Recruitment of bone marrow derived cells during anti-angiogenic therapy in GBM:The potential of combination strategies

Glioblastoma (GBM) is a highly vascular tumor characterized by rapid and invasive tumor growth, followed by oxygen depletion, hypoxia and neovascularization, which generate a network of disorganized, tortuous and permeable vessels. Recruitment of bone marrow derived cells (BMDC) is crucial for vasculogenesis. These dells may act as vascular progenitors by integrating into the newly formed blood vessels or as vascular modulators by releasing pro-angiogenic factors. In patients with recurrent GBM, anti-vascular endothelial growth factor (VEGF) therapy has been evaluated in combination with chemotherapy, yielding improvements in progression-free survival (PFS). However, benefits are temporary as vascular tumors acquire angiogenic pathways independently of VEGF. Specifically, acute hypoxia following prolonged VEGF depletion induces the recruitment of certain myeloid cell subpopulations, which highly contribute to treatment refractoriness. Here we review the molecular mechanisms of neovascularization in relation to bevacizumab therapy with special emphasis on the recruitment of BMDCs and possible combination therapies for GBM patients. (C) 2014 Elsevier Ireland Ltd. All rights reserved

Social learning in multilevel flood risk governance: Lessons from the Dutch Room for the River Program

Although social learning is a key element of multilevel flood risk governance, it is hardly studied. This paper addresses this knowledge gap. The paper aims to identify enabling conditions for social learning in multilevel flood risks governance arrangements.We first conceptualize social learning and draw up a conceptual framework consisting of enabling conditions for social learning, using the literature on adaptive co-management, sustainable land and water management, and integrated flood risk management. Next, we apply this framework to analyze social learning in the context of the Dutch Room for the River program. Our interview results reveal that social learning about integrated flood protection measures took place at multiple levels. We found that a strong personal commitment to learning and mutual interpersonal trust in working groups are key conditions for successful social learning. Based on our analysis, we conclude with some recommendations for enhancing social learning processes in future flood protection programs

Including Limited Partners in the Diversity Jurisdiction Analysis

This paper presents the results of the Dynamic Pricing Challenge, held on the occasion of the 17th INFORMS Revenue Management and Pricing Section Conference on June 29–30, 2017 in Amsterdam, The Netherlands. For this challenge, participants submitted algorithms for pricing and demand learning of which the numerical performance was analyzed in simulated market environments. This allows consideration of market dynamics that are not analytically tractable or can not be empirically analyzed due to practical complications. Our findings implicate that the relative performance of algorithms varies substantially across different market dynamics, which confirms the intrinsic complexity of pricing and learning in the presence of competition

Practical free-start collision attacks on 76-step SHA-1

In this paper we analyze the security of the compression function of SHA-1 against collision attacks, or equivalently free-start collisions on the hash function. While a lot of work has been dedicated to the analysis of SHA-1 in the past decade, this is the first time that free-start collisions have been considered for this function. We exploit the additional freedom provided by this model by using a new start-from-the-middle approach in combination with improvements on the cryptanalysis tools that have been developed for SHA-1 in the recent years. This results in particular in better differential paths than the ones used for hash function collisions so far. Overall, our attack requires about $2^{50}$ evaluations of the compression function in order to compute a one-block free-start collision for a 76-step reduced version, which is so far the highest number of steps reached for a collision on the SHA-1 compression function. We have developed an efficient GPU framework for the highly branching code typical of a cryptanalytic collision attack and used it in an optimized implementation of our attack on recent GTX 970 GPUs. We report that a single cheap US\$ 350 GTX 970 is sufficient to find the collision in less than 5 days. This showcases how recent mainstream GPUs seem to be a good platform for expensive and even highly-branching cryptanalysis computations. Finally, our work should be taken as a reminder that cryptanalysis on SHA-1 continues to improve. This is yet another proof that the industry should quickly move away from using this function

Trauma mechanism and patient reported outcome in tibial plateau fractures with posterior involvement

Introduction: Posterior tibial plateau fractures (PTPF) have a high impact on functional outcome and the optimal treatment strategy is not well established. The goal of this study was to assess the relationship between trauma mechanism, fracture morphology and functional outcome in a large multicenter cohort and define possible strategies to improve the outcome. Methods: An international retrospective cohort study was conducted in five level-1 trauma centers. All consecutive operatively treated PTPF were evaluated. Preoperative imaging was reviewed to determine the trauma mechanism. Patient reported outcome was scored using the Knee injury and Osteoarthritis Outcome Score (KOOS). Results: A total of 145 tibial plateau fractures with posterior involvement were selected with a median follow-up of 32.2 months (IQR 24.1-43.2). Nine patients (6%) sustained an isolated posterior fracture. Seventy-two patients (49%) sustained a two-column fracture and three-column fractures were diagnosed in 64 (44%) patients. Varus trauma was associated with poorer outcome on the 'symptoms' (p = 0.004) and 'pain' subscales (p = 0.039). Delayed-staged surgery was associated with worse outcome scores for all subscales except 'pain'. In total, 27 patients (18%) were treated with posterior plate osteosynthesis without any significant difference in outcome. Conclusions: Fracture morphology, varus trauma mechanism and delayed-staged surgery (i.e. extensive soft-tissue injury) were identified as important prognostic factors on postoperative outcome in PTPF. In order to assess possible improvement of outcome, future studies with routine preoperative MRI to assess associated ligamentous injury in tibial plateau fractures (especially for varus trauma) are needed. (c) 2021 Elsevier B.V. All rights reserved

