Low-Dose Aronia melanocarpa

Herbicides containing paraquat may contribute to the pathogenesis of neurodegenerative disorders such as Parkinson’s disease. Paraquat induces reactive oxygen species-mediated apoptosis in neurons, which is a primary mechanism behind its toxicity. We sought to test the effectiveness of a commercially available polyphenol-rich Aronia melanocarpa (aronia berry) concentrate in the amelioration of paraquat-induced neurotoxicity. Considering the abundance of antioxidants in aronia berries, we hypothesized that aronia berry concentrate attenuates the paraquat-induced increase in reactive oxygen species and protects against paraquat-mediated neuronal cell death. Using a neuronal cell culture model, we observed that low doses of aronia berry concentrate protected against paraquat-mediated neurotoxicity. Additionally, low doses of the concentrate attenuated the paraquat-induced increase in superoxide, hydrogen peroxide, and oxidized glutathione levels. Interestingly, high doses of aronia berry concentrate increased neuronal superoxide levels independent of paraquat, while at the same time decreasing hydrogen peroxide. Moreover, high-dose aronia berry concentrate potentiated paraquat-induced superoxide production and neuronal cell death. In summary, aronia berry concentrate at low doses restores the homeostatic redox environment of neurons treated with paraquat, while high doses exacerbate the imbalance leading to further cell death. Our findings support that moderate levels of aronia berry concentrate may prevent reactive oxygen species-mediated neurotoxicity

LIGHTNESS: a function-virtualizable software defined data center network with all-optical circuit/packet switching

©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Modern high-performance data centers are responsible for delivering a huge variety of cloud applications to the end-users, which are increasingly pushing the limits of the currently deployed computing and network infrastructure. All-optical dynamic data center network (DCN) architectures are strong candidates to overcome those adversities, especially when they are combined with an intelligent software defined control plane. In this paper, we report the first harmonious integration of an optical flexible hardware framework operated by an agile software and virtualization platform. The LIGHTNESS deeply programmable all-optical circuit and packet switched data plane is able to perform unicast/multicast switch-over on-demand, while the powerful software defined networking (SDN) control plane enables the virtualization of computing and network resources creating a virtual data center and virtual network functions (VNF) on top of the data plane. We experimentally demonstrate realistic intra DCN with deterministic latencies for both unicast and multicast, showcasing monitoring, and database migration scenarios each of which is enabled by an associated network function virtualization element. Results demonstrate a fully functional complete unification of an advanced optical data plane with an SDN control plane, promising more efficient management of the next-generation data center compute and network resources.Peer ReviewedPostprint (author's final draft

CD133-directed CAR T-cells for MLL Leukemia: On-Target, Off-Tumor Myeloablative Toxicity

Acknowledgements: We thank the Interfant treatment protocol and local physicians for contributing patient samples: Dr. Ronald W Stam (Princess Maxima Centre, Utrech), Dr. Mireia Camos and Dr. Jose Luis Fuster (Spanish Society of Pediatric Hematoncology), Dr. Paola Ballerini (A. Trousseau Hospital, Paris). We also thank Prof. Paresh Vyas (Oxford Univeristy, UK) and Prof. Kajsa Paulsson (Lund University, Sweden) for facilitating access to their RNA-seq database. This work has been supported by the European Research Council (CoG-2014-646903, PoC-2018-811220) to PM, the Spanish Ministry of Economy and Competitiveness (MINECO, SAF-SAF2016-80481-R, BIO2017-85364-R) to PM and EE, the Generalitat de Catalunya (SGR330, SGR102 and PERIS) to PM and EE, the Spanish Association against cancer (AECC-CI-2015) to CB, and the Health Institute Carlos III (ISCIII/FEDER, PI14-01191) to CB. PM also acknowledges financial support from the Obra Social La Caixa-Fundaciò Josep Carreras. SRZ and TV are supported by a Marie Curie fellowships. OM is supported by the Catalan Government through a Beatriu de Pinos fellowship. MB is supported by MINECO through a PhD scholarship. PM is an investigator of the Spanish Cell Therapy cooperative network (TERCEL)

