The eLogBook Framework: Sustaining Interaction, Collaboration, and Learning in Laboratory-Oriented CoPs

Convinced by the important role of CoPs (communities of practice) and the innovative learning modality they offer, the Ecole Polytechnique Fédérale de Lausanne is currently developing a framework to sustain interaction, collaboration, and learning in laboratory-oriented CoPs, namely the eLogBook. This paper describes the services provided by this framework, the 3A model on which it is based, and the main features it presents. The eLogBook presents several innovative features that make it different from other classical collaboration workspaces. The eLogBook offers a high level of flexibility and adaptability so that it can fit the requirements of various CoPs. It allows CoPs' members to define their own rules, protocols, and vocabularies. The eLogBook also focus on usability and user acceptance thanks to its personalization and contextualization mechanisms. Finally, the eLogBook provides a community's members with ubiquitous services thanks to its multiple views and its advanced awareness services

Participatory Design for Awareness Features: Enhancing Interaction in Communities of Practice

In the framework of the European Integrated Project PALETTE, the École Polytechnique Fédérale de Lausanne (EPFL) and the University of Patras are developing mediation services. These services aim at sustaining collaboration, supporting tacit and explicit knowledge management and enhancing individual and organizational learning in communities of practice (CoPs). Defined by Dourish and Belloti as "an understanding of the activities of others, which provides a context for one's own activity", awareness is one of the most crucial needs expressed by communities of practice in the framework of the participatory design process implemented within the Palette project. Awareness of past and current actions in shared environments and over shared artifacts motivates participation and guides the members' decisions and course of actions. This paper describes the approach adopted by two Web-based collaboration support applications, namely eLogbook and CoPe_it!, for developing awareness services. CoPs needs, in terms of awareness, were identified through the participatory design approach. Then, a combination of relevant awareness types found in the literature was adopted in order to address the identified awareness requirements. The resulting awareness services implemented by Palette's mediation services (eLogbook and CoPe_it!) are presented. In particular, the kind of awareness information provided and its rendering means are described. For each tool, the available awareness functionality is related to the awareness type it contributes

W2S: Microscopy Data with Joint Denoising and Super-Resolution for Widefield to SIM Mapping

In fluorescence microscopy live-cell imaging, there is a critical trade-off between the signal-to-noise ratio and spatial resolution on one side, and the integrity of the biological sample on the other side. To obtain clean high-resolution (HR) images, one can either use microscopy techniques, such as structured-illumination microscopy (SIM), or apply denoising and super-resolution (SR) algorithms. However, the former option requires multiple shots that can damage the samples, and although efficient deep learning based algorithms exist for the latter option, no benchmark exists to evaluate these algorithms on the joint denoising and SR (JDSR) tasks. To study JDSR on microscopy data, we propose such a novel JDSR dataset, Widefield2SIM (W2S), acquired using a conventional fluorescence widefield and SIM imaging. W2S includes 144,000 real fluorescence microscopy images, resulting in a total of 360 sets of images. A set is comprised of noisy low-resolution (LR) widefield images with different noise levels, a noise-free LR image, and a corresponding high-quality HR SIM image. W2S allows us to benchmark the combinations of 6 denoising methods and 6 SR methods. We show that state-of-the-art SR networks perform very poorly on noisy inputs. Our evaluation also reveals that applying the best denoiser in terms of reconstruction error followed by the best SR method does not necessarily yield the best final result. Both quantitative and qualitative results show that SR networks are sensitive to noise and the sequential application of denoising and SR algorithms is sub-optimal. Lastly, we demonstrate that SR networks retrained end-to-end for JDSR outperform any combination of state-of-the-art deep denoising and SR networksComment: ECCVW 2020. Project page: \<https://github.com/ivrl/w2s

Outcome and Predictors of Treatment Failure in Total Hip/Knee Prosthetic Joint Infections Due to Staphylococcus aureus

The results of the present study suggest that ASA score ≤ 2 and use of rifampin-combination therapy are two independent factors associated with favorable outcome of patients treated for total hip or knee prosthetic infections due to S. aureus

Pre-cooling for endurance exercise performance in the heat: a systematic review.

PMCID: PMC3568721The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1741-7015/10/166. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Endurance exercise capacity diminishes under hot environmental conditions. Time to exhaustion can be increased by lowering body temperature prior to exercise (pre-cooling). This systematic literature review synthesizes the current findings of the effects of pre-cooling on endurance exercise performance, providing guidance for clinical practice and further research

Less is more: Antibiotics at the beginning of life

Antibiotic exposure at the beginning of life can lead to increased antimicrobial resistance and perturbations of the developing microbiome. Early-life microbiome disruption increases the risks of developing chronic diseases later in life. Fear of missing evolving neonatal sepsis is the key driver for antibiotic overtreatment early in life. Bias (a systemic deviation towards overtreatment) and noise (a random scatter) affect the decision-making process. In this perspective, we advocate for a factual approach quantifying the burden of treatment in relation to the burden of disease balancing antimicrobial stewardship and effective sepsis management

