Immunotherapy with FBTA05 (Bi20), a trifunctional bispecific anti-CD3 x anti-CD20 antibody and donor lymphocyte infusion (DLI) in relapsed or refractory B-cell lymphoma after allogeneic stem cell transplantation: study protocol of an investigator-driven, open-label, non-randomized, uncontrolled, dose-escalating Phase I/II-trial

Background: Patients with B cell malignancies refractory to allogeneic stem cell transplantation (SCT) can be treated by subsequent immunotherapy with donor lymphocyte infusions (DLI). But unlike myeloid leukemia, B cell leukemia and lymphoma are less sensitive to allogeneic adoptive immunotherapy. Moreover, the beneficial graft-versus-lymphoma (GVL) effect may be associated with moderate to severe graft-versus-host disease (GVHD). Thus, novel therapeutic approaches augmenting the anti-tumor efficacy of DLI and dissociating the GVL effect from GVHD are needed. The anti-CD20 x anti-CD3 trifunctional bispecific antibody (trAb) FBTA05 may improve the targeting of tumor cells by redirecting immune allogeneic effector cells while reducing the risk of undesirable reactivity against normal host cells. Hence, FBTA05 may maximize GVL effects by simultaneously decreasing the incidence and severity of GVHD. Methods/Design: Based on this underlying treatment concept and on promising data taken from preclinical results and a small pilot study, an open-label, non-randomized, uncontrolled, dose-escalating phase I/II-study is conducted to evaluate safety and preliminary efficacy of the investigational antibody FBTA05 in combination with DLI for patients suffering from rituximab-and/or alemtuzumab-refractory, CD20-positive low-or high-grade lymphoma after allogeneic SCT. During the first trial phase with emphasis on dose escalation a maximum of 24 patients distributed into 4 cohorts will be enrolled. For the evaluation of preliminary efficacy data a maximum of 12 patients (6 patients with low-grade lymphoma and/or Chronic Lymphocytic Leukemia (CLL) / 6 patients with high-grade or aggressive lymphoma) will attend the second phase of this clinical trial. Discussion: Promising data (e. g. induction of cellular immunity; GVL predominance over GVHD; achievement of partial or complete responses; prolongation of time-to-progression) obtained from this phase I/II trial would represent the first milestone in the clinical evaluation of a novel immunotherapeutic concept for treatment-resistant low- and high-grade lymphoma and NHL patients in relapse

Signature of short-range van der Waals forces observed in Poisson spot diffraction with indium atoms

The phase of de Broglie matter waves is a sensitive probe for small forces. In particular, the attractive van der Waals force experienced by polarizable atoms in the close vicinity of neutral surfaces is of importance in nanoscale systems. It results in a phase shift that can be observed in matter-wave diffraction experiments. Here, we observe Poisson spot diffraction of indium atoms at submillimeter distances behind spherical submicron silicon dioxide particles to probe the dispersion forces between atoms and the particle surfaces. We compare the measured relative intensity of Poisson’s spot to theoretical results derived from first principles in an earlier communication and find a clear signature of the atom-surface interaction

Shared Data and Algorithms for Deep Learning in Fundamental Physics

We introduce a collection of datasets from fundamental physics research -- including particle physics, astroparticle physics, and hadron- and nuclear physics -- for supervised machine learning studies. These datasets, containing hadronic top quarks, cosmic-ray induced air showers, phase transitions in hadronic matter, and generator-level histories, are made public to simplify future work on cross-disciplinary machine learning and transfer learning in fundamental physics. Based on these data, we present a simple yet flexible graph-based neural network architecture that can easily be applied to a wide range of supervised learning tasks in these domains. We show that our approach reaches performance close to state-of-the-art dedicated methods on all datasets. To simplify adaptation for various problems, we provide easy-to-follow instructions on how graph-based representations of data structures, relevant for fundamental physics, can be constructed and provide code implementations for several of them. Implementations are also provided for our proposed method and all reference algorithms.Comment: 13 pages, 5 figures, 5 table

Individuals' skills progression Patterns of mobility from lower to higher levels of employment

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