Synchronized pulses generated at 20 eV and 90 eV for attosecond pump-probe experiments

The development of attosecond pulses across different photon energies is an essential precursor to performing pump–probe attosecond experiments in complex systems, where the potential of attosecond science1 can be further developed2,3. We report the generation and characterization of synchronized extreme ultraviolet (90 eV) and vacuum ultraviolet (20 eV) pulses, generated simultaneously via high-harmonic generation. The vacuum ultraviolet pulses are well suited for pump–probe experiments that exploit the high photo-ionization cross-sections of many molecules in this spectral region4 as well as the higher photon flux due to the higher conversion efficiency of the high harmonic generation process at these energies5. We temporally characterized all pulses using the attosecond streaking technique6 and the FROG-CRAB retrieval method7. We report 576 ± 16 as pulses at 20 eV and 257 ± 21 as pulses at 90 eV. Our demonstration of synchronized attosecond pulses at different photon energies, which are inherently jitter-free due to the common-path geometry implemented, offers unprecedented possibilities for pump–probe studies

Accurate prediction of X-ray pulse properties from a free-electron laser using machine learning

Free-electron lasers providing ultra-short high-brightness pulses of X-ray radiation have great potential for a wide impact on science, and are a critical element for unravelling the structural dynamics of matter. To fully harness this potential, we must accurately know the X-ray properties: intensity, spectrum and temporal profile. Owing to the inherent fluctuations in free-electron lasers, this mandates a full characterization of the properties for each and every pulse. While diagnostics of these properties exist, they are often invasive and many cannot operate at a high-repetition rate. Here, we present a technique for circumventing this limitation. Employing a machine learning strategy, we can accurately predict X-ray properties for every shot using only parameters that are easily recorded at high-repetition rate, by training a model on a small set of fully diagnosed pulses. This opens the door to fully realizing the promise of next-generation high-repetition rate X-ray lasers

Correlation-Driven Transient Hole Dynamics Resolved in Space and Time in the Isopropanol Molecule

The possibility of suddenly ionized molecules undergoing extremely fast electron hole (or hole) dynamics prior to significant structural change was first recognized more than 20 years ago and termed charge migration. The accurate probing of ultrafast electron hole dynamics requires measurements that have both sufficient temporal resolution and can detect the localization of a specific hole within the molecule. We report an investigation of the dynamics of inner valence hole states in isopropanol where we use an x-ray pump–x-ray probe experiment, with site and state-specific probing of a transient hole state localized near the oxygen atom in the molecule, together with an ab initio theoretical treatment. We record the signature of transient hole dynamics and make the first tentative observation of dynamics driven by frustrated Auger-Meitner transitions. We verify that the effective hole lifetime is consistent with our theoretical prediction. This state-specific measurement paves the way to widespread application for observations of transient hole dynamics localized in space and time in molecules and thus to charge transfer phenomena that are fundamental in chemical and material physics

Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information

<p>Abstract</p> <p>Background</p> <p>The identification of essential genes is important for the understanding of the minimal requirements for cellular life and for practical purposes, such as drug design. However, the experimental techniques for essential genes discovery are labor-intensive and time-consuming. Considering these experimental constraints, a computational approach capable of accurately predicting essential genes would be of great value. We therefore present here a machine learning-based computational approach relying on network topological features, cellular localization and biological process information for prediction of essential genes.</p> <p>Results</p> <p>We constructed a decision tree-based meta-classifier and trained it on datasets with individual and grouped attributes-network topological features, cellular compartments and biological processes-to generate various predictors of essential genes. We showed that the predictors with better performances are those generated by datasets with integrated attributes. Using the predictor with all attributes, i.e., network topological features, cellular compartments and biological processes, we obtained the best predictor of essential genes that was then used to classify yeast genes with unknown essentiality status. Finally, we generated decision trees by training the J48 algorithm on datasets with all network topological features, cellular localization and biological process information to discover cellular rules for essentiality. We found that the number of protein physical interactions, the nuclear localization of proteins and the number of regulating transcription factors are the most important factors determining gene essentiality.</p> <p>Conclusion</p> <p>We were able to demonstrate that network topological features, cellular localization and biological process information are reliable predictors of essential genes. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing essentiality.</p

Improving care for people with heart failure in Uganda: serial in-depth interviews with patients' and their health care professionals

