A review of composite product data interoperability and product life-cycle management challenges in the composites industry

A review of composite product data interoperability and product life-cycle management challenges is presented, which addresses “Product Life-cycle Management”, developments in materials. The urgent need for this is illustrated by the life-cycle management issues faced in modern military aircraft, where in-service failure of composite parts is a problem, not just in terms of engineering understanding, but also in terms of the process for managing and maintaining the fleet. A demonstration of the use of ISO 10303-235 for a range of through-life composite product data is reported. The standardization of the digital representation of data can help businesses to automate data processing. With the development of new materials, the requirements for data information models for materials properties are evolving, and standardization drives transparency, improves the efficiency of data analysis, and enhances data accuracy. Current developments in Information Technology, such as big data analytics methodologies, have the potential to be highly transformative

Baseline natural killer and T cell populations correlation with virologic outcome after regimen simplification to atazanavir/ritonavir alone (ACTG 5201)

Objectives: Simplified maintenance therapy with ritonavir-boosted atazanavir (ATV/r) provides an alternative treatment option for HIV-1 infection that spares nucleoside analogs (NRTI) for future use and decreased toxicity. We hypothesized that the level of immune activation (IA) and recovery of lymphocyte populations could influence virologic outcomes after regimen simplification. Methods: Thirty-four participants with virologic suppression ≥48 weeks on antiretroviral therapy (2 NRTI plus protease inhibitor) were switched to ATV/r alone in the context of the ACTG 5201 clinical trial. Flow cytometric analyses were performed on PBMC isolated from 25 patients with available samples, of which 24 had lymphocyte recovery sufficient for this study. Assessments included enumeration of T-cells (CD4/CD8), natural killer (NK) (CD3+CD56 +CD16+) cells and cell-associated markers (HLA-DR, CD's 38/69/94/95/158/279). Results: Eight of the 24 patients had at least one plasma HIV-1 RNA level (VL) <50 copies/mL during the study. NK cell levels below the group median of 7.1% at study entry were associated with development of VL <50 copies/mL following simplification by regression and survival analyses (p = 0.043 and 0.023), with an odds ratio of 10.3 (95% CI: 1.92-55.3). Simplification was associated with transient increases in naïve and CD25+ CD4+ T-cells, and had no impact on IA levels. Conclusions: Lower NK cell levels prior to regimen simplification were predictive of virologic rebound after discontinuation of nucleoside analogs. Regimen simplification did not have a sustained impact on markers of IA or T lymphocyte populations in 48 weeks of clinical monitoring. Trial Registration: ClinicalTrials.gov NCT00084019

A perspective on physical reservoir computing with nanomagnetic devices

Neural networks have revolutionized the area of artificial intelligence and introduced transformative applications to almost every scientific field and industry. However, this success comes at a great price; the energy requirements for training advanced models are unsustainable. One promising way to address this pressing issue is by developing low-energy neuromorphic hardware that directly supports the algorithm's requirements. The intrinsic non-volatility, non-linearity, and memory of spintronic devices make them appealing candidates for neuromorphic devices. Here, we focus on the reservoir computing paradigm, a recurrent network with a simple training algorithm suitable for computation with spintronic devices since they can provide the properties of non-linearity and memory. We review technologies and methods for developing neuromorphic spintronic devices and conclude with critical open issues to address before such devices become widely used

High Annual Risk of Tuberculosis Infection among Nursing Students in South India: A Cohort Study

