Impact of inadequate empirical therapy on the mortality of patients with bloodstream infections: a propensity score-based analysis.

The impact of the adequacy of empirical therapy on outcome for patients with bloodstream infections (BSI) is key for determining whether adequate empirical coverage should be prioritized over other, more conservative approaches. Recent systematic reviews outlined the need for new studies in the field, using improved methodologies. We assessed the impact of inadequate empirical treatment on the mortality of patients with BSI in the present-day context, incorporating recent methodological recommendations. A prospective multicenter cohort including all BSI episodes in adult patients was performed in 15 hospitals in Andalucía, Spain, over a 2-month period in 2006 to 2007. The main outcome variables were 14- and 30-day mortality. Adjusted analyses were performed by multivariate analysis and propensity score-based matching. Eight hundred one episodes were included. Inadequate empirical therapy was administered in 199 (24.8%) episodes; mortality at days 14 and 30 was 18.55% and 22.6%, respectively. After controlling for age, Charlson index, Pitt score, neutropenia, source, etiology, and presentation with severe sepsis or shock, inadequate empirical treatment was associated with increased mortality at days 14 and 30 (odds ratios [ORs], 2.12 and 1.56; 95% confidence intervals [95% CI], 1.34 to 3.34 and 1.01 to 2.40, respectively). The adjusted ORs after a propensity score-based matched analysis were 3.03 and 1.70 (95% CI, 1.60 to 5.74 and 0.98 to 2.98, respectively). In conclusion, inadequate empirical therapy is independently associated with increased mortality in patients with BSI. Programs to improve the quality of empirical therapy in patients with suspicion of BSI and optimization of definitive therapy should be implemented.

An alternative method for dating unknown tephras based on a segmented regression model

In CoDaWork’05, we presented an application of discriminant function analysis (DFA) to 4 differentcompositional datasets and modelled the first canonical variable using a segmented regression modelsolely based on an observation about the scatter plots. In this paper, multiple linear regressions areapplied to different datasets to confirm the validity of our proposed model. In addition to dating theunknown tephras by calibration as discussed previously, another method of mapping the unknown tephrasinto samples of the reference set or missing samples in between consecutive reference samples isproposed. The application of these methodologies is demonstrated with both simulated and real datasets.This new proposed methodology provides an alternative, more acceptable approach for geologists as theirfocus is on mapping the unknown tephra with relevant eruptive events rather than estimating the age ofunknown tephra.Kew words: Tephrochronology; Segmented regression

A Negotiation Style Recommender Based on Computational Ecology in Open Negotiation Environments

The system described herein represents the first example of a recommender system in digital ecosystems where agents negotiate services on behalf of small companies. The small companies compete not only with price or quality, but with a wider service-by-service composition by subcontracting with other companies. The final result of these offerings depends on negotiations at the scale of millions of small companies. This scale requires new platforms for supporting digital business ecosystems, as well as related services like open-id, trust management, monitors and recommenders. This is done in the Open Negotiation Environment (ONE), which is an open-source platform that allows agents, on behalf of small companies, to negotiate and use the ecosystem services, and enables the development of new agent technologies. The methods and tools of cyber engineering are necessary to build up Open Negotiation Environments that are stable, a basic condition for predictable business and reliable business environments. Aiming to build stable digital business ecosystems by means of improved collective intelligence, we introduce a model of negotiation style dynamics from the point of view of computational ecology. This model inspires an ecosystem monitor as well as a novel negotiation style recommender. The ecosystem monitor provides hints to the negotiation style recommender to achieve greater stability of an open negotiation environment in a digital business ecosystem. The greater stability provides the small companies with higher predictability, and therefore better business results. The negotiation style recommender is implemented with a simulated annealing algorithm at a constant temperature, and its impact is shown by applying it to a real case of an open negotiation environment populated by Italian companies

Clinical and epidemiological features and prognosis of complicated pyelonephritis: a prospective observational single hospital-based study.