Abstract Background The short prognosis of patients with advanced heart failure (HF) and the associated multidimensional distress as illustrated in literature from high income countries necessitates the integration of palliative care into the care of advanced HF patients to address these needs and improve their quality of life. These needs, which are subjective, have not been described from the patients’ and health care professionals’(HPs) view point in the Ugandan setting, a low income country with a different socio-cultural context. This study aimed at bridging this gap in knowledge by eliciting patients’ and HPs’ views of HF patients’ needs over the course of their illness to enable generalists, cardiologists and palliative care clinicians to develop guidelines to provide patient-centred realistic care in Uganda. Methods Serial qualitative in-depth interviews were conducted with HF patients who were purposively sampled and recruited in Mulago National Referral Hospital (MNRH) until thematic saturation. In-depth interviews were conducted at three time points with intervals of 3 month between interviews over the course of their illness in the hospital and their home context. One-off interviews were conducted with HPs that manage HF in MNRH. We used a grounded theory approach in data analysis. The Uganda National Council of science and technology approved the research. Results Forty-eight interviews were conducted with 21 patients and their carers and eight interviews with their HPs. Multidimensional needs including physical, psychological, social, spiritual and information needs were identified. These highlighted the underpinning need to have normal functioning, control, to cope and adapt to a changed life and to find meaning. Spiritual needs were less recognised by HPs than the other multidimensional needs. Information needs were commonly unmet. Patients and HPs suggested improvements in care that were congruent with the recommendations in chronic disease care and the six pillars of the WHO health systems strengthening approach. Conclusion Management of HF in Uganda requires an approach that targets multidimensional needs, embraces multidisciplinary care and strengthens health systems which are all important tenets of palliative care

Comparative genetic analysis: the utility of mouse genetic systems for studying human monogenic disease

One of the long-term goals of mutagenesis programs in the mouse has been to generate mutant lines to facilitate the functional study of every mammalian gene. With a combination of complementary genetic approaches and advances in technology, this aim is slowly becoming a reality. One of the most important features of this strategy is the ability to identify and compare a number of mutations in the same gene, an allelic series. With the advent of gene-driven screening of mutant archives, the search for a specific series of interest is now a practical option. This review focuses on the analysis of multiple mutations from chemical mutagenesis projects in a wide variety of genes and the valuable functional information that has been obtained from these studies. Although gene knockouts and transgenics will continue to be an important resource to ascertain gene function, with a significant proportion of human diseases caused by point mutations, identifying an allelic series is becoming an equally efficient route to generating clinically relevant and functionally important mouse models

Search for resonant production of second-generation sleptons with same-sign dimuon events in proton-proton collisions at root s=13 TeV

A search is presented for resonant production of second-generation sleptons ( μ˜L , ν˜μ ) via the R-parity-violating coupling λ′211 to quarks, in events with two same-sign muons and at least two jets in the final state. The smuon (muon sneutrino) is expected to decay into a muon and a neutralino (chargino), which will then decay into a second muon and at least two jets. The analysis is based on the 2016 data set of proton-proton collisions at s√=13TeV recorded with the CMS detector at the LHC, corresponding to an integrated luminosity of 35.9 fb−1 . No significant deviation is observed with respect to standard model expectations. Upper limits on cross sections, ranging from 0.24 to 730 fb , are derived in the context of two simplified models representing the dominant signal contributions leading to a same-sign muon pair. The cross section limits are translated into coupling limits for a modified constrained minimal supersymmetric model with λ′211 as the only nonzero R-parity violating coupling. The results significantly extend restrictions of the parameter space compared with previous searches for similar models

Enhanced attosecond pulse generation in the vacuum ultraviolet using a two-colour driving field for high harmonic generation

High-harmonic radiation in the extreme ultraviolet and soft X-ray spectral regions can be used to generate attosecond pulses and to obtain structural and dynamic information in atoms and molecules. However, these sources typically suffer from a limited photon flux. An additional issue at lower photon energies is the appearance of satellites in the time domain, stemming from insufficient temporal gating and the spectral filtering required for the isolation of attosecond pulses. Such satellites limit the temporal resolution. The use of multi-colour driving fields has been proven to enhance the harmonic yield and provide additional control, using the relative delays between the different spectral components for waveform shaping. We describe here a two-colour high-harmonic source that combines a few-cycle near-infrared pulse with a multi-cycle second harmonic pulse, with both relative phase and carrier-envelope phase stabilization. We observe strong modulations in the harmonic flux, and present simulations and experimental results supporting the suppression of satellites in sub-femtosecond pulses at 20 eV compared to the single colour field case, an important requirement for attosecond pump-probe measurements