Type A quadricuspid aortic valve and ascending aorta aneurysm: a rare combination.

Quadricuspid aortic valve (QAV) is a rare congenital anomaly associated with aortic valve insufficiency and significant morbidity, and requires the replacement or, rarely, the repair of the malfunctioning heart valve. A QAV associated with an ascending aorta aneurysm is an extremely rare anatomic combination with a hypothetical, but not clear, shared embryological etiology. To date, only two cases of type B QAV with ascending aorta aneurysm have been reported. Herein is described the first ever case of a 38-year-old male suffering from severe symptomatic aortic valve regurgitation due to a type A QAV, associated with an ascending aorta aneurism, who underwent a successful combined replacement of the aortic valve and ascending aorta.

Dose-dependent influence of didanosine on immune recovery in HIV-infected patients treated with tenofovir.

BACKGROUND: Antiretroviral therapy (ART) containing tenofovir disoproxil fumarate (TDF) and didanosine (ddI) has been associated with poor immune recovery despite virologic success. This effect might be related to ddI toxicity since ddI exposure is substantially increased by TDF. OBJECTIVE: To analyze whether immune recovery during ART with TDF and ddI is ddI-dose dependent. DESIGN AND METHODS: A retrospective longitudinal analysis of immune recovery measured by the CD4 T-cell slope in 614 patients treated with ART containing TDF with or without ddI. Patients were stratified according to the tertiles of their weight-adjusted ddI dose: low dose (< 3.3 mg/kg), intermediate dose (3.3-4.1 mg/kg) and high dose (> 4.1 mg/kg). Cofactors modifying the degree of immune recovery after starting TDF-containing ART were identified by univariable and multivariable linear regression analyses. RESULTS: CD4 T-cell slopes were comparable between patients treated with TDF and a weight-adjusted ddI-dose of < 4.1 mg/kg per day (n = 143) versus TDF-without-ddI (n = 393). In the multivariable model the slopes differed by -13 CD4 T cells/mul per year [95% confidence interval (CI), -42 to 17; P = 0.40]. In contrast, patients treated with TDF and a higher ddI dose (> 4.1 mg/kg per day, n = 78) experienced a significantly impaired immune recovery (-47 CD4 T cells/microl per year; 95% CI, -82 to -12; P = 0.009). The virologic response was comparable between the different treatment groups. CONCLUSIONS: Immune recovery is impaired, when high doses of ddI (> 4.1 mg/kg) are given in combination with TDF. If the dose of ddI is adjusted to less than 4.1 mg/kg per day, immune recovery is similar to other TDF-containing ART regimen.

Bayesian nash equilibrium in ''linear'' cournot models with private information about costs

Calculating explicit closed form solutions of Cournot models where firms have private information about their costs is, in general, very cumbersome. Most authors consider therefore linear demands and constant marginal costs. However, within this framework, the nonnegativity constraint on prices (and quantities) has been ignored or not properly dealt with and the correct calculation of all Bayesian Nash equilibria is more complicated than expected. Moreover, multiple symmetric and interior Bayesianf equilibria may exist for an open set of parameters. The reason for this is that linear demand is not really linear, since there is a kink at zero price: the general ''linear'' inverse demand function is P (Q) = max{a - bQ, 0} rather than P (Q) = a - bQ.

β-Lactam Monotherapy vs β-Lactam-Macrolide Combination Treatment in Moderately Severe Community-Acquired Pneumonia: A Randomized Noninferiority Trial.