BACKGROUND Complicated pyelonephritis (cPN), a common cause of hospital admission, is still a poorly-understood entity given the difficulty involved in its correct definition. The aim of this study was to analyze the main epidemiological, clinical, and microbiological characteristics of cPN and its prognosis in a large cohort of patients with cPN. METHODS We conducted a prospective, observational study including 1325 consecutive patients older than 14 years diagnosed with cPN and admitted to a tertiary university hospital between 1997-2013. After analyzing the main demographic, clinical and microbiological data, covariates found to be associated with attributable mortality in univariate analysis were included in a multivariate logistic regression model. RESULTS Of the 1325 patients, 689 (52%) were men and 636 (48%) women; median age 63 years, interquartile range [IQR] (46.5-73). Nine hundred and forty patients (70.9%) had functional or structural abnormalities in the urinary tract, 215 (16.2%) were immunocompromised, 152 (11.5%) had undergone a previous urinary tract instrumentation, and 196 (14.8%) had a long-term bladder catheter, nephrostomy tube or ureteral catheter. Urine culture was positive in 813 (67.7%) of the 1251 patients in whom it was done, and in the 1032 patients who had a blood culture, 366 (34%) had bacteraemia. Escherichia coli was the causative agent in 615 episodes (67%), Klebsiella spp in 73 (7.9%) and Proteus ssp in 61 (6.6%). Fourteen point one percent of GNB isolates were ESBL producers. In total, 343 patients (25.9%) developed severe sepsis and 165 (12.5%) septic shock. Crude mortality was 6.5% and attributable mortality was 4.1%. Multivariate analysis showed that an age >75 years (OR 2.77; 95% CI, 1.35-5.68), immunosuppression (OR 3.14; 95% CI, 1.47-6.70), and septic shock (OR 58.49; 95% CI, 26.6-128.5) were independently associated with attributable mortality. CONCLUSIONS cPN generates a high morbidity and mortality and likely a great consumption of healthcare resources. This study highlights the factors directly associated with mortality, though further studies are needed in the near future aimed at identifying subgroups of low-risk patients susceptible to outpatient management.

iNKT/CD1d-antitumor immunotherapy significantly increases the efficacy of therapeutic CpG/peptide-based cancer vaccine.

BACKGROUND: Therapeutic cancer vaccines aim to boost the natural immunity against transformed cancer cells, and a series of adjuvants and co-stimulatory molecules have been proposed to enhance the immune response against weak self-antigens expressed on cancer cells. For instance, a peptide/CpG-based cancer vaccine has been evaluated in several clinical trials and was shown in pre-clinical studies to favor the expansion of effector T versus Tregs cells, resulting in a potent antitumor activity, as compared to other TLR ligands. Alternatively, the adjuvant activity of CD1d-restricted invariant NKT cells (iNKT) on the innate and adaptive immunity is well demonstrated, and several CD1d glycolipid ligands are under pre-clinical and clinical evaluation. Importantly, additive or even synergistic effects have been shown upon combined CD1d/NKT agonists and TLR ligands. The aim of the present study is to combine the activation and tumor targeting of activated iNKT, NK and T cells. METHODS: Activation and tumor targeting of iNKT cells via recombinant α-galactosylceramide (αGC)-loaded CD1d-anti-HER2 fusion protein (CD1d-antitumor) is combined or not with OVA peptide/CpG vaccine. Circulating and intratumoral NK and H-2Kb/OVA-specific CD8 responses are monitored, as well as the state of activation of dendritic cells (DC) with regard to activation markers and IL-12 secretion. The resulting antitumor therapy is tested against established tumor grafts of B16 melanoma cells expressing human HER2 and ovalbumin. RESULTS: The combined CD1d/iNKT antitumor therapy and CpG/peptide-based immunization leads to optimized expansion of NK and OVA-specific CD8 T cells (CTLs), likely resulting from the maturation of highly pro-inflammatory DCs as seen by a synergistic increase in serum IL-12. The enhanced innate and adaptive immune responses result in higher tumor inhibition that correlates with increased numbers of OVA-specific CTLs at the tumor site. Antibody-mediated depletion experiments further demonstrate that in this context, CTLs rather than NK cells are essential for the enhanced tumor inhibition. CONCLUSIONS: Altogether, our study in mice demonstrates that αGC/CD1d-antitumor fusion protein greatly increases the efficacy of a therapeutic CpG-based cancer vaccine, first as an adjuvant during T cell priming and second, as a therapeutic agent to redirect immune responses to the tumor site.