Liver biopsy-based validation, confirmation and comparison of the diagnostic performance of established and novel non-invasive non-alcoholic fatty liver disease indexes:Results from a large multi-center study

Background: Non-invasive tools (NIT) for non-alcoholic fatty liver disease (NAFLD) screening or diagnosis need to be thoroughly validated using liver biopsies.Purpose: To externally validate NITs designed to differentiate the presence or absence of liver steatosis as well as more advanced disease stages, to confirm fully validated indexes (n = 7 NITs), to fully validate partially validated indexes (n = 5 NITs), and to validate for the first time one new index (n = 1 NIT).Methods: This is a multi-center study from two Gastroenterology-Hepatology Departments (Greece and Australia) and one Bariatric-Metabolic Surgery Department (Italy). Overall, n = 455 serum samples of patients with biopsy-proven NAFLD (n = 374, including 237 patients with non-alcoholic steatohepatitis (NASH)) and Controls (n = 81) were recruited. A complete validation analysis was performed to differentiate the presence of NAFLD vs. Controls, NASH vs. NAFL, histological features of NASH, and fibrosis stages.Results: The index of NASH (ION) demonstrated the highest differentiation ability for the presence of NAFLD vs. Controls, with the area under the curve (AUC) being 0.894. For specific histological characterization of NASH, no NIT demonstrated adequate performance, while in the case of specific features of NASH, such as hepatocellular ballooning and lobular inflammation, ION demonstrated the best performance with AUC being close to or above 0.850. For fibrosis (F) classification, the highest AUC was reached by the aspartate aminotransferase to platelet ratio index (APRI) being ~0.850 yet only with the potential to differentiate the severe fibrosis stages (F3, F4) vs. mild or moderate fibrosis (F0–2) with an AUC > 0.900 in patients without T2DM. When we excluded patients with morbid obesity, the differentiation ability of APRI was improved, reaching AUC = 0.802 for differentiating the presence of fibrosis F2–4 vs. F0–1. The recommended by current guidelines index FIB-4 seemed to differentiate adequately between severe (i.e., F3–4) and mild or moderate fibrosis (F0–2) with an AUC = 0.820, yet this was not the case when FIB-4 was used to classify patients with fibrosis F2–4 vs. F0–1. Trying to improve the predictive value of all NITs, using Youden's methodology, to optimize the suggested cut-off points did not materially improve the results.Conclusions: The validation of currently available NITs using biopsy-proven samples provides new evidence for their ability to differentiate between specific disease stages, histological features, and, most importantly, fibrosis grading. The overall performance of the examined NITs needs to be further improved for applications in the clinic

Liver biopsy-based validation, confirmation and comparison of the diagnostic performance of established and novel non-invasive non-alcoholic fatty liver disease indexes:Results from a large multi-center study