IMPORTANCE: The clinical benefit of adding a macrolide to a β-lactam for empirical treatment of moderately severe community-acquired pneumonia remains controversial. OBJECTIVE: To test noninferiority of a β-lactam alone compared with a β-lactam and macrolide combination in moderately severe community-acquired pneumonia. DESIGN, SETTING, AND PARTICIPANTS: Open-label, multicenter, noninferiority, randomized trial conducted from January 13, 2009, through January 31, 2013, in 580 immunocompetent adult patients hospitalized in 6 acute care hospitals in Switzerland for moderately severe community-acquired pneumonia. Follow-up extended to 90 days. Outcome assessors were masked to treatment allocation. INTERVENTIONS: Patients were treated with a β-lactam and a macrolide (combination arm) or with a β-lactam alone (monotherapy arm). Legionella pneumophila infection was systematically searched and treated by addition of a macrolide to the monotherapy arm. MAIN OUTCOMES AND MEASURES: Proportion of patients not reaching clinical stability (heart rate <100/min, systolic blood pressure >90 mm Hg, temperature <38.0°C, respiratory rate <24/min, and oxygen saturation >90% on room air) at day 7. RESULTS: After 7 days of treatment, 120 of 291 patients (41.2%) in the monotherapy arm vs 97 of 289 (33.6%) in the combination arm had not reached clinical stability (7.6% difference, P = .07). The upper limit of the 1-sided 90% CI was 13.0%, exceeding the predefined noninferiority boundary of 8%. Patients infected with atypical pathogens (hazard ratio [HR], 0.33; 95% CI, 0.13-0.85) or with Pneumonia Severity Index (PSI) category IV pneumonia (HR, 0.81; 95% CI, 0.59-1.10) were less likely to reach clinical stability with monotherapy, whereas patients not infected with atypical pathogens (HR, 0.99; 95% CI, 0.80-1.22) or with PSI category I to III pneumonia (HR, 1.06; 95% CI, 0.82-1.36) had equivalent outcomes in the 2 arms. There were more 30-day readmissions in the monotherapy arm (7.9% vs 3.1%, P = .01). Mortality, intensive care unit admission, complications, length of stay, and recurrence of pneumonia within 90 days did not differ between the 2 arms. CONCLUSIONS AND RELEVANCE: We did not find noninferiority of β-lactam monotherapy in patients hospitalized for moderately severe community-acquired pneumonia. Patients infected with atypical pathogens or with PSI category IV pneumonia had delayed clinical stability with monotherapy. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00818610.

Genetic structure of a linear population of Beta vulgaris ssp maritima (sea beet) revealed by isozyme and RFLP analysis

Knowledge of the genetic structure of plant populations is necessary for the understanding of the dynamics of major ecological processes. It also has applications in conservation biology and risk assessment for genetically modified crops. This paper reports the genetic structure of a linear population of sea beet, Beta vulgaris ssp. maritima (the wild relative of sugar beet), on Furzey Island, Poole Harbour. The relative spatial positions of the plants were accurately mapped and the plants were scored for variation at isozyme and RFLP loci. Structure was analysed by repeated subdivision of the population to find the average size of a randomly mating group. Estimates of F-ST between randomly mating units were then made, and gave patterns consistent with the structure of the population being determined largely by founder effects. The implications of these results for the monitoring of transgene spread in wild sea beet populations are discussed.

Linear response functions for a vibrational configuration interaction state

Linear response functions are implemented for a vibrational configuration interaction state allowing accurate analytical calculations of pure vibrational contributions to dynamical polarizabilities. Sample calculations are presented for the pure vibrational contributions to the polarizabilities of water and formaldehyde. We discuss the convergence of the results with respect to various details of the vibrational wave function description as well as the potential and property surfaces. We also analyze the frequency dependence of the linear response function and the effect of accounting phenomenologically for the finite lifetime of the excited vibrational states. Finally, we compare the analytical response approach to a sum-over-states approach

Variational calculation of vibrational linear and nonlinear optical properties

A variational approach for reliably calculating vibrational linear and nonlinear optical properties of molecules with large electrical and/or mechanical anharmonicity is introduced. This approach utilizes a self-consistent solution of the vibrational Schrödinger equation for the complete field-dependent potential-energy surface and, then, adds higher-level vibrational correlation corrections as desired. An initial application is made to static properties for three molecules of widely varying anharmonicity using the lowest-level vibrational correlation treatment (i.e., vibrational Møller-Plesset perturbation theory). Our results indicate when the conventional Bishop-Kirtman perturbation method can be expected to break down and when high-level vibrational correlation methods are likely to be required. Future improvements and extensions are discussed

Combination of fluorescence microscopy and nanomotion detection to characterize bacteria.