Orbital decay in an accreting and eclipsing 13.7 minute orbital period binary with a luminous donor

We report the discovery of ZTF J0127+5258, a compact mass-transferring binary with an orbital period of 13.7 minutes. The system contains a white dwarf accretor, which likely originated as a post-common envelope carbon-oxygen (CO) white dwarf, and a warm donor ($T_{\rm eff,\,donor}= 16,400\pm1000\,\rm K$). The donor probably formed during a common envelope phase between the CO white dwarf and an evolving giant which left behind a helium star or helium white dwarf in a close orbit with the CO white dwarf. We measure gravitational wave-driven orbital inspiral with $\sim 35\sigma$ significance, which yields a joint constraint on the component masses and mass transfer rate. While the accretion disk in the system is dominated by ionized helium emission, the donor exhibits a mixture of hydrogen and helium absorption lines. Phase-resolved spectroscopy yields a donor radial-velocity semi-amplitude of $771\pm27\,\rm km\, s^{-1}$, and high-speed photometry reveals that the system is eclipsing. We detect a {\it Chandra} X-ray counterpart with $L_{X}\sim 3\times 10^{31}\,\rm erg\,s^{-1}$. Depending on the mass-transfer rate, the system will likely evolve into either a stably mass-transferring helium CV, merge to become an R Crb star, or explode as a Type Ia supernova in the next million years. We predict that the Laser Space Interferometer Antenna (LISA) will detect the source with a signal-to-noise ratio of $24\pm6$ after 4 years of observations. The system is the first \emph{LISA}-loud mass-transferring binary with an intrinsically luminous donor, a class of sources that provide the opportunity to leverage the synergy between optical and infrared time domain surveys, X-ray facilities, and gravitational-wave observatories to probe general relativity, accretion physics, and binary evolution.Comment: 13 pages, 7 figures, 2 tables, submitted to ApJ

Cost impact of procalcitonin-guided decision making on duration of antibiotic therapy for suspected early-onset sepsis in neonates

Abstract Backgrounds The large, international, randomized controlled NeoPInS trial showed that procalcitonin (PCT)-guided decision making was superior to standard care in reducing the duration of antibiotic therapy and hospitalization in neonates suspected of early-onset sepsis (EOS), without increased adverse events. This study aimed to perform a cost-minimization study of the NeoPInS trial, comparing health care costs of standard care and PCT-guided decision making based on the NeoPInS algorithm, and to analyze subgroups based on country, risk category and gestational age. Methods Data from the NeoPInS trial in neonates born after 34 weeks of gestational age with suspected EOS in the first 72 h of life requiring antibiotic therapy were used. We performed a cost-minimization study of health care costs, comparing standard care to PCT-guided decision making. Results In total, 1489 neonates were included in the study, of which 754 were treated according to PCT-guided decision making and 735 received standard care. Mean health care costs of PCT-guided decision making were not significantly different from costs of standard care (€3649 vs. €3616). Considering subgroups, we found a significant reduction in health care costs of PCT-guided decision making for risk category ‘infection unlikely’ and for gestational age ≥ 37 weeks in the Netherlands, Switzerland and the Czech Republic, and for gestational age < 37 weeks in the Czech Republic. Conclusions Health care costs of PCT-guided decision making of term and late-preterm neonates with suspected EOS are not significantly different from costs of standard care. Significant cost reduction was found for risk category ‘infection unlikely,’ and is affected by both the price of PCT-testing and (prolonged) hospitalization due to SAEs

Machine learning used to compare the diagnostic accuracy of risk factors, clinical signs and biomarkers and to develop a new prediction model for neonatal early-onset sepsis

Background: Current strategies for risk stratification and prediction of neonatal early-onset sepsis (EOS) are inefficient and lack diagnostic performance. The aim of this study was to use machine learning to analyze the diagnostic accuracy of risk factors (RFs), clinical signs and biomarkers and to develop a prediction model for culture-proven EOS. We hypothesized that the contribution to diagnostic accuracy of biomarkers is higher than of RFs or clinical signs. Study Design: Secondary analysis of the prospective international multicenter NeoPInS study. Neonates born after completed 34 weeks of gestation with antibiotic therapy due to suspected EOS within the first 72 hours of life participated. Primary outcome was defined as predictive performance for culture-proven EOS with variables known at the start of antibiotic therapy. Machine learning was used in form of a random forest classifier. Results: One thousand six hundred eighty-five neonates treated for suspected infection were analyzed. Biomarkers were superior to clinical signs and RFs for prediction of culture-proven EOS. C-reactive protein and white blood cells were most important for the prediction of the culture result. Our full model achieved an area-under-the-receiver-operating-characteristic-curve of 83.41% (±8.8%) and an area-under-the-precision-recall-curve of 28.42% (±11.5%). The predictive performance of the model with RFs alone was comparable with random. Conclusions: Biomarkers have to be considered in algorithms for the management of neonates suspected of EOS. A 2-step approach with a screening tool for all neonates in combination with our model in the preselected population with an increased risk for EOS may have the potential to reduce the start of unnecessary antibiotics