Long-term safety and effectiveness of lopinavir/ritonavir in antiretroviral-experienced HIV-1-infected children.

AIM: To evaluate the long-term safety and effectiveness of lopinavir/ritonavir (LPV/r) in a population-based cohort of HIV-1-infected children. METHODS: All children enrolled in the Swiss Mother and Child HIV Cohort Study, treated with LPV/r-based combination antiretroviral treatment (cART) between November 2000 and October 2008, were included. RESULTS: 88 children (25 (28%) protease inhibitor (PI)-naive, 16 (18%) ART-naive) were analysed (251 patient-years on LPV/r). After 48 weeks on LPV/r, 70 children had a median (interquartile range (IQR)) decrease in HIV-1 viral load of 4.25 log (5.45-3.17; PI-naive, n=17) and 2.53 (3.68-1.38; PI-experienced, n=53). Median (IQR) increase in CD4 count was 429 (203-593; PI-naive) and 177 (21-331; PI-experienced) cells/microl. These effects remained stable throughout 192 weeks for 25 children. Treatment was stopped for viral rebound in seven and suspected toxicity in 12 children. CONCLUSION: Long-term treatment with LPV/r-based cART is safe and effective in HIV-1-infected children.

SGP-1: prediction and validation of homologous genes based on sequence alignments

Conventional methods of gene prediction rely on the recognition of DNA-sequence signals, the coding potential or the comparison of a genomic sequence with a cDNA, EST, or protein database. Reasons for limited accuracy in many circumstances are species-specific training and the incompleteness of reference databases. Lately, comparative genome analysis has attracted increasing attention. Several analysis tools that are based on human/mouse comparisons are already available. Here, we present a program for the prediction of protein-coding genes, termed SGP-1 (Syntenic Gene Prediction), which is based on the similarity of homologous genomic sequences. In contrast to most existing tools, the accuracy of SGP-1 depends little on species-specific properties such as codon usage or the nucleotide distribution. SGP-1 may therefore be applied to nonstandard model organisms in vertebrates as well as in plants, without the need for extensive parameter training. In addition to predicting genes in large-scale genomic sequences, the program may be useful to validate gene structure annotations from databases. To this end, SGP-1 output also contains comparisons between predicted and annotated gene structures in HTML format. The program can be accessed via a Web server at http://soft.ice.mpg.de/sgp-1. The source code, written in ANSI C, is available on request from the authors.

An assessment of gene prediction accuracy in large DNA sequences

One of the first useful products from the human genome will be a set of predicted genes. Besides its intrinsic scientific interest, the accuracy and completeness of this data set is of considerable importance for human health and medicine. Though progress has been made on computational gene identification in terms of both methods and accuracy evaluation measures, most of the sequence sets in which the programs are tested are short genomic sequences, and there is concern that these accuracy measures may not extrapolate well to larger, more challenging data sets. Given the absence of experimentally verified large genomic data sets, we constructed a semiartificial test set comprising a number of short single-gene genomic sequences with randomly generated intergenic regions. This test set, which should still present an easier problem than real human genomic sequence, mimics the approximately 200kb long BACs being sequenced. In our experiments with these longer genomic sequences, the accuracy of GENSCAN, one of the most accurate ab initio gene prediction programs, dropped significantly, although its sensitivity remained high. Conversely, the accuracy of similarity-based programs, such as GENEWISE, PROCRUSTES, and BLASTX was not affected significantly by the presence of random intergenic sequence, but depended on the strength of the similarity to the protein homolog. As expected, the accuracy dropped if the models were built using more distant homologs, and we were able to quantitatively estimate this decline. However, the specificities of these techniques are still rather good even when the similarity is weak, which is a desirable characteristic for driving expensive follow-up experiments. Our experiments suggest that though gene prediction will improve with every new protein that is discovered and through improvements in the current set of tools, we still have a long way to go before we can decipher the precise exonic structure of every gene in the human genome using purely computational methodology.