Antibiotic-resistant pathogens are a major health concern in everyday clinical practice. Because their detection by conventional microbial techniques requires minimally 24 h, some of us have recently introduced a nanomechanical sensor, which can reveal motion at the nanoscale. By monitoring the fluctuations of the sensor, this technique can evidence the presence of bacteria and their susceptibility to antibiotics in less than 1 h. Their amplitude correlates to the metabolism of the bacteria and is a powerful tool to characterize these microorganisms at low densities. This technique is new and calls for an effort to optimize its protocol and determine its limits. Indeed, many questions remain unanswered, such as the detection limits or the correlation between the bacterial distribution on the sensor and the detection's output. In this work, we couple fluorescence microscopy to the nanomotion investigation to determine the optimal experimental protocols and to highlight the effect of the different bacterial distributions on the sensor.

Towards a new combination therapy for tuberculosis with next generation benzothiazinones.

The benzothiazinone lead compound, BTZ043, kills Mycobacterium tuberculosis by inhibiting the essential flavo-enzyme DprE1, decaprenylphosphoryl-beta-D-ribose 2-epimerase. Here, we synthesized a new series of piperazine-containing benzothiazinones (PBTZ) and show that, like BTZ043, the preclinical candidate PBTZ169 binds covalently to DprE1. The crystal structure of the DprE1-PBTZ169 complex reveals formation of a semimercaptal adduct with Cys387 in the active site and explains the irreversible inactivation of the enzyme. Compared to BTZ043, PBTZ169 has improved potency, safety and efficacy in zebrafish and mouse models of tuberculosis (TB). When combined with other TB drugs, PBTZ169 showed additive activity against M. tuberculosis in vitro except with bedaquiline (BDQ) where synergy was observed. A new regimen comprising PBTZ169, BDQ and pyrazinamide was found to be more efficacious than the standard three drug treatment in a murine model of chronic disease. PBTZ169 is thus an attractive drug candidate to treat TB in humans.

Assembling genes from predicted exons in linear time with dynamic programming

In a number of programs for gene structure prediction in higher eukaryotic genomic sequences, exon prediction is decoupled from gene assembly: a large pool of candidate exons is predicted and scored from features located in the query DNA sequence, and candidate genes are assembled from such a pool as sequences of nonoverlapping frame-compatible exons. Genes are scored as a function of the scores of the assembled exons, and the highest scoring candidate gene is assumed to be the most likely gene encoded by the query DNA sequence. Considering additive gene scoring functions, currently available algorithms to determine such a highest scoring candidate gene run in time proportional to the square of the number of predicted exons. Here, we present an algorithm whose running time grows only linearly with the size of the set of predicted exons. Polynomial algorithms rely on the fact that, while scanning the set of predicted exons, the highest scoring gene ending in a given exon can be obtained by appending the exon to the highest scoring among the highest scoring genes ending at each compatible preceding exon. The algorithm here relies on the simple fact that such highest scoring gene can be stored and updated. This requires scanning the set of predicted exons simultaneously by increasing acceptor and donor position. On the other hand, the algorithm described here does not assume an underlying gene structure model. Indeed, the definition of valid gene structures is externally defined in the so-called Gene Model. The Gene Model specifies simply which gene features are allowed immediately upstream which other gene features in valid gene structures. This allows for great flexibility in formulating the gene identification problem. In particular it allows for multiple-gene two-strand predictions and for considering gene features other than coding exons (such as promoter elements) in valid gene structures.

Lack of antitumour activity of human recombinant tumour necrosis factor-alpha, alone or in combination with melphalan in a nude mouse human melanoma xenograft system.