Discovering the campus together: a mobile and computer-based learning experience

One of the most relevant difficulties faced by first-year undergraduate students is to settle into the educational environment of universities. This paper presents a case study that proposes a computer-assisted collaborative experience designed to help students in their transition from high school to university. This is done by facilitating their first contact with the campus and its services, the university community, methodologies and activities. The experience combines individual and collaborative activities, conducted in and out of the classroom, structured following the Jigsaw Collaborative Learning Flow Pattern. A specific environment including portable technologies with network and computer applications has been developed to support and facilitate the orchestration of a flow of learning activities into a single integrated learning setting. The result is a Computer-Supported Collaborative Blended Learning scenario, which has been evaluated with first-year university students of the degrees of Software and Audiovisual Engineering within the subject Introduction to Information and Communications Technologies. The findings reveal that the scenario improves significantly students’ interest in their studies and their understanding about the campus and services provided. The environment is also an innovative approach to successfully support the heterogeneous activities conducted by both teachers and students during the scenario. This paper introduces the goals and context of the case study, describes how the technology was employed to conduct the learning scenario, the evaluation methods and the main results of the experience.

Development, optimization, and validation of novel anti-TEM1/CD248 affinity agent for optical imaging in cancer.

Tumor Endothelial Marker-1 (TEM1/CD248) is a tumor vascular marker with high therapeutic and diagnostic potentials. Immuno-imaging with TEM1-specific antibodies can help to detect cancerous lesions, monitor tumor responses, and select patients that are most likely to benefit from TEM1-targeted therapies. In particular, near infrared(NIR) optical imaging with biomarker-specific antibodies can provide real-time, tomographic information without exposing the subjects to radioactivity. To maximize the theranostic potential of TEM1, we developed a panel of all human, multivalent Fc-fusion proteins based on a previously identified single chain antibody (scFv78) that recognizes both human and mouse TEM1. By characterizing avidity, stability, and pharmacokinectics, we identified one fusion protein, 78Fc, with desirable characteristics for immuno-imaging applications. The biodistribution of radiolabeled 78Fc showed that this antibody had minimal binding to normal organs, which have low expression of TEM1. Next, we developed a 78Fc-based tracer and tested its performance in different TEM1-expressing mouse models. The NIR imaging and tomography results suggest that the 78Fc-NIR tracer performs well in distinguishing mouse- or human-TEM1 expressing tumor grafts from normal organs and control grafts in vivo. From these results we conclude that further development and optimization of 78Fc as a TEM1-targeted imaging agent for use in clinical settings is warranted.

Spacial debris collector robot : An AI-based and autonomous debris collector satellite simulation

In this paper the core functions of an artificial intelligence (AI) for controlling a debris collector robot are designed and implemented. Using the robot operating system (ROS) as the base of this work a multi-agent system is built with abilities for task planning.

Parachlamydia acanthamoebae, an emerging agent of pneumonia.

