A critical evaluation of network and pathway based classifiers for outcome prediction in breast cancer

Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single gene classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single gene classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single gene classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single gene sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single gene classifiers for predicting outcome in breast cancer

Estrogens Can Disrupt Amphibian Mating Behavior

The main component of classical contraceptives, 17α-ethinylestradiol (EE2), has high estrogenic activity even at environmentally relevant concentrations. Although estrogenic endocrine disrupting compounds are assumed to contribute to the worldwide decline of amphibian populations by adverse effects on sexual differentiation, evidence for EE2 affecting amphibian mating behaviour is lacking. In this study, we demonstrate that EE2 exposure at five different concentrations (0.296 ng/L, 2.96 ng/L, 29.64 ng/L, 2.96 µg/L and 296.4 µg/L) can disrupt the mating behavior of adult male Xenopus laevis. EE2 exposure at all concentrations lowered male sexual arousal, indicated by decreased proportions of advertisement calls and increased proportions of the call type rasping, which characterizes a sexually unaroused state of a male. Additionally, EE2 at all tested concentrations affected temporal and spectral parameters of the advertisement calls, respectively. The classical and highly sensitive biomarker vitellogenin, on the other hand, was only induced at concentrations equal or higher than 2.96 µg/L. If kept under control conditions after a 96 h EE2 exposure (2.96 µg/L), alterations of male advertisement calls vanish gradually within 6 weeks and result in a lower sexual attractiveness of EE2 exposed males toward females as demonstrated by female choice experiments. These findings indicate that exposure to environmentally relevant EE2 concentrations can directly disrupt male mate calling behavior of X. laevis and can indirectly affect the mating behavior of females. The results suggest the possibility that EE2 exposure could reduce the reproductive success of EE2 exposed animals and these effects might contribute to the global problem of amphibian decline

On the stability of high-speed milling with spindle speed variation

Spindle speed variation is a well-known technique to suppress regenerative machine tool vibrations, but it is usually considered to be effective only for low spindle speeds. In this paper, the effect of spindle speed variation is analyzed in the high-speed domain for spindle speeds corresponding to the first flip (period doubling) and to the first Hopf lobes. The optimal amplitudes and frequencies of the speed modulations are computed using the semidiscre- tization method. It is shown that period doubling chatter can effectively be suppressed by spindle speed variation, although, the technique is not effective for the quasiperiodic chatter above the Hopf lobe. The results are verified by cutting tests. Some special cases are also discussed where the practical behavior of the system differs from the predicted one in some ways. For these cases, it is pointed out that the concept of stability is understood on the scale of the principal period of the system—that is, the speed modulation period for variable spindle speed machining and the tooth passing period for constant spindle speed machining

Could rebel child soldiers prolong civil wars?

While we know why rebels may recruit children for their cause, our understanding of the consequences of child soldiering by non-state armed groups remains limited. The following research contributes to addressing this by examining how rebels? child recruitment practice affects the duration of internal armed conflicts. We advance the argument that child soldiering increases the strength of rebel organizations vis-�-vis the government. This, in turn, lowers the capability asymmetry between these nonstate actors and the incumbent, allowing the former to sustain in dispute. Ultimately, the duration of armed conflicts is likely to be prolonged. We analyze this relationship with quantitative data on child soldier recruitment by rebel groups in the post-1989 period. The results confirm our main hypothesis: disputes are substantially longer when rebels recruit children. This work has important implications for the study of armed conflicts, conflict duration, and our understanding of child soldiering

Immunodepletion of high-abundant proteins from acute and chronic wound fluids to elucidate low-abundant regulators in wound healing

