Prognostic significance of tumour budding in Merkel cell carcinoma

Prognostic factors in Merkel cell carcinoma (MCC) are scarce. Tumour budding (TB) has been shown to have a prognostic role in different cancers but has not been explored in MCC. We aimed to determine if TB influences survival in MCC. We performed a retrospective evaluation of 45 cases of MCC in a cancer centre. This included a survival analysis involving TB in patients with MCC, and we searched for variables associated with TB. The mean age of the patients was 69 years. Histologically, the average Breslow was 11.36 mm, and the mean mitotic rate was 31.9 mitoses/mm2. The diagnosis was made in clinical stages I and II in 40% of cases, 22.2% in stage III, and 37.8% in stage IV. Tumour budding was low ( 10 buds/0.785 mm2) in 24.4%. There were no clinical or pathological features associated with high TB. Among the prognostic factors for 5-year survival, we found that tumour size and clinical stage were statistically associated with survival (p = 0.031 and 0.021), but TB was not. No clinical or pathological characteristics of MCC are associated with any degree of TB. Tumour budding does not influence overall survival

Efficacy and safety of self-expanding metal stents in patients with inoperable esophageal cancer: a real-life study

Background: Dysphagia is the most frequent symptom in patients diagnosed with esophageal cancer. Self-expanding metal stents (SEMS) are the current palliative treatment of choice for dysphagia in patients with non-curable esophageal cancer. This study aimed to evaluate the efficacy and adverse events (AEs) of different types of SEMS for palliation of dysphagia. Methods: We performed a retrospective cohort study of patients with advanced esophageal cancer and SEMS placement for dysphagia palliation in a tertiary care center. The primary outcome was the clinical success defined as an improvement in dysphagia (reduction of at least 2 points in the Mellow–Pinkas scoring system for dysphagia) after SEMS placement. Results: Between January 1999 and May 2020, 295 patients with esophageal cancer were identified. Among them, 75 had a SEMS placement for dysphagia palliation. The mean age of the patients was 61.3 years (standard deviation: 13.4), 69 patients (92%) were men, and the mean Mellow–Pinkas scoring for dysphagia pre- and post-SEMS placement were 3.1 and 1.4 (change from baseline −1.7), respectively. Technical success and clinical success were achieved in 98.6% and 58.9%, respectively. AEs were identified in 35/75 patients (46.7%), and SEMS migration was the most frequent AE in 22/75 patients (29.3%). There were no significant differences in improvement in dysphagia ( p  = 0.054), weight changes ( p  = 0.78), and AE ( p  = 0.73) among fully covered SEMS (fc-SEMS) and partially covered SEMS (pc-SEMS). The median follow-up was 89 days (interquartile range: 29–221). Conclusion: SEMS placement was associated with a rapid improvement in dysphagia, high technical success, and a modest improvement in dysphagia with no major AE among fc-SEMS and pc-SEMS

sj-docx-1-cmg-10.1177_26317745231200975 – Supplemental material for Efficacy and safety of self-expanding metal stents in patients with inoperable esophageal cancer: a real-life study

Supplemental material, sj-docx-1-cmg-10.1177_26317745231200975 for Efficacy and safety of self-expanding metal stents in patients with inoperable esophageal cancer: a real-life study by José Miguel Jiménez-Gutiérrez, Juan Octavio Alonso-Lárraga, Angélica I. Hernández-Guerrero, Leonardo Saul Lino-Silva and Antonio Olivas-Martinez in Therapeutic Advances in Gastrointestinal Endoscopy</p

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on $10^3$ pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on $10^3$ pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on $10^3$ pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on $10^3$ pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Impact of cross-section uncertainties on supernova neutrino spectral parameter fitting in the Deep Underground Neutrino Experiment

International audienceA primary goal of the upcoming Deep Underground Neutrino Experiment (DUNE) is to measure the O(10)  MeV neutrinos produced by a Galactic core-collapse supernova if one should occur during the lifetime of the experiment. The liquid-argon-based detectors planned for DUNE are expected to be uniquely sensitive to the νe component of the supernova flux, enabling a wide variety of physics and astrophysics measurements. A key requirement for a correct interpretation of these measurements is a good understanding of the energy-dependent total cross section σ(Eν) for charged-current νe absorption on argon. In the context of a simulated extraction of supernova νe spectral parameters from a toy analysis, we investigate the impact of σ(Eν) modeling uncertainties on DUNE’s supernova neutrino physics sensitivity for the first time. We find that the currently large theoretical uncertainties on σ(Eν) must be substantially reduced before the νe flux parameters can be extracted reliably; in the absence of external constraints, a measurement of the integrated neutrino luminosity with less than 10% bias with DUNE requires σ(Eν) to be known to about 5%. The neutrino spectral shape parameters can be known to better than 10% for a 20% uncertainty on the cross-section scale, although they will be sensitive to uncertainties on the shape of σ(Eν). A direct measurement of low-energy νe-argon scattering would be invaluable for improving the theoretical precision to the needed level