Parachlamydia acanthamoebae is a Chlamydia-like organism that easily grows within Acanthamoeba spp. Thus, it probably uses these widespread free-living amoebae as a replicative niche, a cosmopolite aquatic reservoir and a vector. A potential role of P. acanthamoebae as an agent of lower respiratory tract infection was initially suggested by its isolation within an Acanthamoeba sp. recovered from the water of a humidifier during the investigation of an outbreak of fever. Additional serological and molecular-based investigations further supported its pathogenic role, mainly in bronchiolitis, bronchitis, aspiration pneumonia and community-acquired pneumonia. P. acanthamoebae was shown to survive and replicate within human macrophages, lung fibroblasts and pneumocytes. Moreover, this strict intracellular bacterium also causes severe pneumonia in experimentally infected mice, thus fulfilling the third and fourth Koch criteria for a pathogenic role. Consequently, new tools have been developed for the diagnosis of parachlamydial infections. It will be important to routinely search for this emerging agent of pneumonia, as P. acanthamoebae is apparently resistant to quinolones, which are antibiotics often used for the empirical treatment of atypical pneumonia. Other Chlamydia-related bacteria, including Protochlamydia naegleriophila, Simkania negevensis and Waddlia chondrophila, might also cause lung infections. Moreover, several additional novel chlamydiae, e.g. Criblamydia sequanensis and Rhabdochlamydia crassificans, have been discovered and are now being investigated for their human pathogenicity.

Phase-based manganese enhanced MRI, a new methodology to enhance brain cytoarchitectural contrast and study manganese uptake.

PURPOSE: As the magnetic susceptibility induced frequency shift increases linearly with magnetic field strength, the present work evaluates manganese as a phase imaging contrast agent and investigates the dose dependence of brain enhancement in comparison to T1 -weighted imaging after intravenous administration of MnCl2 . METHODS: Experiments were carried out on 12 Sprague-Dawley rats. MnCl2 was infused intravenously with the following doses: 25, 75, 125 mg/kg (n=4). Phase, T1 -weighted images and T1 maps were acquired before and 24h post MnCl2 administration at 14.1 Tesla. RESULTS: Manganese enhancement was manifested in phase imaging by an increase in frequency shift differences between regions rich in calcium gated channels and other tissues, together with local increase in signal to noise ratio (from the T1 reduction). Such contrast improvement allowed a better visualization of brain cytoarchitecture. The measured T1 decrease observed across different manganese doses and in different brain regions were consistent with the increase in the contrast to noise ratio (CNR) measured by both T1 -weighted and phase imaging, with the strongest variations being observed in the dentate gyrus and olfactory bulb. CONCLUSION: Overall from its high sensitivity to manganese combined with excellent CNR, phase imaging is a promising alternative imaging protocol to assess manganese enhanced MRI at ultra high field. Magn Reson Med 72:1246-1256, 2014. © 2013 Wiley Periodicals, Inc.

Solving heterogeneous-agent models by projection and perturbation

The paper proposes a numerical solution method for general equilibrium models with a continuum of heterogeneous agents, which combines elements of projection and of perturbation methods. The basic idea is to solve first for the stationary solutionof the model, without aggregate shocks but with fully specified idiosyncratic shocks. Afterwards one computes a first-order perturbation of the solution in the aggregate shocks. This approach allows to include a high-dimensional representation of the cross-sectional distribution in the state vector. The method is applied to a model of household saving with uninsurable income risk and liquidity constraints. The model includes not only productivity shocks, but also shocks to redistributive taxation, which cause substantial short-run variation in the cross-sectional distribution of wealth. If those shocks are operative, it is shown that a solution method based on very few statistics of the distribution is not suitable, while the proposed method can solve the model with high accuracy, at least for the case of small aggregate shocks. Techniques are discussed to reduce the dimension of the state space such that higher order perturbations are feasible.Matlab programs to solve the model can be downloaded.

Global Genomic Diversity of Human Papillomavirus 6 Based on 724 Isolates and 190 Complete Genome Sequences.

