Protontherapy is a rapidly expanding radiotherapy modality where accelerated proton beams are used to precisely deliver the dose to the tumor target but is generally considered ineffective against radioresistant tumors. Proton-Boron Capture Therapy (PBCT) is a novel approach aimed at enhancing proton biological effectiveness. PBCT exploits a nuclear fusion reaction between low-energy protons and 11B atoms, i.e. p+11B→ 3α (p-B), which is supposed to produce highly-DNA damaging α-particles exclusively across the tumor-conformed Spread-Out Bragg Peak (SOBP), without harming healthy tissues in the beam entrance channel. To confirm previous work on PBCT, here we report new in-vitro data obtained at the 62-MeV ocular melanoma-dedicated proton beamline of the INFN-Laboratori Nazionali del Sud (LNS), Catania, Italy. For the first time, we also tested PBCT at the 250-MeV proton beamline used for deep-seated cancers at the Centro Nazionale di Adroterapia Oncologica (CNAO), Pavia, Italy. We used Sodium Mercaptododecaborate (BSH) as 11B carrier, DU145 prostate cancer cells to assess cell killing and non-cancer epithelial breast MCF-10A cells for quantifying chromosome aberrations (CAs) by FISH painting and DNA repair pathway protein expression by western blotting. Cells were exposed at various depths along the two clinical SOBPs. Compared to exposure in the absence of boron, proton irradiation in the presence of BSH significantly reduced DU145 clonogenic survival and increased both frequency and complexity of CAs in MCF-10A cells at the mid- and distal SOBP positions, but not at the beam entrance. BSH-mediated enhancement of DNA damage response was also found at mid-SOBP. These results corroborate PBCT as a strategy to render protontherapy amenable towards radiotherapy-resilient tumor. If coupled with emerging proton FLASH radiotherapy modalities, PBCT could thus widen the protontherapy therapeutic index.

21We statistically investigate the Coronavirus Disease 19 (hereinafter Covid-19) epidemics, which is 22 particularly invasive in Italy. We show that the high apparent mortality (or Case Fatality Ratio, 23 CFR) observed in Italy, as compared with other countries, is likely biased by a strong 24 underestimation of infected cases. To give a more realistic estimate of the mortality of Covid-19, 25we use the most recent estimates of the IFR (Infection Fatality Ratio) of epidemic, based on the 26 minimum observed CFR, and furthermore analyse data obtained from the ship Diamond Princess, a 27 good representation of a 'laboratory' case-study from an isolated system in which all the people 28 have been tested. From such analyses we derive more realistic estimates of the real extension of the 29 infection, as well as more accurate indicators of how fast the infection propagates. We then point 30 out from the various explanations proposed, the dominant factors causing such an abnormal 31 seriousness of the disease in Italy. Finally, we use the deceased data, the only ones estimated to be 32 reliable enough, to predict the total number of infected people and the interval of time when the 33 infection in Italy could stop.

We statistically investigate the Coronavirus Disease 19 (COVID-19) pandemic, which became particularly invasive in Italy in March 2020. We show that the high apparent lethality or case fatality ratio (CFR) observed in Italy, as compared with other countries, is likely biased by a strong underestimation of the number of infection cases. To give a more realistic estimate of the lethality of COVID-19, we use the actual (March 2020) estimates of the infection fatality ratio (IFR) of the pandemic based on the minimum observed CFR and analyze data obtained from the Diamond Princess cruise ship, a good representation of a “laboratory” case-study from an isolated system in which all the people have been tested. From such analyses, we derive more realistic estimates of the real extent of the infection as well as more accurate indicators of how fast the infection propagates. We then isolate the dominant factors causing the abnormal severity of the disease in Italy. Finally, we use the death count—the only data estimated to be reliable enough—to predict the total number of people infected and the interval of time when the infection in Italy could end.