Upper Airways Microbiota in Antibiotic-Naive Wheezing and Healthy Infants from the Tropics of Rural Ecuador

Background: Observations that the airway microbiome is disturbed in asthma may be confounded by the widespread use of antibiotics and inhaled steroids. We have therefore examined the oropharyngeal microbiome in early onset wheezinginfants from a rural area of tropical Ecuador where antibiotic usage is minimal and glucocorticoid usage is absent. Materials and Methods: We performed pyrosequencing of amplicons of the polymorphic bacterial 16S rRNA gene from oropharyngeal samples from 24 infants with non-infectious early onset wheezing and 24 healthy controls (average age 10.2 months). We analyzed microbial community structure and differences between cases and controls by QIIME software. Results: We obtained 76,627 high quality sequences classified into 182 operational taxonomic units (OTUs). Firmicutes was the most common and diverse phylum (71.22% of sequences) with Streptococcus being the most common genus (49.72%). Known pathogens were found significantly more often in cases of infantile wheeze compared to controls, exemplified by Haemophilus spp. (OR = 2.12, 95% Confidence Interval (CI) 1.82–2.47; P = 5.46610223) and Staphylococcus spp. (OR = 124.1, 95%CI 59.0–261.2; P = 1.876102241). Other OTUs were less common in cases than controls, notably Veillonella spp. (OR = 0.59, 95%CI = 0.56–0.62; P = 8.06610286). Discussion: The airway microbiota appeared to contain many more Streptococci than found in Western Europe and the USA. Comparisons between healthy and wheezing infants revealed a significant difference in several bacterial phylotypes that were not confounded by antibiotics or use of inhaled steroids. The increased prevalence of pathogens such as Haemophilus and Staphylococcus spp. in cases may contribute to wheezing illnesses in this age group

Delayed acquisition of airway commensals in antibiotic naïve children and its relationship with wheezing in rural Ecuador.

INTRODUCTION: The hygiene hypothesis identified a relationship between living in rural areas and acquiring protective environmental factors against the development of asthma and atopy. In our previous study, we found a correlation between particular bacterial species and early-onset wheezing in infants from the rural tropics of Ecuador who were corticosteroid-naïve and had limited antibiotic exposure. We now describe a longitudinal study of infants conducted to determine the age-related changes of the microbiome and its relationship with wheezing. METHODS: We performed an amplicon sequencing of the 16S rRNA bacterial gene from the oropharyngeal samples obtained from 110 infants who had a history of recurrent episodic wheezing sampled at different ages (7, 12, and 24 months) and compared it to the sequencing of the oropharyngeal samples from 150 healthy infants sampled at the same time points. Bioinformatic analyses were conducted using QIIME and R. RESULTS: As expected, the microbiota diversity consistently increased as the infants grew older. Considering age-based microbiota changes, we found that infants with wheeze had significantly lower species richness than the healthy infants at 7 months, but not at 12 or 24 months. Most of the core and accessory organisms increased in abundance and prevalence with age, except for a few which decreased. At 7 months of age, infants with wheeze had notably higher levels of a single Streptococcus operational taxonomic unit and core microbiota member than controls. CONCLUSIONS: In a cohort with limited antibiotic and corticosteroid use, a progressively more complex and diverse respiratory microbial community develops with age. The respiratory microbiota in early life is altered in infants with wheeze, but this does not hold true in older infants

Development and validation of a computational model of the knee joint for the evaluation of surgical treatments for osteoarthritis

A three-dimensional (3D) knee joint computational model was developed and validated to predict knee joint contact forces and pressures for different degrees of malalignment. A 3D computational knee model was created from high-resolution radiological images to emulate passive sagittal rotation (full-extension to 658-flexion) and weight acceptance. A cadaveric knee mounted on a six-degree-of-freedom robot was subjected to matching boundary and loading conditions. A ligamenttuning process minimised kinematic differences between the robotically loaded cadaver specimen and the finite element (FE) model. The model was validated by measured intra-articular force and pressure measurements. Percent full scale error between FE-predicted and in vitro-measured values in the medial and lateral compartments were 6.67% and 5.94%, respectively, for normalised peak pressure values, and 7.56% and 4.48%, respectively, for normalised force values. The knee model can accurately predict normalised intra-articular pressure and forces for different loading conditions and could be further developed for subject-specific surgical planning

