a randomized, placebo-controlled phase II AIO trial with serum biomarker program

Background As a multi-targeted anti-angiogenic receptor tyrosine kinase (RTK) inhibitor sunitinib (SUN) has been established for renal cancer and gastrointestinal stromal tumors. In advanced refractory esophagogastric cancer patients, monotherapy with SUN was associated with good tolerability but limited tumor response. Methods This double-blind, placebo-controlled, multicenter, phase II clinical trial was conducted to evaluate the efficacy, safety and tolerability of SUN as an adjunct to second and third-line FOLFIRI (NCT01020630). Patients were randomized to receive 6-week cycles including FOLFIRI plus sodium folinate (Na-FOLFIRI) once every two weeks and SUN or placebo (PL) continuously for four weeks followed by a 2-week rest period. The primary study endpoint was progression-free survival (PFS). Preplanned serum analyses of VEGF-A, VEGF-D, VEGFR2 and SDF-1α were performed retrospectively. Results Overall, 91 patients were randomized, 45 in each group (one patient withdrew). The main grade ≥3 AEs were neutropenia and leucopenia, observed in 56 %/20 % and 27 %/16 % for FOLFIRI + SUN/FOLFIRI + PL, respectively. Median PFS was similar, 3.5 vs. 3.3 months (hazard ratio (HR) 1.11, 95 % CI 0.70–1.74, P = 0.66) for FOLFIRI + SUN vs. FOLFIRI + PL, respectively. For FOLFIRI + SUN, a trend towards longer median overall survival (OS) compared with placebo was observed (10.4 vs. 8.9 months, HR 0.82, 95 % CI 0.50–1.34, one-sided P = 0.21). In subgroup serum analyses, significant changes in VEGF-A (P = 0.017), VEGFR2 (P = 0.012) and VEGF-D (P < 0.001) serum levels were observed. Conclusions Although sunitinib combined with FOLFIRI did not improve PFS and response in chemotherapy-resistant gastric cancer, a trend towards better OS was observed. Further biomarker-driven studies with other anti- angiogenic RTK inhibitors are warranted. Trial registration This study was registered prospectively in the NCT Clinical Trials Registry (ClinicalTrials.gov) under NCT01020630 on November 23, 2009 after approval by the leading ethics committee of the Medical Association of Rhineland- Palatinate, Mainz, in coordination with the participating ethics committees (see Additional file 2) on September 16, 2009

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Tomographie par absorption et par oscillation de la terre profonde avec KM3NeT et les futurs détecteurs de neutrinos atmosphériques

