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Abstract The efficacy of costimulation blockade with CTLA4-Ig (belatacept) in transplantation is limited due to T cell-mediated rejection, which also persists after induction with anti-thymocyte globulin (ATG). Here, we investigate why ATG fails to prevent costimulation blockade-resistant rejection and how this barrier can be overcome. ATG did not prevent graft rejection in a murine heart transplant model of CTLA4-Ig therapy and induced a pro-inflammatory cytokine environment. While ATG improved the balance between regulatory T cells (Treg) and effector T cells in the spleen, it had no such effect within cardiac allografts. Neutralizing IL-6 alleviated graft inflammation, increased intragraft Treg frequencies, and enhanced intragraft IL-10 and Th2-cytokine expression. IL-6 blockade together with ATG allowed CTLA4-Ig therapy to achieve long-term, rejection-free heart allograft survival. This beneficial effect was abolished upon Treg depletion. Combining ATG with IL-6 blockade prevents costimulation blockade-resistant rejection, thereby eliminating a major impediment to clinical use of costimulation blockers in transplantation.

Summary: Background: Induction of donor-specific tolerance is a promising approach to achieve long-term graft patency in transplantation with little to no maintenance immunosuppression. Changes to the recipient’s T cell receptor (TCR) repertoire are understood to play a pivotal role in the establishment of a robust state of tolerance in chimerism-based transplantation protocols. Methods: We investigated changes to the TCR repertoires of patients participating in an ongoing prospective, controlled, phase I/IIa trial designed to evaluate the safety and efficacy of combination cell therapy in living donor kidney transplantation. Using high-throughput sequencing, we characterized the repertoires of six kidney recipients who also received bone marrow from the same donor (CKBMT), together with an infusion of polyclonal autologous Treg cells instead of myelosuppression. Findings: Patients undergoing combination cell therapy exhibited partial clonal deletion of donor-reactive CD4+ T cells at one, three, and six months post-transplant, compared to control patients receiving the same immunosuppression regimen but no cell therapy (p = 0.024). The clonality, R20 and turnover rates of the CD4+ and CD8+ TCR repertoires were comparable in both groups, showing our protocol caused no excessive repertoire shift or loss of diversity. Treg clonality was lower in the case group than in control (p = 0.033), suggesting combination cell therapy helps to preserve Treg diversity. Interpretation: Overall, our data indicate that combining Treg cell therapy with CKBMT dampens the alloimmune response to transplanted kidneys in humans in the absence of myelosuppression. Funding: This study was funded by the Vienna Science and Technology Fund (WWTF).

Abstract Even after decades of research, pancreatic ductal adenocarcinoma (PDAC) remains a highly lethal disease and responses to conventional treatments remain mostly poor. Subclassification of PDAC into distinct biological subtypes has been proposed by various groups to further improve patient outcome and reduce unnecessary side effects. Recently, an immunohistochemistry (IHC)‐based subtyping method using cytokeratin‐81 (KRT81) and hepatocyte nuclear factor 1A (HNF1A) could recapitulate some of the previously established molecular subtyping methods, while providing significant prognostic and, to a limited degree, also predictive information. We refined the KRT81/HNF1A subtyping method to classify PDAC into three distinct biological subtypes. The prognostic value of the IHC‐based method was investigated in two primary resected cohorts, which include 269 and 286 patients, respectively. In the second cohort, we also assessed the predictive effect for response to erlotinib + gemcitabine. In both PDAC cohorts, the new HNF1A‐positive subtype was associated with the best survival, the KRT81‐positive subtype with the worst, and the double‐negative with an intermediate survival (p

