Blinatumomab can induce a complete haematological remission in patients in 46.6% with relapsed/refractory B-precursor acute lymphoblastic leukemia (r/r ALL) resulting in a survival benefit when compared with chemotherapy. Only bone marrow blast counts before therapy have shown a weak prediction of response. Here we investigated the role of regulatory T cells (Tregs), measured by CD4/CD25/FOXP3 expression, in predicting the outcome of immunotherapy with the CD19-directed bispecific T-cell engager construct blinatumomab. Blinatumomab responders (n=22) had an average of 4.82% Tregs (confidence interval (CI): 1.79–8.34%) in the peripheral blood, whereas non-responders (n=20) demonstrated 10.25% Tregs (CI: 3.36–65.9%). All other tested markers showed either no prediction value or an inferior prediction level including blast BM counts and the classical enzyme marker lactate dehydrogenase. With a cutoff of 8.525%, Treg enumeration can identify 100% of all blinatumomab responders and exclude 70% of the non-responders. The effect is facilitated by blinatumomab-activated Tregs, leading to interleukin-10 production, resulting in suppression of T-cell proliferation and reduced CD8-mediated lysis of ALL cells. Proliferation of patients' T cells can be restored by upfront removal of Tregs. Thus, enumeration of Treg identifies r/r ALL patients with a high response rate to blinatumomab. Therapeutic removal of Tregs may convert blinatumomab non-responders to responders.

We propose a method to recognize the traffic scene in front of a moving vehicle with respect to the road topology and the existence of objects. To this end, we use a two-stage system, where the first stage abstracts from the underlying image by means of a rough super-pixel segmentation of the scene. In a second stage, this meta representation is then used to construct a feature set for a classifier that is able to distinguish between different road types as well as detect the existence of commonly encountered objects, such as cars or pedestrian crossings. We show that by relying on an intermediate stage, we can effectively abstract from any peculiarities of the underlying image data due to e.g. color abberrations. The method is tested on two long, challenging urban data sets, covering both day light and dusk conditions. Compared to a state-of-the-art descriptor, we show improved classification performance, especially for object classes.

SUMMARY BackgroundEndoscopic balloon dilation has been shown to be an alternative to surgery in the treatment of Crohn's symptomatic strictures.

The eruption of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (corona virus disease, COVID-19) in Wuhan, China, and its global spread has led to an exponentially growing number of infected patients, currently exceeding over 6.6 million and over 390,000 deaths as of the 5th of June 2020. In this pandemic situation, health systems have been put under stress, and the demand for personal protective equipment (PPE) exceeded the delivery capabilities of suppliers. To address this issue, 3D printing was identified as a possible solution to quickly produce PPE items such as face shields, mask straps, masks, valves, and ear savers. Around the world, companies, universities, research institutions, and private individuals/hobbyists stepped into the void, using their 3D printers to support hospitals, doctors, nursing homes, and even refugee camps by providing them with PPE. In Germany, the makervsvirus movement took up the challenge and connected thousands of end users, makers, companies, and logistic providers for the production and supply of face shields, protective masks, and ear savers. The Karlsruhe Institute of Technology (KIT) also joined the makervsvirus movement and used its facilities to print headbands for face shield assemblies and ear savers. Within this paper, the challenges and lessons learned from the quick ramp up of a research laboratory to a production site for medium-sized batches of PPE, the limitations in material supply, selection criteria for suitable models, quality measures, and future prospects are reported and conclusions drawn.

A process for the development, characterization and correlation of composite materials for 3D printing is presented, alongside the processing of a polymer-ceramic functional composite using fused deposition modeling (FDM). The composite was developed using acrylonitrile butadiene styrene (ABS) as the matrix material filled with barium titanate (BT) micro-powder up to 35 vol % (74.2 wt %). The ABS-BT composites exhibited a shear thinning behavior with increasing ceramic content. The composite was 3D printed into structural and functional test samples using FDM by adapting and optimizing the print parameters. Structural characterization revealed increasingly brittle behavior at higher filler ratios, with the ultimate tensile strength falling from 25.5 MPa for pure ABS to 13.7 MPa for the ABS-35 vol % BT composite. Four-point flexural tests showed a similar decrease in flexural strength with increasing ceramic content. Functional characterization revealed an increase in the relative permittivity at 200 kHz from 3.08 for pure ABS to 11.5 for the composite with 35 vol % BT. These results were correlated with the Maxwell-Garnett and Jayasundere-Smith effective medium models. The process described in this work can be used for other 3D printing processes and provides a framework for the rapid prototyping of functional composites into functional parts with reliable properties. The ABS-BT composite shows promise as a functional dielectric material, with potential applications as capacitors and light-weight passive antennas.