Genetic predictors of acute toxicities related to radiation therapy following lumpectomy for breast cancer: a case-series study

INTRODUCTION: The cytotoxic effects of radiation therapy are mediated primarily through increased formation of hydroxyl radicals and reactive oxygen species, which can damage cells, proteins and DNA; the glutathione S-transferases (GSTs) function to protect against oxidative stress. We hypothesized that polymorphisms encoding reduced or absent activity in the GSTs might result in greater risk for radiation-associated toxicity. METHODS: Women receiving therapy in radiation units in Germany following lumpectomy for breast cancer (1998–2001) provided a blood sample and completed an epidemiological questionnaire (n = 446). Genotypes were determined using Sequonom MALDI-TOF (GSTA1, GSTP1) and Masscode (GSTM1, GSTT1). Biologically effective radiotherapy dose (BED) was calculated, accounting for differences in fractionation and overall treatment time. Side effects considered were grade 2c and above, as classified using the modified Common Toxicity Criteria. Predictors of toxicity were modelled using Cox regression models in relation to BED, with adjustment for treating clinic, photon field, beam energy and boost method, and potential confounding variables. RESULTS: Low activity GSTP1 genotypes were associated with a greater than twofold increase in risk for acute skin toxicities (adjusted hazard ratio 2.28, 95% confidence interval 1.04–4.99). No associations were noted for the other GST genotypes. CONCLUSION: These data indicate that GSTP1 plays an important role in protecting normal cells from damage associated with radiation therapy. Studies examining the effects of GSTP1 polymorphisms on toxicity, recurrence and survival will further inform individualized therapeutics based on genotypes

Improving the Efficiency of Physical Examination Services

The objective of our project was to improve the efficiency of the physical examination screening service of a large hospital system. We began with a detailed simulation model to explore the relationships between four performance measures and three decision factors. We then attempted to identify the optimal physician inquiry starting time by solving a goal-programming problem, where the objective function includes multiple goals. One of our simulation results shows that the proposed optimal physician inquiry starting time decreased patient wait times by 50% without increasing overall physician utilization

Physics Potentials with the Second Hyper-Kamiokande Detector in Korea

We have conducted sensitivity studies on an alternative configuration of the Hyper-Kamiokande experiment by locating the 2nd Hyper-Kamiokande detector in Korea at $\sim$1100$-\$1300 km baseline. Having two detectors at different baselines improves sensitivity to leptonic CP violation, neutrino mass ordering as well as nonstandard neutrino interactions. There are several candidate sites in Korea with greater than 1 km high mountains ranged at an 1$-$3 degree off-axis angle. Thanks to larger overburden of the candidate sites in Korea, low energy physics, such as solar and supernova neutrino physics as well as dark matter search, is expected to be improved. In this paper sensitivity studies on the CP violation phase and neutrino mass ordering are performed using current T2K systematic uncertainties in most cases. We plan to improve our sensitivity studies in the near future with better estimation of our systematic uncertainties

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6  ×  6  ×  6 m 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between data and simulation

Low exposure long-baseline neutrino oscillation sensitivity of the DUNE experiment

The Deep Underground Neutrino Experiment (DUNE) will produce world-leading neutrino oscillation measurements over the lifetime of the experiment. In this work, we explore DUNE's sensitivity to observe charge-parity violation (CPV) in the neutrino sector, and to resolve the mass ordering, for exposures of up to 100 kiloton-megawatt-years (kt-MW-yr). The analysis includes detailed uncertainties on the flux prediction, the neutrino interaction model, and detector effects. We demonstrate that DUNE will be able to unambiguously resolve the neutrino mass ordering at a 3σ (5σ) level, with a 66 (100) kt-MW-yr far detector exposure, and has the ability to make strong statements at significantly shorter exposures depending on the true value of other oscillation parameters. We also show that DUNE has the potential to make a robust measurement of CPV at a 3σ level with a 100 kt-MW-yr exposure for the maximally CP-violating values \delta_{\rm CP}} = \pm\pi/2. Additionally, the dependence of DUNE's sensitivity on the exposure taken in neutrino-enhanced and antineutrino-enhanced running is discussed. An equal fraction of exposure taken in each beam mode is found to be close to optimal when considered over the entire space of interest