Pancreatic ductal adenocarcinoma (PDAC) is typically diagnosed at advanced stages and associated with early distant metastasis and poor survival. Besides clinical factors, the tumor microenvironment (TME) emerged as a crucial determinant of patient survival and therapy response in many tumors, including PDAC. Thus, the presence of tumor-infiltrating lymphocytes and the formation of tertiary lymphoid structures (TLS) is associated with longer survival in PDAC. Although neoadjuvant therapy (NeoTx) has improved the management of locally advanced tumors, detailed insight into its effect on various TME components is limited. While a remodeling towards a proinflammatory state was reported for PDAC-infiltrating T cells, the effect of NeoTx on B cell subsets, including plasma cells, and TLS formation is widely unclear. We thus investigated the frequency, composition, and spatial distribution of PDAC-infiltrating B cells in primary resected (PR) versus neoadjuvant-treated patients using a novel multiplex immunohistochemistry panel. The NeoTx group displayed significantly lower frequencies of pan B cells, GC B cells, plasmablasts, and plasma cells, accompanied by a reduced abundance of TLS. This finding was supported by bulk RNA-sequencing analysis of an independent fresh frozen tissue cohort, which revealed that major B cell pathways were downregulated in the NeoTx group. We further observed that plasma cells frequently formed aggregates that localized close to TLS and that TLS+ patients displayed significantly higher plasma cell frequencies compared to TLS- patients in the PR group. Additionally, high densities of CD20+ intratumoral B cells were significantly associated with longer overall survival in the PR group. While CD20+ B cells held no prognostic value for NeoTx patients, an increased frequency of proliferating CD20+Ki67+ B cells emerged as an independent prognostic factor for longer survival in the NeoTx group. These results indicate that NeoTx differentially affects PDAC-infiltrating immune cells and may have detrimental effects on the existing B cell landscape and the formation of TLS. Gaining further insight into the underlying molecular mechanisms is crucial to overcome the intrinsic immunotherapy resistance of PDAC and develop novel strategies to improve the long-term outcome of PDAC patients.

Solid cancers like pancreatic ductal adenocarcinoma (PDAC), a type of pancreatic cancer, frequently exploit nerves for rapid dissemination. This neural invasion (NI) is an independent prognostic factor in PDAC, but insufficiently modeled in genetically engineered mouse models (GEMM) of PDAC. Here, we systematically screened for human-like NI in Europe’s largest repository of GEMM of PDAC, comprising 295 different genotypes. This phenotype screen uncovered 2 GEMMs of PDAC with human-like NI, which are both characterized by pancreas-specific overexpression of transforming growth factor α (TGF-α) and conditional depletion of p53. Mechanistically, cancer-cell-derived TGF-α upregulated CCL2 secretion from sensory neurons, which induced hyperphosphorylation of the cytoskeletal protein paxillin via CCR4 on cancer cells. This activated the cancer migration machinery and filopodia formation toward neurons. Disrupting CCR4 or paxillin activity limited NI and dampened tumor size and tumor innervation. In human PDAC, phospho-paxillin and TGF-α–expression constituted strong prognostic factors. Therefore, we believe that the TGF-α-CCL2-CCR4-p-paxillin axis is a clinically actionable target for constraining NI and tumor progression in PDAC.

New advanced driver assistance system/automated driving (ADAS/AD) functions have the potential to significantly enhance the safety of vehicle passengers and road users, while also enabling new transportation applications and potentially reducing CO2 emissions. To achieve the next level of driving automation, i.e., SAE Level-3, physical test drives need to be supplemented by simulations in virtual test environments. A major challenge for today’s virtual test environments is to provide a realistic representation of the vehicle’s perception system (camera, lidar, radar). Therefore, new and improved sensor models are required to perform representative virtual tests that can supplement physical test drives. In this article, we present a computationally efficient, mathematically complete, and geometrically exact generic sensor modeling approach that solves the FOV (field of view) and occlusion task. We also discuss potential extensions, such as bounding-box cropping and sensor-specific, weather-dependent FOV-reduction approaches for camera, lidar, and radar. The performance of the new modeling approach is demonstrated using camera measurements from a test campaign conducted in Hungary in 2020 plus three artificial scenarios (a multi-target scenario with an adjacent truck occluding other road users and two traffic jam situations in which the ego vehicle is either a car or a truck). These scenarios are benchmarked against existing sensor modeling approaches that only exclude objects that are outside the sensor’s maximum detection range or angle. The modeling approach presented can be used as is or provide the basis for a more complex sensor model, as it reduces the number of potentially detectable targets and therefore improves the performance of subsequent simulation steps.