The most promising developments in the field of isolated limb perfusion have centred around the use of the recombinant cytokine tumour necrosis factor-alpha (rTNF-alpha) in combination with melphalan. While the results of clinical trials are impressive, the exact antitumour mechanisms of rTNF-alpha and its role in combination with melphalan remain unclear. Our aim was to study the antitumour activity of human rTNF-alpha with or without the combination of melphalan in a nude mouse human melanoma xenograft system. In a first attempt to define the maximal tolerated single dose of rTNF-alpha in this setting, 15 animals were exposed to increasing doses of rTNF-alpha (60-2500 microg/kg intraperitoneally). All but one animal survived and tumour growth was not influenced by these single dose applications of rTNF-alpha even at the very high doses. Anti-tumour activity of repeated application of melphalan (three times 9 mg/kg in group 2 and three times 6 mg/kg in group 3), of rTNF-alpha alone (nine doses of 50 microg/kg in group 4), and of rTNF-alpha in combination with melphalan (nine doses of 50 microg/kg rTNF-alpha and three times 6 mg/kg melphalan in group 5) was further compared with non-treated animals (group 1). Tumour growth was significantly inhibited in all animals treated with melphalan (group 2, 3 and 5), but was not decreased in animals treated with rTNF-alpha alone (group 4). Mean final tumour volumes and mean tumour weight were not different in group 2 (789 +/- 836 mm3, 0.38 +/- 0.20 g), group 3 (1173 +/- 591 mm3, 0.55 +/- 0.29 g) and group 5 (230 +/- 632 mm3, 0.37 +/- 0.29 g), but significant lower than group 1 (3156 +/- 1512 mm3, 2.35 +/- 0.90 g) and group 4 (3228 +/- 1990 mm3, 2.00 +/- 1.16 g). There were no significant differences between high and low dose melphalan treatment and between melphalan treatment in combination with rTNF-alpha. Histological examination did not show differences between treated and non-treated animals besides slightly inhibited mitotic activities of tumour cells in melphalan-treated animals. While tumour growth of human xenotransplanted melanoma in nude mice could be inhibited by melphalan, we failed to demonstrate any antitumour effect of rTNF-alpha. The combination of melphalan and rTNF-alpha did not enhance the antiproliferative effect of melphalan alone. Human xenotransplanted tumours on nude mice might not be the ideal experimental setting for studies of potential direct antineoplastic activity of rTNF-alpha, and these results support the concept that TNF-alpha exerts its antitumour activity indirectly, possibly by impairing the tumour vasculature and by activating the immune system.

Splitting statistical potentials into meaningful scoring functions: testing the prediction of near-native structures from decoy conformations

Background: Recent advances on high-throughput technologies have produced a vast amount of protein sequences, while the number of high-resolution structures has seen a limited increase. This has impelled the production of many strategies to built protein structures from its sequence, generating a considerable amount of alternative models. The selection of the closest model to the native conformation has thus become crucial for structure prediction. Several methods have been developed to score protein models by energies, knowledge-based potentials and combination of both.Results: Here, we present and demonstrate a theory to split the knowledge-based potentials in scoring terms biologically meaningful and to combine them in new scores to predict near-native structures. Our strategy allows circumventing the problem of defining the reference state. In this approach we give the proof for a simple and linear application that can be further improved by optimizing the combination of Zscores. Using the simplest composite score () we obtained predictions similar to state-of-the-art methods. Besides, our approach has the advantage of identifying the most relevant terms involved in the stability of the protein structure. Finally, we also use the composite Zscores to assess the conformation of models and to detect local errors.Conclusion: We have introduced a method to split knowledge-based potentials and to solve the problem of defining a reference state. The new scores have detected near-native structures as accurately as state-of-art methods and have been successful to identify wrongly modeled regions of many near-native conformations.

On codes, matroids, and secure multiparty computation from linear secret-sharing schemes

Error-correcting codes and matroids have been widely used in the study of ordinary secret sharing schemes. In this paper, the connections between codes, matroids, and a special class of secret sharing schemes, namely, multiplicative linear secret sharing schemes (LSSSs), are studied. Such schemes are known to enable multiparty computation protocols secure against general (nonthreshold) adversaries.Two open problems related to the complexity of multiplicative LSSSs are considered in this paper. The first one deals with strongly multiplicative LSSSs. As opposed to the case of multiplicative LSSSs, it is not known whether there is an efficient method to transform an LSSS into a strongly multiplicative LSSS for the same access structure with a polynomial increase of the complexity. A property of strongly multiplicative LSSSs that could be useful in solving this problem is proved. Namely, using a suitable generalization of the well-known Berlekamp–Welch decoder, it is shown that all strongly multiplicative LSSSs enable efficient reconstruction of a shared secret in the presence of malicious faults. The second one is to characterize the access structures of ideal multiplicative LSSSs. Specifically, the considered open problem is to determine whether all self-dual vector space access structures are in this situation. By the aforementioned connection, this in fact constitutes an open problem about matroid theory, since it can be restated in terms of representability of identically self-dual matroids by self-dual codes. A new concept is introduced, the flat-partition, that provides a useful classification of identically self-dual matroids. Uniform identically self-dual matroids, which are known to be representable by self-dual codes, form one of the classes. It is proved that this property also holds for the family of matroids that, in a natural way, is the next class in the above classification: the identically self-dual bipartite matroids.