Background: Non-invasive tools (NIT) for non-alcoholic fatty liver disease (NAFLD) screening or diagnosis need to be thoroughly validated using liver biopsies.Purpose: To externally validate NITs designed to differentiate the presence or absence of liver steatosis as well as more advanced disease stages, to confirm fully validated indexes (n = 7 NITs), to fully validate partially validated indexes (n = 5 NITs), and to validate for the first time one new index (n = 1 NIT).Methods: This is a multi-center study from two Gastroenterology-Hepatology Departments (Greece and Australia) and one Bariatric-Metabolic Surgery Department (Italy). Overall, n = 455 serum samples of patients with biopsy-proven NAFLD (n = 374, including 237 patients with non-alcoholic steatohepatitis (NASH)) and Controls (n = 81) were recruited. A complete validation analysis was performed to differentiate the presence of NAFLD vs. Controls, NASH vs. NAFL, histological features of NASH, and fibrosis stages.Results: The index of NASH (ION) demonstrated the highest differentiation ability for the presence of NAFLD vs. Controls, with the area under the curve (AUC) being 0.894. For specific histological characterization of NASH, no NIT demonstrated adequate performance, while in the case of specific features of NASH, such as hepatocellular ballooning and lobular inflammation, ION demonstrated the best performance with AUC being close to or above 0.850. For fibrosis (F) classification, the highest AUC was reached by the aspartate aminotransferase to platelet ratio index (APRI) being ~0.850 yet only with the potential to differentiate the severe fibrosis stages (F3, F4) vs. mild or moderate fibrosis (F0–2) with an AUC > 0.900 in patients without T2DM. When we excluded patients with morbid obesity, the differentiation ability of APRI was improved, reaching AUC = 0.802 for differentiating the presence of fibrosis F2–4 vs. F0–1. The recommended by current guidelines index FIB-4 seemed to differentiate adequately between severe (i.e., F3–4) and mild or moderate fibrosis (F0–2) with an AUC = 0.820, yet this was not the case when FIB-4 was used to classify patients with fibrosis F2–4 vs. F0–1. Trying to improve the predictive value of all NITs, using Youden's methodology, to optimize the suggested cut-off points did not materially improve the results.Conclusions: The validation of currently available NITs using biopsy-proven samples provides new evidence for their ability to differentiate between specific disease stages, histological features, and, most importantly, fibrosis grading. The overall performance of the examined NITs needs to be further improved for applications in the clinic

Liver biopsy-based validation, confirmation and comparison of the diagnostic performance of established and novel non-invasive non-alcoholic fatty liver disease indexes:Results from a large multi-center study

Background: Non-invasive tools (NIT) for non-alcoholic fatty liver disease (NAFLD) screening or diagnosis need to be thoroughly validated using liver biopsies.Purpose: To externally validate NITs designed to differentiate the presence or absence of liver steatosis as well as more advanced disease stages, to confirm fully validated indexes (n = 7 NITs), to fully validate partially validated indexes (n = 5 NITs), and to validate for the first time one new index (n = 1 NIT).Methods: This is a multi-center study from two Gastroenterology-Hepatology Departments (Greece and Australia) and one Bariatric-Metabolic Surgery Department (Italy). Overall, n = 455 serum samples of patients with biopsy-proven NAFLD (n = 374, including 237 patients with non-alcoholic steatohepatitis (NASH)) and Controls (n = 81) were recruited. A complete validation analysis was performed to differentiate the presence of NAFLD vs. Controls, NASH vs. NAFL, histological features of NASH, and fibrosis stages.Results: The index of NASH (ION) demonstrated the highest differentiation ability for the presence of NAFLD vs. Controls, with the area under the curve (AUC) being 0.894. For specific histological characterization of NASH, no NIT demonstrated adequate performance, while in the case of specific features of NASH, such as hepatocellular ballooning and lobular inflammation, ION demonstrated the best performance with AUC being close to or above 0.850. For fibrosis (F) classification, the highest AUC was reached by the aspartate aminotransferase to platelet ratio index (APRI) being ~0.850 yet only with the potential to differentiate the severe fibrosis stages (F3, F4) vs. mild or moderate fibrosis (F0–2) with an AUC > 0.900 in patients without T2DM. When we excluded patients with morbid obesity, the differentiation ability of APRI was improved, reaching AUC = 0.802 for differentiating the presence of fibrosis F2–4 vs. F0–1. The recommended by current guidelines index FIB-4 seemed to differentiate adequately between severe (i.e., F3–4) and mild or moderate fibrosis (F0–2) with an AUC = 0.820, yet this was not the case when FIB-4 was used to classify patients with fibrosis F2–4 vs. F0–1. Trying to improve the predictive value of all NITs, using Youden's methodology, to optimize the suggested cut-off points did not materially improve the results.Conclusions: The validation of currently available NITs using biopsy-proven samples provides new evidence for their ability to differentiate between specific disease stages, histological features, and, most importantly, fibrosis grading. The overall performance of the examined NITs needs to be further improved for applications in the clinic

PO-315 The mutational and transcriptome landscape of infant B-cell acute lymphoblastic leukaemia: the INTERFANT treatment protocol experience

