Objectives It is still debated if pre-existing minority drug-resistant HIV-1 variants (MVs) affect the virological outcomes of first-line NNRTI-containing ART. Methods This Europe-wide case–control study included ART-naive subjects infected with drug-susceptible HIV-1 as revealed by population sequencing, who achieved virological suppression on first-line ART including one NNRTI. Cases experienced virological failure and controls were subjects from the same cohort whose viraemia remained suppressed at a matched time since initiation of ART. Blinded, centralized 454 pyrosequencing with parallel bioinformatic analysis in two laboratories was used to identify MVs in the 1%–25% frequency range. ORs of virological failure according to MV detection were estimated by logistic regression. Results Two hundred and sixty samples (76 cases and 184 controls), mostly subtype B (73.5%), were used for the analysis. Identical MVs were detected in the two laboratories. 31.6% of cases and 16.8% of controls harboured pre-existing MVs. Detection of at least one MV versus no MVs was associated with an increased risk of virological failure (OR = 2.75, 95% CI = 1.35–5.60, P = 0.005); similar associations were observed for at least one MV versus no NRTI MVs (OR = 2.27, 95% CI = 0.76–6.77, P = 0.140) and at least one MV versus no NNRTI MVs (OR = 2.41, 95% CI = 1.12–5.18, P = 0.024). A dose–effect relationship between virological failure and mutational load was found. Conclusions Pre-existing MVs more than double the risk of virological failure to first-line NNRTI-based ART.

Reliable and strong surface enhanced Raman scattering (SERS) signatures of intracellular compartments in live NIH3T3 fibroblasts are collected in real time by means of SERS active thin nanofilm (30 nm) on colloidal silica (1.5 μm). Nanofilm is composed of preformed silver nanoparticles in the matrix of polyacrylic acid, protecting against heating (37 °C) in water, or culture medium or phosphate buffered saline aqueous solution. The SERS enhancement factors (EFs) of the order 10(8) allow single biomolecule detection in the native environment of a single live cell. Primary and secondary SERS hot spots of nanofilm are responsible for such high EFs. A slow SERS EF intensity decay occurs over a broader distance of micron silica with nanofilm, not achievable in a common core-shell model (silver nanoparticle coated with a thin silica layer). Extensive local field EFs and SERS EFs are mainly delivered by prolate silver nanoparticles ("rugby-like" shape). This is achieved if an incident field is polarized along the z-axis and the direction of incident polarization and main axis (z) are perpendicular to each other, not observable in water or on gold.

To explore the development and maintenance of human-robot interaction (HRI) in a real-world setting, we conducted a three-month long field study with the socially assistive robot PARO in a nursing home. We placed PARO a public area in the institution and observed naturally occurring interactions of nursing home residents, staff, and visitors with the robot. We collected both quantitative (on-site behavioral coding and interactor counts) and qualitative (observational field notes) data. The results of behavioral analysis complemented with information from our field notes show that interaction with PARO was often not spontaneous and that mediation from staff and family members was integral to successful interactions between residents and PARO. We also observed that individual interactors engaged with the robot in diverse ways based on their needs. We conclude by discussing design and methodological implications for in situ HRI studies.

With robots becoming more prevalent in daily life, it is important to understand human attitudes toward robots not only when humans interact with them directly, as most research examines, but also when people are indirectly exposed to robots performing nonsocial tasks (e.g., cleaning) in their vicinity. Because minimalistic robots are at present more likely to be found in households than human-like robots, this study examined human reactions to nonsocial, nonanthropomorphic robots. The specific focus of this study was on how robot communication style during human-robot co-location affects human perceptions of a group of robots. This paper also evaluates the relationship between participants' scores on the Negative Attitudes toward Robots Scale (NARS) and their behavioral response to and perceptions of robots in their environment. Our results suggest that robot communication style did not affect perceptions of robots and that responses on the NARS may not translate directly to behavior toward robots.

We performed an experimental study (n=48) of the effects of context congruency on human perceptions of robotic facial expressions across cultures (Western and East Asian individuals). We found that context congruency had a significant effect on human perceptions, and that this effect varied by the emotional valence of the context and facial expression. Moreover, these effects occurred regardless of the cultural background of the participants. In short, there were predictable patterns in the effects of congruent/incongruent environmental context on perceptions of robot affect across Western and East Asian individuals. We argue that these findings fit with a dynamical systems view of social cognition as an emergent phenomenon. Taking advantage of such context effects may ease the constraints for developing culturally-specific affective cues in human-robot interaction, opening the possibility to create culture-neutral models of robots and affective interaction.

Background Many techniques are proposed for the quantification of tumor heterogeneity as an imaging biomarker for differentiation between tumor types, tumor grading, response monitoring and outcome prediction. However, in clinical practice these methods are barely used. This study evaluates the reported performance of the described methods and identifies barriers to their implementation in clinical practice. Methodology The Ovid, Embase, and Cochrane Central databases were searched up to 20 September 2013. Heterogeneity analysis methods were classified into four categories, i.e., non-spatial methods (NSM), spatial grey level methods (SGLM), fractal analysis (FA) methods, and filters and transforms (F&T). The performance of the different methods was compared. Principal Findings Of the 7351 potentially relevant publications, 209 were included. Of these studies, 58% reported the use of NSM, 49% SGLM, 10% FA, and 28% F&T. Differentiation between tumor types, tumor grading and/or outcome prediction was the goal in 87% of the studies. Overall, the reported area under the curve (AUC) ranged from 0.5 to 1 (median 0.87). No relation was found between the performance and the quantification methods used, or between the performance and the imaging modality. A negative correlation was found between the tumor-feature ratio and the AUC, which is presumably caused by overfitting in small datasets. Cross-validation was reported in 63% of the classification studies. Retrospective analyses were conducted in 57% of the studies without a clear description. Conclusions In a research setting, heterogeneity quantification methods can differentiate between tumor types, grade tumors, and predict outcome and monitor treatment effects. To translate these methods to clinical practice, more prospective studies are required that use external datasets for validation: these datasets should be made available to the community to facilitate the development of new and improved methods.