Deep learning-based recognition of key anatomical structures during robot-assisted minimally invasive esophagectomy

Objective: To develop a deep learning algorithm for anatomy recognition in thoracoscopic video frames from robot-assisted minimally invasive esophagectomy (RAMIE) procedures using deep learning. Background: RAMIE is a complex operation with substantial perioperative morbidity and a considerable learning curve. Automatic anatomy recognition may improve surgical orientation and recognition of anatomical structures and might contribute to reducing morbidity or learning curves. Studies regarding anatomy recognition in complex surgical procedures are currently lacking. Methods: Eighty-three videos of consecutive RAMIE procedures between 2018 and 2022 were retrospectively collected at University Medical Center Utrecht. A surgical PhD candidate and an expert surgeon annotated the azygos vein and vena cava, aorta, and right lung on 1050 thoracoscopic frames. 850 frames were used for training of a convolutional neural network (CNN) to segment the anatomical structures. The remaining 200 frames of the dataset were used for testing the CNN. The Dice and 95% Hausdorff distance (95HD) were calculated to assess algorithm accuracy. Results: The median Dice of the algorithm was 0.79 (IQR = 0.20) for segmentation of the azygos vein and/or vena cava. A median Dice coefficient of 0.74 (IQR = 0.86) and 0.89 (IQR = 0.30) were obtained for segmentation of the aorta and lung, respectively. Inference time was 0.026 s (39 Hz). The prediction of the deep learning algorithm was compared with the expert surgeon annotations, showing an accuracy measured in median Dice of 0.70 (IQR = 0.19), 0.88 (IQR = 0.07), and 0.90 (0.10) for the vena cava and/or azygos vein, aorta, and lung, respectively. Conclusion: This study shows that deep learning-based semantic segmentation has potential for anatomy recognition in RAMIE video frames. The inference time of the algorithm facilitated real-time anatomy recognition. Clinical applicability should be assessed in prospective clinical studies.</p

Improved stability regions for ground states of the extended Hubbard model

The ground state phase diagram of the extended Hubbard model containing nearest and next-to-nearest neighbor interactions is investigated in the thermodynamic limit using an exact method. It is found that taking into account local correlations and adding next-to-nearest neighbor interactions both have significant effects on the position of the phase boundaries. Improved stability domains for the $\eta$-pairing state and for the fully saturated ferromagnetic state at half filling have been constructed. The results show that these states are the ground states for model Hamiltonians with realistic values of the interaction parameters.Comment: 21 pages (10 figures are included) Revtex, revised version. To be published in Phys. Rev. B. E-mail: [email protected]

Targeted RNA-Sequencing Enables Detection of Relevant Translocations and Single Nucleotide Variants and Provides a Method for Classification of Hematological Malignancies-RANKING

BACKGROUND: Patients with hematological malignancies (HMs) carry a wide range of chromosomal and molecular abnormalities that impact their prognosis and treatment. Since no current technique can detect all relevant abnormalities, technique(s) are chosen depending on the reason for referral, and abnormalities can be missed. We tested targeted transcriptome sequencing as a single platform to detect all relevant abnormalities and compared it to current techniques. MATERIAL AND METHODS: We performed RNA-sequencing of 1385 genes (TruSight RNA Pan-Cancer, Illumina) in bone marrow from 136 patients with a primary diagnosis of HM. We then applied machine learning to expression profile data to perform leukemia classification, a method we named RANKING. Gene fusions for all the genes in the panel were detected, and overexpression of the genes EVI1, CCND1, and BCL2 was quantified. Single nucleotide variants/indels were analyzed in acute myeloid leukemia (AML), myelodysplastic syndrome and patients with acute lymphoblastic leukemia (ALL) using a virtual myeloid (54 genes) or lymphoid panel (72 genes). RESULTS: RANKING correctly predicted the leukemia classification of all AML and ALL samples and improved classification in 3 patients. Compared to current methods, only one variant was missed, c.2447A>T in KIT (RT-PCR at 10(-4)), and BCL2 overexpression was not seen due to a t(14; 18)(q32; q21) in 2% of the cells. Our RNA-sequencing method also identified 6 additional fusion genes and overexpression of CCND1 due to a t(11; 14)(q13; q32) in 2 samples. CONCLUSIONS: Our combination of targeted RNA-sequencing and data analysis workflow can improve the detection of relevant variants, and expression patterns can assist in establishing HM classification

Black Holes as Effective Geometries

Gravitational entropy arises in string theory via coarse graining over an underlying space of microstates. In this review we would like to address the question of how the classical black hole geometry itself arises as an effective or approximate description of a pure state, in a closed string theory, which semiclassical observers are unable to distinguish from the "naive" geometry. In cases with enough supersymmetry it has been possible to explicitly construct these microstates in spacetime, and understand how coarse-graining of non-singular, horizon-free objects can lead to an effective description as an extremal black hole. We discuss how these results arise for examples in Type II string theory on AdS_5 x S^5 and on AdS_3 x S^3 x T^4 that preserve 16 and 8 supercharges respectively. For such a picture of black holes as effective geometries to extend to cases with finite horizon area the scale of quantum effects in gravity would have to extend well beyond the vicinity of the singularities in the effective theory. By studying examples in M-theory on AdS_3 x S^2 x CY that preserve 4 supersymmetries we show how this can happen.Comment: Review based on lectures of JdB at CERN RTN Winter School and of VB at PIMS Summer School. 68 pages. Added reference