Solid cancers like pancreatic ductal adenocarcinoma (PDAC), a type of pancreatic cancer, frequently exploit nerves for rapid dissemination. This neural invasion (NI) is an independent prognostic factor in PDAC, but insufficiently modeled in genetically engineered mouse models (GEMM) of PDAC. Here, we systematically screened for human-like NI in Europe's largest repository of GEMM of PDAC, comprising 295 different genotypes. This phenotype screen uncovered 2 GEMMs of PDAC with human-like NI, which are both characterized by pancreas-specific overexpression of transforming growth factor [alpha] (TGF-[alpha]) and conditional depletion of p53. Mechanistically, cancer-cell-derived TGF-[alpha] upregulated CCL2 secretion from sensory neurons, which induced hyperphosphorylation of the cytoskeletal protein paxillin via CCR4 on cancer cells. This activated the cancer migration machinery and filopodia formation toward neurons. Disrupting CCR4 or paxillin activity limited NI and dampened tumor size and tumor innervation. In human PDAC, phospho-paxillin and TGF-[alpha]-expression constituted strong prognostic factors. Therefore, we believe that the TGF- [alpha]-CCL2-CCR4-p-paxillin axis is a clinically actionable target for constraining NI and tumor progression in PDAC., Introduction Pancreatic ductal adenocarcinoma (PDAC) is currently the third leading cause of cancer-associated death worldwide and is projected to become the second by 2030 (1). Remarkable progress has been made [...]

IntroductionAntibody mediated rejection (ABMR) is a major factor limiting outcome after organ transplantation. Anti-HLA donor-specific antibodies (DSA) of the IgG isotype are mainly responsible for ABMR. Recently DSA of the IgE isotype were demonstrated in murine models as well as in a small cohort of sensitized transplant recipients. In the present study, we aimed to determine the frequency of pre-existing and de novo anti-HLA IgE antibodies in a cohort of 105 solid organ transplant recipients.MethodsWe prospectively measured anti-HLA IgE antibodies in a cohort of kidney (n=60), liver, heart and lung (n=15 each) transplant recipients before and within one-year after transplantation, employing a single-antigen bead assay for HLA class I and class II antigens. Functional activity of anti-HLA IgE antibodies was assessed by an in vitro mediator release assay. Antibodies of the IgG1-4 subclasses and Th1 and Th2 cytokines were measured in anti-HLA IgE positive patients.ResultsPre-existing anti-HLA IgE antibodies were detected in 10% of renal recipients (including 3.3% IgE-DSA) and in 4.4% of non-renal solid organ transplant recipients (heart, liver and lung cohort). Anti-HLA IgE occurred only in patients that were positive for anti-HLA IgG, and most IgE positive patients had had a previous transplant. Only a small fraction of patients developed de novo anti-HLA IgE antibodies (1.7% of kidney recipients and 4.4% of non-renal recipients), whereas no de novo IgE-DSA was detected. IgG subclass antibodies showed a distinct pattern in patients who were positive for anti-HLA IgE. Moreover, patients with anti-HLA IgE showed elevated Th2 and also Th1 cytokine levels. Serum from IgE positive recipients led to degranulation of basophils in vitro, demonstrating functionality of anti-HLA IgE.DiscussionThese data demonstrate that anti-HLA IgE antibodies occur at low frequency in kidney, liver, heart and lung transplant recipients. Anti-HLA IgE development is associated with sensitization at the IgG level, in particular through previous transplants and distinct IgG subclasses. Taken together, HLA specific IgE sensitization is a new phenomenon in solid organ transplant recipients whose potential relevance for allograft injury requires further investigation.

