissParam is available free of charge for academic users at www.swissparam.ch.

A glutathione precursor, N-acetyl-cysteine, modulates mismatch negativity generation in schizophrenia patients

Schizophrenia patients exhibit deficits in low-level processing, including pitch discrimination. This deficiency manifests in auditory evoked potentials (AEPs) as an impaired mismatch negativity (MMN), an electrophysiological response to infrequent target stimuli interspersed among frequent standard stimuli that typically peaks ~100ms post-stimulus onset. NMDA receptor antagonists have been shown to block MMN generation in both animals and humans, and NMDA dysfunction has been linked to the underlying pathophysiology of schizophrenia. A parallel line of evidence indicates that glutathione (GSH) regulation is perturbed in schizophrenia patients at the gene, protein and functional levels (Tosic et al., 2006). This GSH dysregulation leads to NMDA receptors' hypofunction through interaction with their redox site (Steullet et al., 2006). The present study aimed to modulate GSH levels in schizophrenia patients and assessed the effects of such a modulation on MMN generation mechanisms. N-acetyl-cysteine (NAC), a GSH precursor, was administered to schizophrenia patients, using a double-blind cross-over protocol. One group received NAC (2g/day) for 60 days and then placebo for another 60 days, and vice-versa for the second group. AEPs from patients were recorded at the onset of the protocol, at the point of cross-over, and at the end of the study. Participants were instructed to manually respond to target stimuli (2kHz pure tones occurring 20% of the time among 1kHz pure tones). Analyses of AEPs recorded at protocol onset indicated that patients (n=11) were significantly impaired in generating the MMN relative to age-matched controls (n=11). Specifically, the global field power (GFP), an index of AEP magnitude, was measured over the 70- 155ms post-stimulus interval and submitted to an analysis of variance (ANOVA). There was a significant interaction between population and stimulus frequency, indicating impaired MMN generation in patients at protocol onset. Analyses of AEPs recorded during administration of NAC (n=7) versus placebo (n=7) revealed the efficacy of this GSH precursor in modulating MMN generation mechanisms. ANOVA of GFP over the 70- 155ms post-stimulus interval, using stimulus frequency and treatment as within-participants variables, revealed a significant interaction and indicated that NAC can ameliorate MMN generation. We discuss these results in terms of potential therapeutic strategies for schizophrenia.