Bypassing the structural bottleneck in the ultrafast melting of electronic order

The emergent properties of quantum materials, such as symmetry-broken phases and associated spectral gaps, can be effectively manipulated by ultrashort photon pulses. Impulsive optical excitation generally results in a complex non-equilibrium electron and lattice dynamics that involves multiple processes on distinct timescales, and a common conception is that for times shorter than about 100 fs the gap in the electronic spectrum is not seriously affected by lattice vibrations. Here, we directly monitor the photo-induced collapse of the spectral gap in a canonical charge-density-wave material, blue bronze Rb0.3MoO3. We find that ultra-fast (about 60 fs) vibrational disordering due to efficient hot-electron energy dissipation quenches the gap significantly faster than the typical structural bottleneck time corresponding to one half-cycle oscillation (about 315 fs) of the coherent charge-density-wave amplitude mode. This result not only demonstrates the importance of incoherent lattice motion in the photo-induced quenching of electronic order, but also resolves the perennial debate about the nature of the spectral gap in a coupled electron-lattice system

Ultrafast modulation of the chemical potential in BaFe2As2 by coherent phonons

Time- and angle-resolved extreme ultraviolet photoemission spectroscopy is used to study the electronic structure dynamics in BaFe2As2 around the high-symmetry points Γ and M. A global oscillation of the Fermi level at the frequency of the A1g(As) phonon mode is observed. It is argued that this behavior reflects a modulation of the effective chemical potential in the photoexcited surface region that arises from the high sensitivity of the band structure near the Fermi level to the A1g(As) phonon mode combined with a low electron diffusivity perpendicular to the layers. The results establish a novel way to tune the electronic properties of iron pnictides: coherent control of the effective chemical potential. The results further suggest that the equilibration time for the effective chemical potential needs to be considered in the ultrafast electronic structure dynamics of materials with weak interlayer coupling. © 2014 American Physical Society

Time-resolved HAXPES using a microfocused XFEL beam : From vacuum space-charge effects to intrinsic charge-carrier recombination dynamics

Time-resolved hard X-ray photoelectron spectroscopy (trHAXPES) using microfocused X-ray free-electron laser (XFEL, h\u3bd = 8 keV) pulses as a probe and infrared laser pulses (h\u3bd = 1.55 eV) as a pump is employed to determine intrinsic charge- carrier recombination dynamics in La:SrTiO3. By means of a combination of experiments and numerical N-body simulations, we first develop a simple approach to characterize and decrease XFEL-induced vacuum space-charge effects, which otherwise pose a serious limitation to spectroscopy experiments. We then show that, using an analytical mean-field model, vacuum space-charge effects can be counteracted by pump laser-induced photoholes at high excitation densities. This provides us a method to seperate vacuum space-charge effects from the intrinsic charge-carrier recombination dynamics in the time domain. Our trHAXPES results thus open a route to studies of intrinsic charge-carrier dynamics on picosecond time scales with lateral spatial resolution on the micrometer scale

Reproducible radiomics through automated machine learning validated on twelve clinical applications

Radiomics uses quantitative medical imaging features to predict clinical outcomes. Currently, in a new clinical application, findingthe optimal radiomics method out of the wide range of available options has to be done manually through a heuristic trial-anderror process. In this study we propose a framework for automatically optimizing the construction of radiomics workflows perapplication. To this end, we formulate radiomics as a modular workflow and include a large collection of common algorithms foreach component. To optimize the workflow per application, we employ automated machine learning using a random search andensembling. We evaluate our method in twelve different clinical applications, resulting in the following area under the curves: 1)liposarcoma (0.83); 2) desmoid-type fibromatosis (0.82); 3) primary liver tumors (0.80); 4) gastrointestinal stromal tumors (0.77);5) colorectal liver metastases (0.61); 6) melanoma metastases (0.45); 7) hepatocellular carcinoma (0.75); 8) mesenteric fibrosis(0.80); 9) prostate cancer (0.72); 10) glioma (0.71); 11) Alzheimer’s disease (0.87); and 12) head and neck cancer (0.84). Weshow that our framework has a competitive performance compared human experts, outperforms a radiomics baseline, and performssimilar or superior to Bayesian optimization and more advanced ensemble approaches. Concluding, our method fully automaticallyoptimizes the construction of radiomics workflows, thereby streamlining the search for radiomics biomarkers in new applications.To facilitate reproducibility and future research, we publicly release six datasets, the software implementation of our framework,and the code to reproduce this study

DATA-DRIVEN SUBTYPES OF PARKINSON’S DISEASE USING MACHINE LEARNING IN LUXEMBOURG PARKINSON STUDY

peer reviewedR-AGR-0592 - FNR - NCER-PD Phase II Coordination (01/06/2015 - 30/11/2023) - KRÜGER Rejko3. Good health and well-bein

Characterizing the Syphilis-Causing Treponema pallidum ssp. pallidum Proteome Using Complementary Mass Spectrometry

YesBackground. The spirochete bacterium Treponema pallidum ssp. pallidum is the etiological agent of syphilis, a chronic multistage disease. Little is known about the global T. pallidum proteome, therefore mass spectrometry studies are needed to bring insights into pathogenicity and protein expression profiles during infection. Methodology/Principal Findings. To better understand the T. pallidum proteome profile during infection, we studied T. pallidum ssp. pallidum DAL-1 strain bacteria isolated from rabbits using complementary mass spectrometry techniques, including multidimensional peptide separation and protein identification via matrix-assisted laser desorption ionization-time of flight (MALDI-TOF/TOF) and electrospray ionization (ESI-LTQ-Orbitrap) tandem mass spectrometry. A total of 6033 peptides were detected, corresponding to 557 unique T. pallidum proteins at a high level of confidence, representing 54% of the predicted proteome. A previous gel-based T. pallidum MS proteome study detected 58 of these proteins. One hundred fourteen of the detected proteins were previously annotated as hypothetical or uncharacterized proteins; this is the first account of 106 of these proteins at the protein level. Detected proteins were characterized according to their predicted biological function and localization; half were allocated into a wide range of functional categories. Proteins annotated as potential membrane proteins and proteins with unclear functional annotations were subjected to an additional bioinformatics pipeline analysis to facilitate further characterization. A total of 116 potential membrane proteins were identified, of which 16 have evidence supporting outer membrane localization. We found 8/12 proteins related to the paralogous tpr gene family: TprB, TprC/D, TprE, TprG, TprH, TprI and TprJ. Protein abundance was semi-quantified using label-free spectral counting methods. A low correlation (r = 0.26) was found between previous microarray signal data and protein abundance. Conclusions. This is the most comprehensive description of the global T. pallidum proteome to date. These data provide valuable insights into in vivo T. pallidum protein expression, paving the way for improved understanding of the pathogenicity of this enigmatic organism.This work was supported by the grants from the Flanders Research Foundation, SOFI-B Grant to CRK, http://www.fwo.be/, a Public Health Service Grant from the National Institutes of Health to CEC, (grant # AI-051334), https://www.nih.gov/ and a grant from the Grant Agency of the Czech Republic to DS and MS (P302/12/0574, GP14-29596P), https:// gacr.cz/