| 41. |
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| 42. |
- Aurelius, Johan, 1980, et al.
(author)
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NOX2-dependent immunosuppression in chronic myelomonocytic leukemia
- 2017
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In: Journal of Leukocyte Biology. - 0741-5400 .- 1938-3673. ; 102:2, s. 459-466
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Journal article (peer-reviewed)abstract
- Chronic myelomonocytic leukemia (CMML) is a myeloproliferative and myelodysplastic neoplasm with few treatment options and dismal prognosis. The role of natural killer (NK) cells and other antileukemic lymphocytes in CMML is largely unknown. We aimed to provide insight into the mechanisms of immune evasion in CMML with a focus on immunosuppressive reactive oxygen species (ROS) formed by the myeloid cell NADPH oxidase-2 (NOX2). The dominant population of primary human CMML cells was found to express membrane-bound NOX2 and to release ROS, which, in turn, triggered extensive PARP-1-dependent cell death in cocultured NK cells, CD8(+) T effector memory cells, and CD8(+) T effector cells. Inhibitors of ROS formation and scavengers of extracellular ROS prevented CMML cell-induced lymphocyte death and facilitated NK cell degranulation toward Ab-coated, primary CMML cells. In patients with CMML, elevation of immature cell counts (CD34(+)) in blood was associated with reduced expression of several NK cell-activating receptors. We propose that CMML cells may use extracellular ROS as a targetable mechanism of immune escape.
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| 43. |
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| 44. |
- Botteghi, N., et al.
(author)
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Low dimensional state representation learning with reward-shaped priors
- 2020
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In: Proceedings - International Conference on Pattern Recognition. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781728188089 ; , s. 3736-3743
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Conference paper (peer-reviewed)abstract
- Reinforcement Learning has been able to solve many complicated robotics tasks without any need for feature engineering in an end-to-end fashion. However, learning the optimal policy directly from the sensory inputs, i.e the observations, often requires processing and storage of a huge amount of data. In the context of robotics, the cost of data from real robotics hardware is usually very high, thus solutions that achieve high sample-efficiency are needed. We propose a method that aims at learning a mapping from the observations into a lower-dimensional state space. This mapping is learned with unsupervised learning using loss functions shaped to incorporate prior knowledge of the environment and the task. Using the samples from the state space, the optimal policy is quickly and efficiently learned. We test the method on several mobile robot navigation tasks in a simulation environment and also on a real robot. A video of our experiments can be found at: https://youtu.be/dgWxmfSv95U.
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| 45. |
- Botteghi, N., et al.
(author)
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Low Dimensional State Representation Learning with Robotics Priors in Continuous Action Spaces
- 2021
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In: IEEE International Conference on Intelligent Robots and Systems. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665417150 ; , s. 190-197
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Conference paper (peer-reviewed)abstract
- Reinforcement learning algorithms have proven to be capable of solving complicated robotics tasks in an end-to-end fashion without any need for hand-crafted features or policies. Especially in the context of robotics, in which the cost of real-world data is usually extremely high, Reinforcement Learning solutions achieving high sample efficiency are needed. In this paper, we propose a framework combining the learning of a low-dimensional state representation, from high-dimensional observations coming from the robot's raw sensory readings, with the learning of the optimal policy, given the learned state representation. We evaluate our framework in the context of mobile robot navigation in the case of continuous state and action spaces. Moreover, we study the problem of transferring what learned in the simulated virtual environment to the real robot without further retraining using real-world data in the presence of visual and depth distractors, such as lighting changes and moving obstacles. A video of our experiments can be found at: https://youtu.be/rUdGPKr2Wuo.
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| 46. |
- Botteghi, N., et al.
(author)
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Reinforcement learning helps slam : Learning to build maps
- 2020
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In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. - : International Society for Photogrammetry and Remote Sensing. ; , s. 329-336
-
Conference paper (peer-reviewed)abstract
- In this research, we investigate the use of Reinforcement Learning (RL) for an effective and robust solution for exploring unknown and indoor environments and reconstructing their maps. We benefit from a Simultaneous Localization and Mapping (SLAM) algorithm for real-time robot localization and mapping. Three different reward functions are compared and tested in different environments with growing complexity. The performances of the three different RL-based path planners are assessed not only on the training environments, but also on an a priori unseen environment to test the generalization properties of the policies. The results indicate that RL-based planners trained to maximize the coverage of the map are able to consistently explore and construct the maps of different indoor environments.
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| 47. |
- Brune, Mats, 1950, et al.
