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

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

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

Peer reviewe

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

Peer reviewe

Constraints on parton distribution functions and extraction of the strong coupling constant from the inclusive jet cross section in pp collisions at √s=7 TeV

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

Search for squarks and gluinos in final states with jets and missing transverse momentum at root s=13 TeV with the ATLAS detector

SCOAP

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

Heavy Ion Results from ATLAS

These proceedings provide an overview of the new results obtained with the ATLAS detector at the LHC, which were presented in the Quark Matter 2017 conference. These results were covered by twelve parallel talks, one flash talk and eleven posters. These proceedings group these results into five areas: initial state, jet quenching, quarkonium production, longitudinal flow dynamics, and collectivity in small systems