Comparative gene prediction in human and mouse

The completion of the sequencing of the mouse genome promises to help predict human genes with greater accuracy. While current ab initio gene prediction programs are remarkably sensitive (i.e., they predict at least a fragment of most genes), their specificity is often low, predicting a large number of false-positive genes in the human genome. Sequence conservation at the protein level with the mouse genome can help eliminate some of those false positives. Here we describe SGP2, a gene prediction program that combines ab initio gene prediction with TBLASTX searches between two genome sequences to provide both sensitive and specific gene predictions. The accuracy of SGP2 when used to predict genes by comparing the human and mouse genomes is assessed on a number of data sets, including single-gene data sets, the highly curated human chromosome 22 predictions, and entire genome predictions from ENSEMBL. Results indicate that SGP2 outperforms purely ab initio gene prediction methods. Results also indicate that SGP2 works about as well with 3x shotgun data as it does with fully assembled genomes. SGP2 provides a high enough specificity that its predictions can be experimentally verified at a reasonable cost. SGP2 was used to generate a complete set of gene predictions on both the human and mouse by comparing the genomes of these two species. Our results suggest that another few thousand human and mouse genes currently not in ENSEMBL are worth verifying experimentally.

Impairment of mossy fiber long-term potentiation and associative learning in pituitary adenylate cyclase activating polypeptide type I receptor-deficient Mice

The pituitary adenylate cyclase activating polypeptide (PACAP) type I receptor (PAC1) is a G-protein-coupled receptor binding the strongly conserved neuropeptide PACAP with 1000-fold higher affinity than the related peptide vasoactive intestinal peptide. PAC1-mediated signaling has been implicated in neuronal differentiation and synaptic plasticity. To gain further insight into the biological significance of PAC1-mediated signaling in vivo, we generated two different mutant mouse strains, harboring either a complete or a forebrain-specific inactivation of PAC1. Mutants from both strains show a deficit in contextual fear conditioning, a hippocampus-dependent associative learning paradigm. In sharp contrast, amygdala-dependent cued fear conditioning remains intact. Interestingly, no deficits in other hippocampus-dependent tasks modeling declarative learning such as the Morris water maze or the social transmission of food preference are observed. At the cellular level, the deficit in hippocampus-dependent associative learning is accompanied by an impairment of mossy fiber long-term potentiation (LTP). Because the hippocampal expression of PAC1 is restricted to mossy fiber terminals, we conclude that presynaptic PAC1-mediated signaling at the mossy fiber synapse is involved in both LTP and hippocampus-dependent associative learning.

Effects of long-term averaging of quantitative blood pressure traits on the detection of genetic associations.

Blood pressure (BP) is a heritable, quantitative trait with intraindividual variability and susceptibility to measurement error. Genetic studies of BP generally use single-visit measurements and thus cannot remove variability occurring over months or years. We leveraged the idea that averaging BP measured across time would improve phenotypic accuracy and thereby increase statistical power to detect genetic associations. We studied systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP) averaged over multiple years in 46,629 individuals of European ancestry. We identified 39 trait-variant associations across 19 independent loci (p < 5 × 10(-8)); five associations (in four loci) uniquely identified by our LTA analyses included those of SBP and MAP at 2p23 (rs1275988, near KCNK3), DBP at 2q11.2 (rs7599598, in FER1L5), and PP at 6p21 (rs10948071, near CRIP3) and 7p13 (rs2949837, near IGFBP3). Replication analyses conducted in cohorts with single-visit BP data showed positive replication of associations and a nominal association (p < 0.05). We estimated a 20% gain in statistical power with long-term average (LTA) as compared to single-visit BP association studies. Using LTA analysis, we identified genetic loci influencing BP. LTA might be one way of increasing the power of genetic associations for continuous traits in extant samples for other phenotypes that are measured serially over time.

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.