Background: Nurses in developing countries are frequently exposed to infectious tuberculosis (TB) patients, and have a high prevalence of TB infection. To estimate the incidence of new TB infection, we recruited a cohort of young nursing trainees at the Christian Medical College in Southern India. Annual tuberculin skin testing (TST) was conducted to assess the annual risk of TB infection (ARTI) in this cohort. Methodology/Principal Findings: 436 nursing students completed baseline two-step TST testing in 2007 and 217 were TST-negative and therefore eligible for repeat testing in 2008. 181 subjects completed a detailed questionnaire on exposure to tuberculosis from workplace and social contacts. A physician verified the questionnaire and clinical log book and screened the subjects for symptoms of active TB. The majority of nursing students (96.7%) were females, almost 84% were under 22 years of age, and 80% had BCG scars. Among those students who underwent repeat testing in 2008, 14 had TST conversions using the ATS/CDC/IDSA conversion definition of 10 mm or greater increase over baseline. The ARTI was therefore estimated as 7.8% (95%CI: 4.3-12.8%). This was significantly higher than the national average ARTI of 1.5%. Sputum collection and caring for pulmonary TB patients were both high risk activities that were associated with TST conversions in this young nursing cohort. Conclusions: Our study showed a high ARTI among young nursing trainees, substantially higher than that seen in the general Indian population. Indian healthcare providers and the Indian Revised National TB Control Programme will need to implement internationally recommended TB infection control interventions to protect its health care workforce

A Database of Domain Definitions for Proteins with Complex Interdomain Geometry

Protein structural domains are necessary for understanding evolution and protein folding, and may vary widely from functional and sequence based domains. Although, various structural domain databases exist, defining domains for some proteins is non-trivial, and definitions of their domain boundaries are not available. Here, we present a novel database of manually defined structural domains for a representative set of proteins from the SCOP “multi-domain proteins” class. (http://prodata.swmed.edu/multidom/). We consider our domains as mobile evolutionary units, which may rearrange during protein evolution. Additionally, they may be visualized as structurally compact and possibly independently folding units. We also found that representing domains as evolutionary and folding units do not always lead to a unique domain definition. However, unlike existing databases, we retain and refine these “alternate” domain definitions after careful inspection of structural similarity, functional sites and automated domain definition methods. We provide domain definitions, including actual residue boundaries, for proteins that well known databases like SCOP and CATH do not attempt to split. Our alternate domain definitions are suitable for sequence and structure searches by automated methods. Additionally, the database can be used for training and testing domain delineation algorithms. Since our domains represent structurally compact evolutionary units, the database may be useful for studying domain properties and evolution

Automatic structure classification of small proteins using random forest

<p>Abstract</p> <p><b>Background</b></p> <p>Random forest, an ensemble based supervised machine learning algorithm, is used to predict the SCOP structural classification for a target structure, based on the similarity of its structural descriptors to those of a template structure with an equal number of secondary structure elements (SSEs). An initial assessment of random forest is carried out for domains consisting of three SSEs. The usability of random forest in classifying larger domains is demonstrated by applying it to domains consisting of four, five and six SSEs.</p> <p><b>Result</b>s</p> <p>Random forest, trained on SCOP version 1.69, achieves a predictive accuracy of up to 94% on an independent and non-overlapping test set derived from SCOP version 1.73. For classification to the SCOP <it>Class, Fold, Super-family </it>or <it>Family </it>levels, the predictive quality of the model in terms of Matthew's correlation coefficient (MCC) ranged from 0.61 to 0.83. As the number of constituent SSEs increases the MCC for classification to different structural levels decreases.</p> <p>Conclusions</p> <p>The utility of random forest in classifying domains from the place-holder classes of SCOP to the true <it>Class, Fold, Super-family </it>or <it>Family </it>levels is demonstrated. Issues such as introduction of a new structural level in SCOP and the merger of singleton levels can also be addressed using random forest. A real-world scenario is mimicked by predicting the classification for those protein structures from the PDB, which are yet to be assigned to the SCOP classification hierarchy.</p

The F4/AS01B HIV-1 Vaccine Candidate Is Safe and Immunogenic, But Does Not Show Viral Efficacy in Antiretroviral Therapy-Naive, HIV-1-Infected Adults: A Randomized Controlled Trial