Structure and composition of the deep Earth are constrained by seismic methods and geochemical models based on primitive meteorites. These leave some questions unsolved, such as the exact composition of the outer core or the nature of seismic anomalies at the core/mantle boundary (LLSVP). Neutrinos are neutral elementary particles that only interact with matter by the weak force and are thus able to cover large distances even through dense media such as the Earth, opening a new window to study our planet's interior. By studying absorption of atmospheric neutrinos>30TeV, absorption tomography allows to draw conclusions about the average matter density along the neutrino path. Furthermore, at energies of a few GeV, oscillation tomography exploits the fact that neutrino avour oscillations are affected by the electron density along the neutrino path, an observable connected to both the matter density and chemical composition of the traversed media. The first studies in this thesis are performed for the two water-Cherenkov detectors ARCA and ORCA, currently being built in the Mediterranean Sea as part of the KM3NeT infrastructure. The detector response is modelled using Monte Carlo simulations developed within the KM3NeT Collaboration. Absorption tomography with ARCA can resolve the average radial density profile of the Earth with a clear separation of core and mantle. The precision from studying atmospheric neutrinos alone appears insufficient to study finer structures. Improvements could come by exploiting the high energy astrophysical neutrino flux, as detected by IceCube. From oscillation tomography with ORCA, density variations compared to PREM can be constrained with a respective precision of +24%/-32% for the inner core and ~5% for the lower mantle, with 10 yr of ORCA data. In the same timescale, ORCA could constrain the density variations of large seismic anomalies in the deep mantle to +24%/-21 %. The sensitivity to the proton-to-nucleon ratio (Z/A) in the outer core was found to be ~5 %. The second part of this thesis uses a more generic approach based on parameterised response functions, allowing to compare the capabilities of ORCA with other neutrino detectors currently under construction, such as the water-Cherenkov detector Hyper- Kamiokande and the Liquid Argon experiment DUNE. HyperKamiokande is found to provide the highest sensitivity to the outer core composition (Z/A), with a precision of ~2.5 %. However, a sub-percent precision is needed to distinguish concurrent models of core composition. A hypothetical 'Next-Generation' detector with enhanced size and detection capabilities is proposed for that purpose. Albeit the realisation of such a detector seems challenging with current budgets and technologies, it could make a significant contribution to the knowledge of the outer core composition, as well as the nature of LLSVPs, hence the understanding of deep Earth dynamics.La structure et la composition de la Terre profonde sont déterminées par des méthodes sismiques, et des modéles géochimiques basés sur desmétéorites primitives. Les contraintes apportées par ces techniques laissent cependant des questions sans réponse, comme la composition exacte du noyau externe ou la nature des zones présentant des anomalies sismiques á la limite noyau/manteau (LLSVP). Les neutrinos sont des particules élémentaires neutres qui n'interagissent avec la matière que par la force faible et sont donc capables de couvrir de grandes distances, même á travers des milieux denses comme la Terre. Ils ouvrent ainsi une nouvelle voie pour étudier la Terre profonde. En étudiant l'absorption des neutrinos atmosphériques >30TeV, la tomographie d'absorption permet de tirer des conclusions sur la densité moyenne de matière le long du trajet des neutrinos. De plus, á des énergies de quelques GeV, la tomographie d'oscillation exploite le fait que les oscillations de saveur des neutrinos sont affectées par la densité d'électrons le long de la trajectoire du neutrino, une observable liée á la fois á la densité de matiére et á la composition chimique des milieux traversés. Les premières études de cette thése sont réalisées pour les deux détecteurs de Cherenkov á eau ARCA et ORCA, actuellement en cours de construction dans la mer Méditerranée dans le cadre de l'infrastructure KM3NeT. La réponse du détecteur est modélisée á l'aide de simulations Monte Carlo développées au sein de la collaboration KM3NeT. La tomographie par absorption avec ARCA peut résoudre le profil de densité radiale moyen de la Terre avec une séparation claire du noyau et du manteau. La précision de la mesure avec les neutrinos atmosphériques est insufisante pour étudier des structures plus fines, mais de meilleurs résultats pourraient être obtenus en exploitant le flux de neutrinos astrophysiques de haute énergie tel qu'observé par IceCube. Pour ORCA, les variations de densité par rapport au PREM peuvent êtrecontraintes avec une précision respective de +24%/-32% pour le noyau interne et de ~5% pour le manteau inférieur, avec 10 années de données. Sur la même échelle de temps, ORCA pourrait contraindre les variations de densité des grandes anomalies sismiques dans le manteau profond á +24%/-21 %. La sensibilité au rapport proton/nucléon (Z/A) dans le noyau externe est quant á elle de ~5 %. La deuxiéme partie de cette thése utilise une approche plus générique basée sur des fonctions de réponse paramétrées, permettant de comparer les capacités d'ORCA avec d'autres détecteurs de neutrinos actuellement en construction, tels que le detecteur HyperKamiokande á eau-Cherenkov et l'expérience DUNE á argon liquide. Hyper- Kamiokande offre la plus grande sensibilité á la composition du noyau externe (Z/A), avec une précision de ~2.5 %. Cependant, une précision inférieure á un pour cent reste nécessaire pour distinguer les modéles concurrents de composition du noyau. Un détecteur hypothétique de "nouvelle génération", de taille et de capacité de détection accrues, est proposé á cet effet. Bien que la réalisation d'un tel détecteur soit dificileavec les budgets et technologies actuels, il apporterait une contribution significative á la connaissance de la composition du noyau externe et de la nature des anomalies sismiques, donc á la compréhension de l'origine et de la dynamique de la Terre profonde

Probing the earth’s interior with neutrinos

Neutrinos, the lightest entities of the Standard Model of particle physics, can traverse matter like no other known particle. The advent of a new generation of neutrino telescopes is turning these elusive messengers into a new probe to investigate the structure and composition of the deep Earth

KM3NeT performance on oscillation and absorption tomography of the Earth

International audienceThe KM3NeT neutrino telescope, currently under construction, consists of two detectors in the Mediterranean Sea, ORCA and ARCA, both using arrays of optical modules to detect the Cherenkov light produced by charged particles created in neutrino interactions. Although originally designed for neutrino oscillation and astrophysical research, this experiment also bears unprecedented possibilities for other fields of physics. Here we present its performance for neutrino tomography, i.e. \ the study of the Earth’s internal structure and composition.Owing to the different energy ranges covered by its two detectors ORCA and ARCA, KM3NeT will be the first experiment to perform both oscillation and absorption neutrino tomography. Resonance effects in the oscillations of GeV neutrinos traversing the Earth will allow KM3NeT/ORCA to measure the electron density along their trajectory, leading to potential constraints of the proton-to-nucleon (Z/A) ratio in the traversed matter. Absorption tomography aims at the detection of neutrinos in the TeV-PeV range with KM3NeT/ARCA. At PeV energies, the Earth is opaque for neutrinos which leads to a reduction of the upgoing neutrino flux at the detector side from which conclusions can be drawn about the density of the inner layers of the Earth.We show here first sensitivity studies of the potential of KM3NeT to address open questions of geophysics concerning the chemical composition and matter distribution in the Earth’s core and mantle through neutrino tomography

Probing the earth’s interior with neutrinos

Neutrinos, the lightest entities of the Standard Model of particle physics, can traverse matter like no other known particle. The advent of a new generation of neutrino telescopes is turning these elusive messengers into a new probe to investigate the structure and composition of the deep Earth.</jats:p