Introduction Infant B-cell precursor acute lymphoblastic leukaemia (iBCP-ALL) has dismal prognosis, especially with MLLgene rearrangements (MLLr) which are hallmark clonal leukemogenic drivers. Molecular pathogenesis of MLLr-iBCP-ALL remain somehow enigmatic and in vivo recreation of MLLriBCP-ALL is challenging. Material and methods We performed whole-genome, exome, targetted and RNA-sequencing on an Interfant study discovery cohort of 50 iBCP-ALLs (27MLL-AF4+, including relapses, 5MLL-AF9+and 10non-MLL). An independent validation cohort of 82iBCP-ALLs (43MLL-AF4+, 11MLL-AF9+, and 28non-MLL) was used for targeted DNA-sequencing/qRT-PCR. Results and discussions iBCP-ALL shows an extremely low frequency of somatic mutations, irrespective of the presence/subtype of MLLr, with the predominant leukemic clone carrying a mean of 2.5 non-silent mutations. Recurrent mutations were exclusively found in KRAS and NRAS, which were more frequent in the MLL-AF4+than in MLL-AF9+/non-MLL iBCPALL due to common NRAS mutations found in MLL-AF4 +infants (32% vs 6%; p Conclusion iBCP-ALL shows a silent mutational landscape regardless the MLL status. The expression of AF4-MLL associates to a better prognosis and specific upregulation of HOXA cluster genes. A pre-BCR early progenitor/stem cell may represent the cell-of-origin for both the t(4;11) and RAS mutations

Development Refractoriness of MLL-Rearranged Human B Cell Acute Leukemias to Reprogramming into Pluripotency

Induced pluripotent stem cells (iPSCs) are a powerful tool for disease modeling. They are routinely generated from healthy donors and patients from multiple cell types at different developmental stages. However, reprogramming leukemias is an extremely inefficient process. Few studies generated iPSCs from primary chronic myeloid leukemias, but iPSC generation from acute myeloid or lymphoid leukemias (ALL) has not been achieved. We attempted to generate iPSCs from different subtypes of B-ALL to address the developmental impact of leukemic fusion genes. OKSM(L)-expressing mono/polycistronic-, retroviral/lentiviral/episomal-, and Sendai virus vector-based reprogramming strategies failed to render iPSCs in vitro and in vivo. Addition of transcriptomic-epigenetic reprogramming ‘‘boosters’’ also failed to generate iPSCs from B cell blasts and B-ALL lines, and when iPSCs emerged they lacked leukemic fusion genes, demonstrating non-leukemic myeloid origin. Conversely, MLL-AF4-overexpressing hematopoietic stem cells/B progenitors were successfully reprogrammed, indicating that B cell origin and leukemic fusion gene were not reprogramming barriers. Global transcriptome/DNA methylome profiling suggested a developmental/differentiation refractoriness of MLL-rearranged B-ALL to reprogramming into pluripotency

GaNDLF: A Generally Nuanced Deep Learning Framework for Scalable End-to-End Clinical Workflows in Medical Imaging

Deep Learning (DL) has greatly highlighted the potential impact of optimized machine learning in both the scientific and clinical communities. The advent of open-source DL libraries from major industrial entities, such as TensorFlow (Google), PyTorch (Facebook), and MXNet (Apache), further contributes to DL promises on the democratization of computational analytics. However, increased technical and specialized background is required to develop DL algorithms, and the variability of implementation details hinders their reproducibility. Towards lowering the barrier and making the mechanism of DL development, training, and inference more stable, reproducible, and scalable, without requiring an extensive technical background, this manuscript proposes the Generally Nuanced Deep Learning Framework (GaNDLF). With built-in support for k-fold cross-validation, data augmentation, multiple modalities and output classes, and multi-GPU training, as well as the ability to work with both radiographic and histologic imaging, GaNDLF aims to provide an end-to-end solution for all DL-related tasks, to tackle problems in medical imaging and provide a robust application framework for deployment in clinical workflows