Long-term outcome of preterm infants treated with nasal continuous positive airway pressure

RESUME La ventilation en pression positive continue (Continuous Positive Airway Pressure, CPAP), utilisée pour la première fois chez. les prématurés en 1971, est une technique actuellement très largement utilisée dans les unités néonatales. L'utilisation de la CPAP présente de nombreux avantages à court terme: diminution de la fraction maximale inspirée d'oxygène, de la durée de l'oxygénothérapie, du taux d'intubation et donc du recours à une ventilation mécanique, réduction de l'utilisation des amines, des curares et de la morphine, possible prévention de l'apparition d'une bronchodysplasie pulmonaire, et possibles réductions du nombre d'infections postnatales et des entérocolites nécrosantes. Mais peu d'études existent concernant les effets à long terme de la CPAP sur le neurodéveloppement et la croissance, qui constituent l'objectif de la présente étude. L'utilisation systématique de la CPAP comme alternative à la ventilation mécanique a été introduite à Lausanne en 1998. La population cible de cette étude est constituée des prématurés nés à moins de 32 semaines de gestation ou pesant moins de 1500 g à la naissance; ils ont été systématiquement suivis jusqu'en âge préscolaire dans le cadre de l'étude de cohorte «Unité de Développement, CHUV». L'originalité de ce travail réside dans le fait d'évaluer le neurodéveloppement et la croissance à long terme d'enfants prématurés traités préférentiellement avec la CPAP, en comparaison avec un groupe historique contrôle traité par d'autres modes ventilatoires, en tenant compte de nombreux autres paramètres néonataux. Du point de vue du neurodéveloppement, l'usage, de la CPAP montre une tendance à diminuer l'incidence d'hémorragie intraventriculaire et le risque d'avoir un mauvais neurodéveloppement à 6 mois. Ces résultats positifs sur le neurodéveloppement s'estompent à l'âge de 18 mois, où persiste néanmoins une valeur plus élevée du quotient de développement, et disparaissent complètement en âge préscolaire. Du point de vue de la croissance, l'utilisation de la CPAP ne montre aucun effet sur le poids, mais par contre un effet positif sur la taille à 6 et 18 mois et sur le périmètre crânien à 6 mois, 18 mois et en âge préscolaire. Malgré le caractère non randomisé de cette étude, les résultats positifs obtenus ici permettent sans conteste de s'assurer d'une utilisation de la CPAP sans effet négatif sur le neurodéveloppement et la croissance, et fournissent donc un argument supplémentaire pour l'utilisation systématique de la CPAP chez les prématurés.

Prediction of enzyme function by combining sequence similarity and protein interactions

Background: A number of studies have used protein interaction data alone for protein function prediction. Here, we introduce a computational approach for annotation of enzymes, based on the observation that similar protein sequences are more likely to perform the same function if they share similar interacting partners. Results: The method has been tested against the PSI-BLAST program using a set of 3,890 protein sequences from which interaction data was available. For protein sequences that align with at least 40% sequence identity to a known enzyme, the specificity of our method in predicting the first three EC digits increased from 80% to 90% at 80% coverage when compared to PSI-BLAST. Conclusion: Our method can also be used in proteins for which homologous sequences with known interacting partners can be detected. Thus, our method could increase 10% the specificity of genome-wide enzyme predictions based on sequence matching by PSI-BLAST alone.

Predictability of music descriptor time series and its application to cover song detection

Intuitively, music has both predictable and unpredictable components. In this work we assess this qualitative statement in a quantitative way using common time series models fitted to state-of-the-art music descriptors. These descriptors cover different musical facets and are extracted from a large collection of real audio recordings comprising a variety of musical genres. Our findings show that music descriptor time series exhibit a certain predictability not only for short time intervals, but also for mid-term and relatively long intervals. This fact is observed independently of the descriptor, musical facet and time series model we consider. Moreover, we show that our findings are not only of theoretical relevance but can also have practical impact. To this end we demonstrate that music predictability at relatively long time intervals can be exploited in a real-world application, namely the automatic identification of cover songs (i.e. different renditions or versions of the same musical piece). Importantly, this prediction strategy yields a parameter-free approach for cover song identification that is substantially faster, allows for reduced computational storage and still maintains highly competitive accuracies when compared to state-of-the-art systems.