Human papillomavirus type 6 (HPV6) is the major etiological agent of anogenital warts and laryngeal papillomas and has been included in both the quadrivalent and nonavalent prophylactic HPV vaccines. This study investigated the global genomic diversity of HPV6, using 724 isolates and 190 complete genomes from six continents, and the association of HPV6 genomic variants with geographical location, anatomical site of infection/disease, and gender. Initially, a 2,800-bp E5a-E5b-L1-LCR fragment was sequenced from 492/530 (92.8%) HPV6-positive samples collected for this study. Among them, 130 exhibited at least one single nucleotide polymorphism (SNP), indel, or amino acid change in the E5a-E5b-L1-LCR fragment and were sequenced in full. A global alignment and maximum likelihood tree of 190 complete HPV6 genomes (130 fully sequenced in this study and 60 obtained from sequence repositories) revealed two variant lineages, A and B, and five B sublineages: B1, B2, B3, B4, and B5. HPV6 (sub)lineage-specific SNPs and a 960-bp representative region for whole-genome-based phylogenetic clustering within the L2 open reading frame were identified. Multivariate logistic regression analysis revealed that lineage B predominated globally. Sublineage B3 was more common in Africa and North and South America, and lineage A was more common in Asia. Sublineages B1 and B3 were associated with anogenital infections, indicating a potential lesion-specific predilection of some HPV6 sublineages. Females had higher odds for infection with sublineage B3 than males. In conclusion, a global HPV6 phylogenetic analysis revealed the existence of two variant lineages and five sublineages, showing some degree of ethnogeographic, gender, and/or disease predilection in their distribution. IMPORTANCE: This study established the largest database of globally circulating HPV6 genomic variants and contributed a total of 130 new, complete HPV6 genome sequences to available sequence repositories. Two HPV6 variant lineages and five sublineages were identified and showed some degree of association with geographical location, anatomical site of infection/disease, and/or gender. We additionally identified several HPV6 lineage- and sublineage-specific SNPs to facilitate the identification of HPV6 variants and determined a representative region within the L2 gene that is suitable for HPV6 whole-genome-based phylogenetic analysis. This study complements and significantly expands the current knowledge of HPV6 genetic diversity and forms a comprehensive basis for future epidemiological, evolutionary, functional, pathogenicity, vaccination, and molecular assay development studies.

Sex differences in urinary levels of several biological indicators of exposure: a simulation study using a compartmental based toxicokinetic model

Toxicokinetic modeling is a useful tool to describe or predict the behavior of a chemical agent in the human or animal organism. A general model based on four compartments was developed in a previous study in order to quantify the effect of human variability on a wide range of biological exposure indicators. The aim of this study was to adapt this existing general toxicokinetic model to three organic solvents, which were methyl ethyl ketone, 1-methoxy-2-propanol and 1,1,1,-trichloroethane, and to take into account sex differences. We assessed in a previous human volunteer study the impact of sex on different biomarkers of exposure corresponding to the three organic solvents mentioned above. Results from that study suggested that not only physiological differences between men and women but also differences due to sex hormones levels could influence the toxicokinetics of the solvents. In fact the use of hormonal contraceptive had an effect on the urinary levels of several biomarkers, suggesting that exogenous sex hormones could influence CYP2E1 enzyme activity. These experimental data were used to calibrate the toxicokinetic models developed in this study. Our results showed that it was possible to use an existing general toxicokinetic model for other compounds. In fact, most of the simulation results showed good agreement with the experimental data obtained for the studied solvents, with a percentage of model predictions that lies within the 95% confidence interval varying from 44.4 to 90%. Results pointed out that for same exposure conditions, men and women can show important differences in urinary levels of biological indicators of exposure. Moreover, when running the models by simulating industrial working conditions, these differences could even be more pronounced. In conclusion, a general and simple toxicokinetic model, adapted for three well known organic solvents, allowed us to show that metabolic parameters can have an important impact on the urinary levels of the corresponding biomarkers. These observations give evidence of an interindividual variablity, an aspect that should have its place in the approaches for setting limits of occupational exposure.