(author)
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Improved leukemia-free survival after postconsolidation immunotherapy with histamine dihydrochloride and interleukin-2 in acute myeloid leukemia: results of a randomized phase 3 trial
- 2006
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In: Blood. - : American Society of Hematology. - 0006-4971 .- 1528-0020. ; 108:1, s. 88-96
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Journal article (peer-reviewed)abstract
- The primary objective of this phase 3 study was to determine whether postconsolidation immunotherapy with interleukin-2 (IL-2) and histamine dihydrochloride (HDC) improved the leukemia-free survival (LFS) of adult patients with acute myeloid leukemia (AML) in complete remission (CR). Three hundred twenty patients with AML (median age, 57 years; range, 18-84 years) were stratified by CR1 or subsequent CR (CR > 1) and randomly assigned to treatment with HDC/IL-2 or no treatment (control). Treatment comprised 10 21-day cycles with IL-2 (16 400 U/kg) plus HDC (0.5 mg); both compounds were administered by subcutaneous injection twice daily. Study arms were balanced for age, sex, previous treatment, leukemic karyotypes, time from CR to inclusion, and frequency of secondary leukemia. Three years after enrollment of the last patient, treatment with HDC/IL-2 was found to improve LFS over control in the study population (CR1 + CR > 1, n = 320; P < .01, log-rank test). For patients in CR1 (n = 261), treatment significantly improved LFS (P = .01) with 3-year LFS estimates of 40% (HDC/IL-2) compared with 26% (control). Side effects were typically mild to moderate. These results indicate that HDC/IL-2 treatment offers an efficacious and tolerable treatment for patients with AML in remission.
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| 48. |
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| 49. |
- Buyse, Marc, et al.
(author)
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Assessment of the consistency and robustness of results from a multicenter trial of remission maintenance therapy for acute myeloid leukemia.
- 2011
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In: Trials. - : Springer Science and Business Media LLC. - 1745-6215. ; 12
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Journal article (peer-reviewed)abstract
- ABSTRACT: Background Data from a randomized multinational phase 3 trial of 320 adults with acute myeloid leukemia (AML) demonstrated that maintenance therapy with 3-week cycles of histamine dihydrochloride plus low-dose interleukin-2 (HDC/IL-2) for up to 18 months significantly improved leukemia-free survival (LFS) but lacked power to detect an overall survival (OS) difference. Purpose To assess the consistency of treatment benefit across patient subsets and the robustness of data with respect to trial centers and endpoints. Methods Forest plots were constructed with hazard ratios (HRs) of HDC/IL-2 treatment effects versus no treatment (control) for prospectively defined patient subsets. Inconsistency coefficients (I2) and interaction tests (X2) were used to detect any differences in benefit among subsets. Robustness of results to the elimination of individual study centers was performed using "leave-one-center-out" analyses. Associations between treatment effects on the endpoints were evaluated using weighted linear regression between HRs for LFS and OS estimated within countries. Results The benefit of HDC/IL-2 over controls was statistically consistent across all subsets defined by baseline prognostic variables. I2 and P-values of X2 ranged from 0.00 to 0.51 and 0.14 to 0.91, respectively. Treatment effects were statistically significant in 14 of 28 subsets analyzed. The "leave-one-center-out" analysis confirmed that no single center dominated (P-values ranged from 0.004 to 0.020 [mean 0.009]). The HRs representing the HDC/IL-2 effects on LFS and OS were strongly correlated at the country level (R2 = 0.84). Limitations Small sample sizes in some of the subsets analyzed. Conclusions These analyses confirm the consistency and robustness of the HDC/IL-2 effect as compared with no treatment. LFS may be an acceptable surrogate for OS in future AML trials. Analyses of consistency and robustness may aid interpretation of data from multicenter trials, especially in populations with rare diseases, when the size of randomized clinical trials is limited. Trial Registration ClinicalTrials.gov: NCT00003991
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| 50. |
- Buyse, M, et al.
(author)
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Leukemia-free survival as a surrogate end point for overall survival in the evaluation of maintenance therapy for patients with acute myeloid leukemia in complete remission
- 2011
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In: HAEMATOLOGICA-THE HEMATOLOGY JOURNAL. - : Ferrata Storti Foundation (Haematologica). - 0390-6078. ; 96:8, s. 1106-1112
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Journal article (peer-reviewed)abstract
- BACKGROUND: In trials designed to evaluate new therapies for hematologic malignancies, end points such as leukemia-free survival are often used as surrogates for overall survival in acute leukemia. We aimed to assess whether leukemia-free survival is an acceptable statistical surrogate for overall survival when applied to remission maintenance therapy for acute myeloid leukemia. DESIGN AND METHODS: Data were analyzed from a randomized Phase III trial of remission maintenance immunotherapy with histamine dihydrochloride plus low-dose interleukin-2 versus no treatment in adults with acute myeloid leukemia. A two-stage surrogate validation model was applied in which correlations between Kaplan-Meier estimates of leukemia-free survival and overall survival, and between log hazard ratios reflecting treatment effects were analyzed. Country of patient enrollment was the unit of analysis. RESULTS: Kaplan-Meier estimates of overall survival at 36, 48, and 60 months and leukemia-free survival at 24 months were reasonably correlated (R(2) ranging from 0.44 to 0.84) both for the overall (n=320) and first complete remission (n=261) populations. The effects of histamine dihydrochloride/interleukin-2 on log hazard ratios for leukemia-free survival and overall survival were well correlated (R(2)=0.88-0.93). CONCLUSIONS: The significant correlations between overall survival and the surrogate end point (leukemia-free survival) and between the effect of histamine dihydrochloride/interleukin-2 on leukemia-free survival and overall survival satisfy the two-stage surrogate validation model.
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