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

Specific genomic aberrations in primary colorectal cancer are associated with liver metastases

Background: Accurate staging of colorectal cancer (CRC) with clinicopathological parameters is important for predicting prognosis and guiding treatment but provides no information about organ site of metastases. Patterns of genomic aberrations in primary colorectal tumors may reveal a chromosomal signature for organ specific metastases. Methods: Array Comparative Genomic Hybridization (aCGH) was employed to asses DNA copy number changes in primary colorectal tumors of three distinctive patient groups. This included formalin-fixed, paraffin-embedded tissue of patients who developed liver metastases (LM; n = 36), metastases (PM; n = 37) and a group that remained metastases-free (M0; n = 25). A novel statistical method for identifying recurrent copy number changes, KC-SMART, was used to find specific locations of genomic aberrations specific for various groups. We created a classifier for organ specific metastases based on the aCGH data using Prediction Analysis for Microarrays (PAM). Results: Specifically in the tumors of primary CRC patients who subsequently developed liver metastasis, KC-SMART analysis identified genomic aberrations on chromosome 20q. LM-PAM, a shrunken centroids classifier for liver metastases occurrence, was able to distinguish the LM group from the other groups (M0&PM) with 80% accuracy (78% sensitivity and 86% specificity). The classification is predominantly based on chromosome 20q aberrations. Conclusion: Liver specific CRC metastases may be predicted with a high accuracy based on specific genomic aberrations in the primary CRC tumor. The ability to predict the site of metastases is important for improvement of personalized patient management.MediamaticsElectrical Engineering, Mathematics and Computer Scienc

Glucocorticoid Regulation of Astrocytic Fate and Function

Glial loss in the hippocampus has been suggested as a factor in the pathogenesis of stress-related brain disorders that are characterized by dysregulated glucocorticoid (GC) secretion. However, little is known about the regulation of astrocytic fate by GC. Here, we show that astrocytes derived from the rat hippocampus undergo growth inhibition and display moderate activation of caspase 3 after exposure to GC. Importantly, the latter event, observed both in situ and in primary astrocytic cultures is not followed by either early- or late-stage apoptosis, as monitored by stage I or stage II DNA fragmentation. Thus, unlike hippocampal granule neurons, astrocytes are resistant to GC-induced apoptosis; this resistance is due to lower production of reactive oxygen species (ROS) and a greater buffering capacity against the cytotoxic actions of ROS. We also show that GC influence hippocampal cell fate by inducing the expression of astrocyte-derived growth factors implicated in the control of neural precursor cell proliferation. Together, our results suggest that GC instigate a hitherto unknown dialog between astrocytes and neural progenitors, adding a new facet to understanding how GC influence the cytoarchitecture of the hippocampus

Gene Expression Profile of Neuronal Progenitor Cells Derived from hESCs: Activation of Chromosome 11p15.5 and Comparison to Human Dopaminergic Neurons

BACKGROUND: We initiated differentiation of human embryonic stem cells (hESCs) into dopamine neurons, obtained a purified population of neuronal precursor cells by cell sorting, and determined patterns of gene transcription. METHODOLOGY: Dopaminergic differentiation of hESCs was initiated by culturing hESCs with a feeder layer of PA6 cells. Differentiating cells were then sorted to obtain a pure population of PSA-NCAM-expressing neuronal precursors, which were then analyzed for gene expression using Massive Parallel Signature Sequencing (MPSS). Individual genes as well as regions of the genome which were activated were determined. PRINCIPAL FINDINGS: A number of genes known to be involved in the specification of dopaminergic neurons, including MSX1, CDKN1C, Pitx1 and Pitx2, as well as several novel genes not previously associated with dopaminergic differentiation, were expressed. Notably, we found that a specific region of the genome located on chromosome 11p15.5 was highly activated. This region contains several genes which have previously been associated with the function of dopaminergic neurons, including the gene for tyrosine hydroxylase (TH), the rate-limiting enzyme in catecholamine biosynthesis, IGF2, and CDKN1C, which cooperates with Nurr1 in directing the differentiation of dopaminergic neurons. Other genes in this region not previously recognized as being involved in the functions of dopaminergic neurons were also activated, including H19, TSSC4, and HBG2. IGF2 and CDKN1C were also found to be highly expressed in mature human TH-positive dopamine neurons isolated from human brain samples by laser capture. CONCLUSIONS: The present data suggest that the H19-IGF2 imprinting region on chromosome 11p15.5 is involved in the process through which undifferentiated cells are specified to become neuronal precursors and/or dopaminergic neurons

Search for neutral MSSM Higgs bosons decaying to a pair of tau leptons in pp collisions

Peer reviewe

Measurement of top quark–antiquark pair production in association with a W or Z boson in pp collisions at √s=8 TeV

Peer reviewe

Study of hadronic event-shape variables in multijet final states in pp collisions at √s=7 TeV

Peer reviewe

Searches for electroweak production of charginos, neutralinos, and sleptons decaying to leptons and W, Z, and Higgs bosons in pp collisions at 8 TeV

Peer reviewe

Measurement of prompt J/ψ pair production in pp collisions at √s = 7 Tev

Peer reviewe