The impact of the investigational human immunodeficiency virus type 1 (HIV-1) F4/AS01(B) vaccine on HIV-1 viral load (VL) was evaluated in antiretroviral therapy (ART)-naive HIV-1 infected adults.This phase IIb, observer-blind study (NCT01218113), included ART-naive HIV-1 infected adults aged 18 to 55 years. Participants were randomized to receive 2 (F4/AS01(B)_2 group, N=64) or 3 (F4/AS01(B)_3 group, N=62) doses of F4/AS01(B) or placebo (control group, N=64) at weeks 0, 4, and 28. Efficacy (HIV-1 VL, CD4(+) T-cell count, ART initiation, and HIV-related clinical events), safety, and immunogenicity (antibody and T-cell responses) were evaluated during 48 weeks.At week 48, based on a mixed model, no statistically significant difference in HIV-1 VL change from baseline was demonstrated between F4/AS01(B)_2 and control group (0.073 log(10)copies/mL [97.5% confidence interval (CI): -0.088; 0.235]), or F4/AS01(B)_3 and control group (-0.096 log(10)copies/mL [97.5% CI: -0.257; 0.065]). No differences between groups were observed in HIV-1 VL change, CD4(+) T-cell count, ART initiation, or HIV-related clinical events at intermediate timepoints. Among F4/AS01(B) recipients, the most frequent solicited symptoms were pain at injection site (252/300 doses), fatigue (137/300 doses), myalgia (105/300 doses), and headache (90/300 doses). Twelve serious adverse events were reported in 6 participants; 1 was considered vaccine-related (F4/AS01(B)_2 group: angioedema). F4/AS01(B) induced polyfunctional F4-specific CD4(+) T-cells, but had no significant impact on F4-specific CD8(+) T-cell and anti-F4 antibody levels.F4/AS01(B) had a clinically acceptable safety profile, induced F4-specific CD4(+) T-cell responses, but did not reduce HIV-1 VL, impact CD4(+) T-cells count, delay ART initiation, or prevent HIV-1 related clinical events

Discontinuation of Pneumocystis jirovecii Pneumonia Prophylaxis with CD4 Count <200 Cells/µL and Virologic Suppression: A Systematic Review

HIV viral load (VL) is currently not part of the criteria for Pneumocystis jirovecii pneumonia (PCP) prophylaxis discontinuation, but suppression of plasma viremia with antiretroviral therapy may allow for discontinuation of PCP prophylaxis even with CD4 count <200 cells/µL.A systematic review was performed to determine the incidence of PCP in HIV-infected individuals with CD4 count <200 cells/µL and fully suppressed VL on antiretroviral therapy but not receiving PCP prophylaxis.Four articles examined individuals who discontinued PCP prophylaxis with CD4 count <200 cells/µL in the context of fully suppressed VL on antiretroviral therapy. The overall incidence of PCP was 0.48 cases per 100 person-years (PY) (95% confidence interval (CI) (0.06-0.89). This was lower than the incidence of PCP in untreated HIV infection (5.30 cases/100 PY, 95% CI 4.1-6.8) and lower than the incidence in persons with CD4 count <200 cells/µL, before the availability of highly active antiretroviral therapy (HAART), who continued prophylaxis (4.85/100 PY, 95% CI 0.92-8.78). In one study in which individuals were stratified according to CD4 count <200 cells/µL, there was a greater risk of PCP with CD4 count ≤100 cells/µL compared to 101-200 cells/µL.Primary PCP prophylaxis may be safely discontinued in HIV-infected individuals with CD4 count between 101-200 cells/µL provided the VL is fully suppressed on antiretroviral therapy. However, there are inadequate data available to make this recommendation when the CD4 count is ≤100 cells/µL. A revision of guidelines on primary PCP prophylaxis to include consideration of the VL is merited