Incidence and risk factors for Contegra graft infection following right ventricular outflow tract reconstruction: long-term results.

OBJECTIVES: The aim of this study was to evaluate the risk factors associated with Contegra graft (Medtronic Minneapolis, MN, USA) infection after reconstruction of the right ventricular outflow tract. METHODS: One hundred and six Contegra grafts were implanted between April 1999 and April 2010 for the Ross procedure (n = 46), isolated pulmonary valve replacement (n = 32), tetralogy of Fallot (n = 24), double-outlet right ventricle (n = 7), troncus arteriosus (n = 4), switch operation (n = 1) and redo of pulmonary valve replacement (n = 2). The median age of the patients was 13 years (range 0-54 years). A follow-up was completed in all cases with a median duration of 7.6 years (range 1.7-12.7 years). RESULTS: There were 3 cases of in-hospital mortality. The survival rate during 7 years was 95.7%. Despite the lifelong endocarditis prophylaxis, Contegra graft infection was diagnosed in 12 (11.3%) patients at a median time of 4.4 years (ranging from 0.4 to 8.7 years). Univariate analysis of preoperative, perioperative and postoperative variables was performed and the following risk factors for time to infection were identified: female gender with a hazard ratio (HR) of 0.19 (P = 0.042), systemic-to-pulmonary shunt (HR 6.46, P < 0.01), hypothermia (HR 0.79, P = 0.014), postoperative renal insufficiency (HR 11.97, P = 0.015) and implantation of permanent pacemaker during hospitalization (HR 5.29, P = 0.075). In 2 cases, conservative therapy was successful and, in 10 patients, replacement of the infected valve was performed. The Contegra graft was replaced by a homograft in 2 cases and by a new Contegra graft in 8 cases. Cox's proportional hazard model indicated that time to graft infection was significantly associated with tetralogy of Fallot (HR 0.06, P = 0.01), systemic-to-pulmonary shunt (HR 64.71, P < 0.01) and hypothermia (HR 0.77, P < 0.01). CONCLUSION: Contegra graft infection affected 11.3% of cases in our cohort, and thus may be considered as a frequent entity that can be predicted by both intraoperative and early postoperative factors. After the diagnosis of infection associated with the Contegra graft was confirmed, surgical treatment was the therapy of choice.

How to assess prognosis after cardiac arrest and therapeutic hypothermia.

The prognosis of patients who are admitted in a comatose state following successful resuscitation after cardiac arrest remains uncertain. Although the introduction of therapeutic hypothermia (TH) and improvements in post-resuscitation care have significantly increased the number of patients who are discharged home with minimal brain damage, short-term assessment of neurological outcome remains a challenge. The need for early and accurate prognostic predictors is crucial, especially since sedation and TH may alter the neurological examination and delay the recovery of motor response for several days. The development of additional tools, including electrophysiological examinations (electroencephalography and somatosensory evoked potentials), neuroimaging and chemical biomarkers, may help to evaluate the extent of brain injury in these patients. Given the extensive literature existing on this topic and the confounding effects of TH on the strength of these tools in outcome prognostication after cardiac arrest, the aim of this narrative review is to provide a practical approach to post-anoxic brain injury when TH is used. We also discuss when and how these tools could be combined with the neurological examination in a multimodal approach to improve outcome prediction in this population.

Long-term Plan for Concrete Pavement Research and Technology: The CP Road Map, November 2004, Volume 1 of 2

An Iowa State University–led team facilitated development of the CP Road Map. They developed a database of existing research. They gathered input, face to face, from the highway community. They identified gaps in research that became the basis for problem statements, which they organized into a cohesive, strategic research plan.