Deep Convolutional Framelets for Dose Reconstruction in Boron Neutron Capture Therapy with Compton Camera Detector.

Background: Boron neutron capture therapy (BNCT) is an innovative binary form of radiation therapy with high selectivity towards cancer tissue based on the neutron capture reaction B(n,α)Li, consisting in the exposition of patients to neutron beams after administration of a boron compound with preferential accumulation in cancer cells. The high linear energy transfer products of the ensuing reaction deposit their energy at the cell level, sparing normal tissue. Although progress in accelerator-based BNCT has led to renewed interest in this cancer treatment modality, in vivo dose monitoring during treatment still remains not feasible and several approaches are under investigation.

Can Serum and Saliva Inflammatory Cytokines Be Considered a Reliable Marker in Chronic Oral Graft-Versus-Host Disease Patients?

Chronic graft-versus-host disease (cGVHD) and oral lichen planus (LPO) are chronic inflammatory conditions with similar oral manifestations. This study aimed to assess whether serum and salivary cytokines (IL-1α, IL-6, IL-17) could serve as reliable biomarkers for cGVHD. A prospective cohort study was conducted involving cGVHD patients, LPO patients, and healthy controls.

Multicenter Study on the Impact of the Masker Babble Spectrum on the Acceptable Noise Level (ANL) Test.

Introduction: Acceptable Noise Level (ANL) is defined as the most comfortable level (MCL) intensity for speech and is calculated by subtracting the maximum noise tolerable by an individual. The ANL test has been used over time to predict hearing aid use and the impact of digital noise reduction. This study analyzes this impact by using different masker babble spectra when performing the ANL test in both hearing-impaired and healthy subjects in three different languages (Dutch, French, and Italian).

Search for Soft Unclustered Energy Patterns in Proton-Proton Collisions at 13 TeV.

The first search for soft unclustered energy patterns (SUEPs) is performed using an integrated luminosity of 138  fb^{-1} of proton-proton collision data at sqrt[s]=13  TeV, collected in 2016-2018 by the CMS detector at the LHC. Such SUEPs are predicted by hidden valley models with a new, confining force with a large 't Hooft coupling. In events with boosted topologies, selected by high-threshold hadronic triggers, the multiplicity and sphericity of clustered tracks are used to reject the background from standard model quantum chromodynamics.