FlexOracle: predicting flexible hinges by identification of stable domains

<p>Abstract</p> <p>Background</p> <p>Protein motions play an essential role in catalysis and protein-ligand interactions, but are difficult to observe directly. A substantial fraction of protein motions involve hinge bending. For these proteins, the accurate identification of flexible hinges connecting rigid domains would provide significant insight into motion. Programs such as GNM and FIRST have made global flexibility predictions available at low computational cost, but are not designed specifically for finding hinge points.</p> <p>Results</p> <p>Here we present the novel FlexOracle hinge prediction approach based on the ideas that energetic interactions are stronger <it>within </it>structural domains than <it>between </it>them, and that fragments generated by cleaving the protein at the hinge site are independently stable. We implement this as a tool within the Database of Macromolecular Motions, MolMovDB.org. For a given structure, we generate pairs of fragments based on scanning all possible cleavage points on the protein chain, compute the energy of the fragments compared with the undivided protein, and predict hinges where this quantity is minimal. We present three specific implementations of this approach. In the first, we consider only pairs of fragments generated by cutting at a <it>single </it>location on the protein chain and then use a standard molecular mechanics force field to calculate the enthalpies of the two fragments. In the second, we generate fragments in the same way but instead compute their free energies using a knowledge based force field. In the third, we generate fragment pairs by cutting at <it>two </it>points on the protein chain and then calculate their free energies.</p> <p>Conclusion</p> <p>Quantitative results demonstrate our method's ability to predict known hinges from the Database of Macromolecular Motions.</p

Cross-Over between Discrete and Continuous Protein Structure Space: Insights into Automatic Classification and Networks of Protein Structures

Structural classifications of proteins assume the existence of the fold, which is an intrinsic equivalence class of protein domains. Here, we test in which conditions such an equivalence class is compatible with objective similarity measures. We base our analysis on the transitive property of the equivalence relationship, requiring that similarity of A with B and B with C implies that A and C are also similar. Divergent gene evolution leads us to expect that the transitive property should approximately hold. However, if protein domains are a combination of recurrent short polypeptide fragments, as proposed by several authors, then similarity of partial fragments may violate the transitive property, favouring the continuous view of the protein structure space. We propose a measure to quantify the violations of the transitive property when a clustering algorithm joins elements into clusters, and we find out that such violations present a well defined and detectable cross-over point, from an approximately transitive regime at high structure similarity to a regime with large transitivity violations and large differences in length at low similarity. We argue that protein structure space is discrete and hierarchic classification is justified up to this cross-over point, whereas at lower similarities the structure space is continuous and it should be represented as a network. We have tested the qualitative behaviour of this measure, varying all the choices involved in the automatic classification procedure, i.e., domain decomposition, alignment algorithm, similarity score, and clustering algorithm, and we have found out that this behaviour is quite robust. The final classification depends on the chosen algorithms. We used the values of the clustering coefficient and the transitivity violations to select the optimal choices among those that we tested. Interestingly, this criterion also favours the agreement between automatic and expert classifications. As a domain set, we have selected a consensus set of 2,890 domains decomposed very similarly in SCOP and CATH. As an alignment algorithm, we used a global version of MAMMOTH developed in our group, which is both rapid and accurate. As a similarity measure, we used the size-normalized contact overlap, and as a clustering algorithm, we used average linkage. The resulting automatic classification at the cross-over point was more consistent than expert ones with respect to the structure similarity measure, with 86% of the clusters corresponding to subsets of either SCOP or CATH superfamilies and fewer than 5% containing domains in distinct folds according to both SCOP and CATH. Almost 15% of SCOP superfamilies and 10% of CATH superfamilies were split, consistent with the notion of fold change in protein evolution. These results were qualitatively robust for all choices that we tested, although we did not try to use alignment algorithms developed by other groups. Folds defined in SCOP and CATH would be completely joined in the regime of large transitivity violations where clustering is more arbitrary. Consistently, the agreement between SCOP and CATH at fold level was lower than their agreement with the automatic classification obtained using as a clustering algorithm, respectively, average linkage (for SCOP) or single linkage (for CATH). The networks representing significant evolutionary and structural relationships between clusters beyond the cross-over point may allow us to perform evolutionary, structural, or functional analyses beyond the limits of classification schemes. These networks and the underlying clusters are available at http://ub.cbm.uam.es/research/ProtNet.ph