Addressing the evolution of automated user behaviour patterns by runtime model interpretation

The final publication is available at Springer via http://dx.doi.org/10.1007/s10270-013-0371-3The use of high-level abstraction models can facilitate and improve not only system development but also runtime system evolution. This is the idea of this work, in which behavioural models created at design time are also used at runtime to evolve system behaviour. These behavioural models describe the routine tasks that users want to be automated by the system. However, users¿ needs may change after system deployment, and the routine tasks automated by the system must evolve to adapt to these changes. To facilitate this evolution, the automation of the specified routine tasks is achieved by directly interpreting the models at runtime. This turns models into the primary means to understand and interact with the system behaviour associated with the routine tasks as well as to execute and modify it. Thus, we provide tools to allow the adaptation of this behaviour by modifying the models at runtime. This means that the system behaviour evolution is performed by using high-level abstractions and avoiding the costs and risks associated with shutting down and restarting the system.This work has been developed with the support of MICINN, under the project EVERYWARE TIN2010-18011, and the support of the Christian Doppler Forschungsgesellschaft and the BMWFJ, Austria.Serral Asensio, E.; Valderas Aranda, PJ.; Pelechano Ferragud, V. (2013). Addressing the evolution of automated user behaviour patterns by runtime model interpretation. Software and Systems Modeling. https://doi.org/10.1007/s10270-013-0371-3SWeiser, M.: The computer of the 21st century. Sci. Am. 265, 66–75 (1991)Serral, E., Valderas, P., Pelechano, V.: Context-adaptive coordination of pervasive services by interpreting models during runtime. Comput. 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Drug-prescribing patterns during pregnancy in the tertiary care hospitals of Pakistan: a cross sectional study

<p>Abstract</p> <p>Background</p> <p>The rationale for use of drugs during pregnancy requires a careful assessment as in addition to the mother, the health and life of her unborn child is also at stake. Information on the use of drugs during pregnancy is not available in Pakistan. The aim of this study was to evaluate the patterns of drug prescriptions to pregnant women in tertiary care hospitals of Pakistan.</p> <p>Methods</p> <p>This was a cross-sectional study conducted at five tertiary care hospitals of Pakistan. Copies of outpatient medicinal prescriptions given to pregnant patients attending the antenatal clinics were collected. The drugs were classified according to the pharmacological class and their teratogenic potential.</p> <p>Results</p> <p>All the pregnant women attending the antenatal clinics received a prescription containing at least one drug. A total of 3769 distinct prescriptions given to different women were collected. Majority of the women who received the prescriptions belonged to third trimester (55.4%) followed by second (33.6%) and first trimester (11.0%). On an average, each prescription contained 1.66 ± 0.14 drugs. The obstetricians at Civil Hospital, Karachi and Chandka Medical College Hospital, Larkana showed a tendency of prescribing lesser number of drugs compared to those in other hospitals. Anti-anemic drugs including iron preparations and vitamin and mineral supplements (79.4%) were the most frequently prescribed drugs followed by analgesics (6.2%) and anti-bacterials (2.2%). 739 women (19.6%) received prescriptions containing drugs other than vitamin or mineral supplements. Only 1275 (21.6%) of all the prescribed drugs (n = 6100) were outside this vitamin/mineral supplement class. Out of these 1275 drugs, 29 (2.3%) drugs were prescribed which are considered to be teratogenic. Misoprostol was the most frequently prescribed (n = 6) among the teratogenic drugs followed by carbimazole (n = 5) and methotrexate (n = 5). Twenty nine pregnant women (0.8% of all the women studied) were prescribed these teratogenic drugs.</p> <p>Conclusion</p> <p>Less than one percent of the pregnant women attending tertiary care hospitals in Pakistan are prescribed teratogenic drugs. The prescribing practices of Pakistani physicians are similar to those in western countries.</p