<p>Abstract</p> <p>Background</p> <p>The process of wound healing consists of several well distinguishable and finely tuned phases. For most of these phases specific proteins have been characterized, although the underlying mechanisms of regulation are not yet fully understood. It is an open question as to whether deficits in wound healing can be traced back to chronic illnesses such as diabetes mellitus. Previous research efforts in this field focus largely on a restricted set of marker proteins due to the limitations detection by antibodies imposes. For mechanistic purposes the elucidation of differences in acute and chronic wounds can be addressed by a less restricted proteome study. Mass spectrometric (MS) methods, e.g. multi dimensional protein identification technology (MudPIT), are well suitable for this complex theme of interest. The human wound fluid proteome is extremely complex, as is human plasma. Therefore, high-abundant proteins often mask the mass spectrometric detection of lower-abundant ones, which makes a depletion step of such predominant proteins inevitable.</p> <p>Findings</p> <p>In this study a commercially available immunodepletion kit was evaluated for the detection of low-abundant proteins from wound fluids. The dynamic range of the entire workflow was significantly increased to 5-6 orders of magnitude, which makes low-abundant regulatory proteins involved in wound healing accessible for MS detection.</p> <p>Conclusion</p> <p>The depletion of abundant proteins is absolutely necessary in order to analyze highly complex protein mixtures such as wound fluids using mass spectrometry. For this the used immunodepletion kit is a first but important step in order to represent the entire dynamic range of highly complex protein mixtures in the future.</p

Case-oriented computer-based-training in radiology: concept, implementation and evaluation

BACKGROUND: Providing high-quality clinical cases is important for teaching radiology. We developed, implemented and evaluated a program for a university hospital to support this task. METHODS: The system was built with Intranet technology and connected to the Picture Archiving and Communications System (PACS). It contains cases for every user group from students to attendants and is structured according to the ACR-code (American College of Radiology) [2]. Each department member was given an individual account, could gather his teaching cases and put the completed cases into the common database. RESULTS: During 18 months 583 cases containing 4136 images involving all radiological techniques were compiled and 350 cases put into the common case repository. Workflow integration as well as individual interest influenced the personal efforts to participate but an increasing number of cases and minor modifications of the program improved user acceptance continuously. 101 students went through an evaluation which showed a high level of acceptance and a special interest in elaborate documentation. CONCLUSION: Electronic access to reference cases for all department members anytime anywhere is feasible. Critical success factors are workflow integration, reliability, efficient retrieval strategies and incentives for case authoring

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Interactive effects of ambient fine particulate matter and ozone on daily mortality in 372 cities: two stage time series analysis

Objective To investigate potential interactive effects of fine particulate matter (PM2.5) and ozone (O3) on daily mortality at global level. Design Two stage time series analysis. Setting 372 cities across 19 countries and regions. Population Daily counts of deaths from all causes, cardiovascular disease, and respiratory disease. Main outcome measure Daily mortality data during 1994-2020. Stratified analyses by co-pollutant exposures and synergy index (>1 denotes the combined effect of pollutants is greater than individual effects) were applied to explore the interaction between PM2.5 and O3 in association with mortality. Results During the study period across the 372 cities, 19.3 million deaths were attributable to all causes, 5.3 million to cardiovascular disease, and 1.9 million to respiratory disease. The risk of total mortality for a 10 μg/m3 increment in PM2.5 (lag 0-1 days) ranged from 0.47% (95% confidence interval 0.26% to 0.67%) to 1.25% (1.02% to 1.48%) from the lowest to highest fourths of O3 concentration; and for a 10 μg/m3 increase in O3 ranged from 0.04% (−0.09% to 0.16%) to 0.29% (0.18% to 0.39%) from the lowest to highest fourths of PM2.5 concentration, with significant differences between strata (P for interaction <0.001). A significant synergistic interaction was also identified between PM2.5 and O3 for total mortality, with a synergy index of 1.93 (95% confidence interval 1.47 to 3.34). Subgroup analyses showed that interactions between PM2.5 and O3 on all three mortality endpoints were more prominent in high latitude regions and during cold seasons. Conclusion The findings of this study suggest a synergistic effect of PM2.5 and O3 on total, cardiovascular, and respiratory mortality, indicating the benefit of coordinated control strategies for both pollutants