We propose a newly developed modular MObile LIdar SENsor System (MOLISENS) to enable new applications for small industrial lidar (light detection and ranging) sensors. The stand-alone modular setup supports both monitoring of dynamic processes and mobile mapping applications based on SLAM (Simultaneous Localization and Mapping) algorithms. The main objective of MOLISENS is to exploit newly emerging perception sensor technologies developed for the automotive industry for geoscientific applications. However, MOLISENS can also be used for other application areas, such as 3D mapping of buildings or vehicle-independent data collection for sensor performance assessment and sensor modeling. Compared to TLSs, small industrial lidar sensors provide advantages in terms of size (on the order of 10 cm), weight (on the order of 1 kg or less), price (typically between EUR 5000 and 10 000), robustness (typical protection class of IP68), frame rates (typically 10–20 Hz), and eye safety class (typically 1). For these reasons, small industrial lidar systems can provide a very useful complement to currently used TLS (terrestrial laser scanner) systems that have their strengths in range and accuracy performance. The MOLISENS hardware setup consists of a sensor unit, a data logger, and a battery pack to support stand-alone and mobile applications. The sensor unit includes the small industrial lidar Ouster OS1-64 Gen1, a ublox multi-band active GNSS (Global Navigation Satellite System) with the possibility for RTK (real-time kinematic), and a nine-axis Xsens IMU (inertial measurement unit). Special emphasis was put on the robustness of the individual components of MOLISENS to support operations in rough field and adverse weather conditions. The sensor unit has a standard tripod thread for easy mounting on various platforms. The current setup of MOLISENS has a horizontal field of view of 360∘, a vertical field of view with a 45∘ opening angle, a range of 120 m, a spatial resolution of a few centimeters, and a temporal resolution of 10–20 Hz. To evaluate the performance of MOLISENS, we present a comparison between the integrated small industrial lidar Ouster OS1-64 and the state-of-the-art high-accuracy and high-precision TLS Riegl VZ-6000 in a set of controlled experimental setups. We then apply the small industrial lidar Ouster OS1-64 in several real-world settings. The mobile mapping application of MOLISENS has been tested under various conditions, and results are shown from two surveys in the Lurgrotte cave system in Austria and a glacier cave in Longyearbreen on Svalbard.

BackgroundBreast cancer is one of the most common malignancies worldwide and remains incurable after metastasis, with a 3-year overall survival rate of

The main objective of this article is to provide angle-dependent spectral reflectance measurements of various materials in the near infrared spectrum. In contrast to already existing reflectance libraries, e.g., NASA ECOSTRESS and Aster reflectance libraries, which consider only perpendicular reflectance measurements, the presented dataset includes angular resolution of the material reflectance. To conduct the angle-dependent spectral reflectance material measurements, a new measurement device based on a 945 nm time-of-flight camera is used, which was calibrated using Lambertian targets with defined reflectance values at 10, 50, and 95%. The spectral reflectance material measurements are taken for an angle range of 0° to 80° with 10° incremental steps and stored in table format. The developed dataset is categorized with a novel material classification, divided into four different levels of detail considering material properties and distinguishing predominantly between mutually exclusive material classes (level 1) and material types (level 2). The dataset is published open access on the open repository Zenodo with record number 7467552 and version 1.0.1 [1]. Currently, the dataset contains 283 measurements and is continuously extended in new versions on Zenodo.

Avalanches pose a significant threat to the population and infrastructure of mountainous regions. The mapping and documentation of avalanches in Austria is mostly done by experts during field observations and covers usually only specific localized areas. A comprehensive mapping of avalanches is, however, crucial for the work of local avalanche commissions as well as avalanche warning services to assess, e.g., the avalanche danger. Over the past decade, mapping avalanches from satellite imagery has proven to be a promising and rapid approach to monitor avalanche activity in specific regions. Several recent avalanche detection approaches use deep learning-based algorithms to improve detection rates compared to traditional segmentation algorithms. Building on the success of these deep learning-based approaches, we present the first steps to build a modular data pipeline to map historical avalanche cycles in Copernicus Sentinel-1 imagery of the Austrian Alps. The Sentinel-1 mission has provided free all-weather synthetic aperture radar data since 2014, which has proven suitable for avalanche mapping in a Norwegian test area. In addition, we present a roadmap for setting up a segmentation algorithm, in which a general U-Net approach will serve as a baseline and will be compared with the mapping results of additional algorithms initially applied to autonomous driving. We propose to train the U-Net using labeled training dataset of avalanche outlines from Switzerland, Norway and Greenland. Due to the lack of training and validation data from Austria, we plan to compile the first avalanche archive for Austria. Meteorological variables, e.g., precipitation or wind, are highly important for the release of avalanches. In a completely new approach, we will therefore consider weather station data or outputs of numerical weather models in the learning-based algorithm to improve the detection performance. The mapping results in Austria will be complemented with pointwise field measurements of the MOLISENS platform and the RIEGL VZ-6000 terrestrial laser scanner.