An Integrated Decision Making Approach for Adaptive Shared Control of Mobility Assistance Robots

© 2016, Springer Science+Business Media Dordrecht. Mobility assistance robots provide support to elderly or patients during walking. The design of a safe and intuitive assistance behavior is one of the major challenges in this context. We present an integrated approach for the context-specific, on-line adaptation of the assistance level of a rollator-type mobility assistance robot by gain-scheduling of low-level robot control parameters. A human-inspired decision-making model, the drift-diffusion Model, is introduced as the key principle to gain-schedule parameters and with this to adapt the provided robot assistance in order to achieve a human-like assistive behavior. The mobility assistance robot is designed to provide (a) cognitive assistance to help the user following a desired path towards a predefined destination as well as (b) sensorial assistance to avoid collisions with obstacles while allowing for an intentional approach of them. Further, the robot observes the user long-term performance and fatigue to adapt the overall level of (c) physical assistance provided. For each type of assistance a decision-making problem is formulated that affects different low-level control parameters. The effectiveness of the proposed approach is demonstrated in technical validation experiments. Moreover, the proposed approach is evaluated in a user study with 35 elderly persons. Obtained results indicate that the proposed gain-scheduling technique incorporating ideas of human decision-making models shows a general high potential for the application in adaptive shared control of mobility assistance robots

The Hubbard model within the equations of motion approach

The Hubbard model has a special role in Condensed Matter Theory as it is considered as the simplest Hamiltonian model one can write in order to describe anomalous physical properties of some class of real materials. Unfortunately, this model is not exactly solved except for some limits and therefore one should resort to analytical methods, like the Equations of Motion Approach, or to numerical techniques in order to attain a description of its relevant features in the whole range of physical parameters (interaction, filling and temperature). In this manuscript, the Composite Operator Method, which exploits the above mentioned analytical technique, is presented and systematically applied in order to get information about the behavior of all relevant properties of the model (local, thermodynamic, single- and two- particle ones) in comparison with many other analytical techniques, the above cited known limits and numerical simulations. Within this approach, the Hubbard model is shown to be also capable to describe some anomalous behaviors of the cuprate superconductors.Comment: 232 pages, more than 300 figures, more than 500 reference

Modeling influenza epidemics and pandemics: insights into the future of swine flu (H1N1)

Here we present a review of the literature of influenza modeling studies, and discuss how these models can provide insights into the future of the currently circulating novel strain of influenza A (H1N1), formerly known as swine flu. We discuss how the feasibility of controlling an epidemic critically depends on the value of the Basic Reproduction Number (R0). The R0 for novel influenza A (H1N1) has recently been estimated to be between 1.4 and 1.6. This value is below values of R0 estimated for the 1918–1919 pandemic strain (mean R0~2: range 1.4 to 2.8) and is comparable to R0 values estimated for seasonal strains of influenza (mean R0 1.3: range 0.9 to 2.1). By reviewing results from previous modeling studies we conclude it is theoretically possible that a pandemic of H1N1 could be contained. However it may not be feasible, even in resource-rich countries, to achieve the necessary levels of vaccination and treatment for control. As a recent modeling study has shown, a global cooperative strategy will be essential in order to control a pandemic. This strategy will require resource-rich countries to share their vaccines and antivirals with resource-constrained and resource-poor countries. We conclude our review by discussing the necessity of developing new biologically complex models. We suggest that these models should simultaneously track the transmission dynamics of multiple strains of influenza in bird, pig and human populations. Such models could be critical for identifying effective new interventions, and informing pandemic preparedness planning. Finally, we show that by modeling cross-species transmission it may be possible to predict the emergence of pandemic strains of influenza