Integrated methodologies to study human transcriptional regulation from functional genomics data

Abstract : The human body is composed of a huge number of cells acting together in a concerted manner. The current understanding is that proteins perform most of the necessary activities in keeping a cell alive. The DNA, on the other hand, stores the information on how to produce the different proteins in the genome. Regulating gene transcription is the first important step that can thus affect the life of a cell, modify its functions and its responses to the environment. Regulation is a complex operation that involves specialized proteins, the transcription factors. Transcription factors (TFs) can bind to DNA and activate the processes leading to the expression of genes into new proteins. Errors in this process may lead to diseases. In particular, some transcription factors have been associated with a lethal pathological state, commonly known as cancer, associated with uncontrolled cellular proliferation, invasiveness of healthy tissues and abnormal responses to stimuli. Understanding cancer-related regulatory programs is a difficult task, often involving several TFs interacting together and influencing each other's activity. This Thesis presents new computational methodologies to study gene regulation. In addition we present applications of our methods to the understanding of cancer-related regulatory programs. The understanding of transcriptional regulation is a major challenge. We address this difficult question combining computational approaches with large collections of heterogeneous experimental data. In detail, we design signal processing tools to recover transcription factors binding sites on the DNA from genome-wide surveys like chromatin immunoprecipitation assays on tiling arrays (ChIP-chip). We then use the localization about the binding of TFs to explain expression levels of regulated genes. In this way we identify a regulatory synergy between two TFs, the oncogene C-MYC and SP1. C-MYC and SP1 bind preferentially at promoters and when SP1 binds next to C-NIYC on the DNA, the nearby gene is strongly expressed. The association between the two TFs at promoters is reflected by the binding sites conservation across mammals, by the permissive underlying chromatin states 'it represents an important control mechanism involved in cellular proliferation, thereby involved in cancer. Secondly, we identify the characteristics of TF estrogen receptor alpha (hERa) target genes and we study the influence of hERa in regulating transcription. hERa, upon hormone estrogen signaling, binds to DNA to regulate transcription of its targets in concert with its co-factors. To overcome the scarce experimental data about the binding sites of other TFs that may interact with hERa, we conduct in silico analysis of the sequences underlying the ChIP sites using the collection of position weight matrices (PWMs) of hERa partners, TFs FOXA1 and SP1. We combine ChIP-chip and ChIP-paired-end-diTags (ChIP-pet) data about hERa binding on DNA with the sequence information to explain gene expression levels in a large collection of cancer tissue samples and also on studies about the response of cells to estrogen. We confirm that hERa binding sites are distributed anywhere on the genome. However, we distinguish between binding sites near promoters and binding sites along the transcripts. The first group shows weak binding of hERa and high occurrence of SP1 motifs, in particular near estrogen responsive genes. The second group shows strong binding of hERa and significant correlation between the number of binding sites along a gene and the strength of gene induction in presence of estrogen. Some binding sites of the second group also show presence of FOXA1, but the role of this TF still needs to be investigated. Different mechanisms have been proposed to explain hERa-mediated induction of gene expression. Our work supports the model of hERa activating gene expression from distal binding sites by interacting with promoter bound TFs, like SP1. hERa has been associated with survival rates of breast cancer patients, though explanatory models are still incomplete: this result is important to better understand how hERa can control gene expression. Thirdly, we address the difficult question of regulatory network inference. We tackle this problem analyzing time-series of biological measurements such as quantification of mRNA levels or protein concentrations. Our approach uses the well-established penalized linear regression models where we impose sparseness on the connectivity of the regulatory network. We extend this method enforcing the coherence of the regulatory dependencies: a TF must coherently behave as an activator, or a repressor on all its targets. This requirement is implemented as constraints on the signs of the regressed coefficients in the penalized linear regression model. Our approach is better at reconstructing meaningful biological networks than previous methods based on penalized regression. The method is tested on the DREAM2 challenge of reconstructing a five-genes/TFs regulatory network obtaining the best performance in the "undirected signed excitatory" category. Thus, these bioinformatics methods, which are reliable, interpretable and fast enough to cover large biological dataset, have enabled us to better understand gene regulation in humans.