Lidar sensors play an essential role in the perception system of automated vehicles. Fault Detection, Isolation, Identification, and Recovery (FDIIR) systems are essential for increasing the reliability of lidar sensors. Knowing the influence of different faults on lidar data is the first crucial step towards fault detection for lidar sensors in automated vehicles. We investigate the influences of sensor cover contaminations on the output data, i.e., on the lidar point cloud and full waveform. Different contamination types were applied (dew, dirt, artificial dirt, foam, water, and oil) and the influence on the output data of the single beam lidar RIEGL LD05-A20 and the automotive mechanically spinning lidar Ouster OS1-64 was evaluated. The LD05-A20 measurements show that dew, artificial dirt, and foam lead to unwanted reflections at the sensor cover. Dew, artificial dirt over the entire transmitter, and foam measurements lead to severe faults, i.e., complete sensor blindness. The OS1-64 measurements also show that dew can lead to almost complete sensor blindness. The results look promising for further studies on fault detection and isolation, since the different contamination types lead to different symptom combinations.

Lidar is an important component of the perception suite for automated systems. The effects of vibration on lidar point clouds are mostly unknown, despite the lidar’s wide adaption and usual application under conditions where vibration occurs frequently. In this study, we performed controlled vibration tests from 6 to 2000 Hz at 9 and 12 m/s2 in vertical direction on the automotive lidar OS1-64 by Ouster. An information loss emerged which is mostly independent from frequency and acceleration. The loss of points is randomly distributed and does not correlate with range, intensity, or ring number (the horizontal line of the rotating lidar unit). The resonance frequency of 1426 Hz proved to be unproblematic as no pronounced negative effects on the point cloud could be identified. For vibration detection, the internal Inertial Measurement Unit (IMU) of the OS1-64 is accurate and sufficient for vibrations up to 50 Hz. Above 50 Hz, external IMUs would be required for vibration detection. Counting the number of points on a target close to the edges was investigated as an exemplary way to detect vibration purely based on the point cloud, i.e., independent of the lidar’s IMU.

IntroductionIn de-novo kidney transplantation, the CTLA4-Ig fusion protein belatacept is associated with improved graft function but also an increased risk of acute rejection compared to calcineurin inhibitor therapy. The combination with a second costimulation blocker could potentially improve outcome while avoiding calcineurin inhibitor toxicity. The aim of this study was to define the conditions under which the combination of CTLA4-Ig and CD40L blockade leads to rejection-free permanent graft survival in a stringent murine heart transplantation model.MethodsNaïve wild-type or CD40L (CD154) knock-out mice received a fully mismatched BALB/c cardiac allograft. Selected induction and maintenance protocols for CTLA4-Ig and blocking αCD40L monoclonal antibodies (mAB) were investigated. Graft survival, rejection severity and donor-specific antibody (DSA) formation were assessed during a 100-day follow-up period.Results and DiscussionAdministering αCD40L mAb as monotherapy at the time of transplantation significantly prolonged heart allograft survival but did not further improve the outcome when given in addition to chronic CTLA4-Ig therapy (which prolongs graft survival to a median of 22 days). Likewise, chronic αCD40L mAb therapy (0.5mg) combined with perioperative CTLA4-Ig led to rejection in a proportion of mice and extensive histological damage, despite abrogating DSA formation. Only the permanent interruption of CD40-CD40L signaling by using CD40L-/- recipient mice or by chronic αCD40L administration synergized with chronic CTLA4-Ig to achieve long-term allograft survival with preserved histological graft integrity in all recipients without DSA formation. The combination of α-CD40L and CTLA4-Ig works most effectively when both therapeutics are administered chronically.