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- Alarcón Cuevas, Alvaro, 1991-
(author)
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A Few-Mode-Fiber Platform for Quantum Communication Applications
- 2022
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Licentiate thesis (other academic/artistic)abstract
- Society as we know it today would not have been possible without the explosive and astonishing development of telecommunications systems, and optical fibers have been one of the pillars of these technologies.Despite the enormous amount of data being transmitted over optical networks today, the trend is that the demand for higher bandwidths will also increase. Given this context, a central element in the design of telecommunications networks will be data security, since information can often be confidential or private.Quantum information emerges as a solution to encrypt data by quantum key distribution (QKD) between two users. This technique uses the properties of nature as the fundamentals of operation rather than relying on mathematical constructs to provide data protection. A popular alternative to performing QKD is to use the relative phase between two individual photon paths for information encoding. However, this method was not practical over long distances. The time-bin- based scheme was a solution to the previous problem given its practical nature, however, it introduces intrinsic losses due to its design, which increases with the dimension of the encoded quantum system.In this thesis we have designed and tested a fiber-optic platform using spatial-division- multiplexing techniques. The use of few-mode fibers and photonic lanterns are the cornerstone of our proposal, which also allow us to support orbital angular momentum (OAM) modes. The platform builds on the core ideas of the phase-coded quantum communication system and also takes advantage of the benefits proposed by the time-bin scheme. We have experimentally tested our proposal by successfully transmitting phase-coded single-photon states over 500 m few-mode fiber, demonstrating the feasibility of our scheme. We demonstrated the successful creation of OAM states, their propagation and their successful detection in an all in-fiber scheme. Our platform eliminates the post-selection losses of time-bin quantum communication systems and ensures compatibility with next-generation optical networks and opens up new possibilities for quantum communication.
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2. |
- Andersson, Alma, et al.
(author)
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Spatial deconvolution of HER2-positive breast cancer delineates tumor-associated cell type interactions
- 2021
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In: Nature Communications. - : Springer Nature. - 2041-1723. ; 12:1
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Journal article (peer-reviewed)abstract
- In the past decades, transcriptomic studies have revolutionized cancer treatment and diagnosis. However, tumor sequencing strategies typically result in loss of spatial information, critical to understand cell interactions and their functional relevance. To address this, we investigate spatial gene expression in HER2-positive breast tumors using Spatial Transcriptomics technology. We show that expression-based clustering enables data-driven tumor annotation and assessment of intra- and interpatient heterogeneity; from which we discover shared gene signatures for immune and tumor processes. By integration with single cell data, we spatially map tumor-associated cell types to find tertiary lymphoid-like structures, and a type I interferon response overlapping with regions of T-cell and macrophage subset colocalization. We construct a predictive model to infer presence of tertiary lymphoid-like structures, applicable across tissue types and technical platforms. Taken together, we combine different data modalities to define a high resolution map of cellular interactions in tumors and provide tools generalizing across tissues and diseases. While transcriptomics have enhanced our understanding for cancer, spatial transcriptomics enable the characterisation of cellular interactions. Here, the authors integrate single cell data with spatial information for HER2 + tumours and develop tools for the prediction of interactions between tumour-infiltrating cells.
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3. |
- Andersson, Alma, et al.
(author)
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Spatial Deconvolution of HER2-positive Breast Tumors Reveals Novel Intercellular Relationships
- 2020
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Other publication (other academic/artistic)abstract
- In the past decades, transcriptomic studies have revolutionized cancer treatment and diagnosis. However, tumor sequencing strategies typically result in loss of spatial information, critical to understand cell interactions and their functional relevance. To address this, we investigate spatial gene expression in HER2-positive breast tumors using Spatial Transcriptomics technology. We show that expression-based clustering enables data-driven tumor annotation and assessment of intra-and interpatient heterogeneity; from which we discover shared gene signatures for immune and tumor processes. We integrate and spatially map tumor-associated types from single cell data to find: segregated epithelial cells, interactions between B and T-cells and myeloid cells, co-localization of macrophage and T-cell subsets. A model is constructed to infer presence of tertiary lymphoid structures, applicable across tissue types and technical platforms. Taken together, we combine different data modalities to define novel interactions between tumor-infiltrating cells in breast cancer and provide tools generalizing across tissues and diseases.
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4. |
- Andersson Svärd, Agnes, et al.
(author)
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Decreased HLA-DQ expression on peripheral blood cells in children with varying number of beta cell autoantibodies
- 2020
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In: Journal of Translational Autoimmunity. - : Elsevier BV. - 2589-9090. ; 3
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Journal article (peer-reviewed)abstract
- The risk for type 1 diabetes is strongly associated with HLA-DQ and the appearance of beta cell autoantibodies against either insulin, glutamate decarboxylase (GAD65), insulinoma-associated protein-2 (IA-2), or zinc transporter 8 (ZnT8). Prolonged exposure to autoantibodies may be related to T cell exhaustion known to occur in chronic infections or autoimmune disorders. It was hypothesized that autoantibody exposure may affect HLA-DQ expression on peripheral blood cells and thereby contribute to T cell exhaustion thought to be associated with the pathogenesis of type 1 diabetes. The aim of this study was to determine whether autoantibody exposure as an expression of autoimmunity burden was related to peripheral blood cell HLA-DQ cell surface expression in either 1) a cross-sectional analysis or 2) cumulative as area under the trajectory of autoantibodies during long term follow-up in the Diabetes Prediction in Skåne (DiPiS) study. Children (n = 67), aged 10-15 years were analyzed for complete blood count, HLA-DQ cell surface median fluorescence intensity (MFI), autoantibody frequency, and HLA genotypes by Next Generation Sequencing. Decreased HLA-DQ cell surface MFI with an increasing number of autoantibodies was observed in CD16+, CD14+CD16-, CD4+ and CD8+ cells but not in CD19+ cells and neutrophils. HLA-DQ cell surface MFI was associated with HLA-DQ2/8 in CD4+ T cells, marginally in CD14+CD16- monocytes and CD8+ T cells. These associations appeared to be related to autoimmunity burden. The results suggest that HLA-DQ cell surface expression was related to HLA and autoimmunity burden.
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5. |
- Aquilante, Francesco, et al.
(author)
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Modern quantum chemistry with [Open]Molcas
- 2020
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In: Journal of Chemical Physics. - : AIP Publishing. - 0021-9606 .- 1089-7690. ; 152:21
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Journal article (peer-reviewed)abstract
- MOLCAS/OpenMolcas is an ab initio electronic structure program providing a large set of computational methods from Hartree-Fock and density functional theory to various implementations of multiconfigurational theory. This article provides a comprehensive overview of the main features of the code, specifically reviewing the use of the code in previously reported chemical applications as well as more recent applications including the calculation of magnetic properties from optimized density matrix renormalization group wave functions.
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7. |
- Brueffer, Christian, et al.
(author)
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The Mutational Landscape of the SCAN-B Real-World Primary Breast Cancer Transcriptome
- 2020
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Other publication (other academic/artistic)abstract
- Breast cancer is a disease of genomic alterations, of which the complete panorama of somatic mutations and how these relate to molecular subtypes and therapy response is incompletely understood. Within the Sweden Cancerome Analysis Network–Breast project (SCAN-B; ClinicalTrials.govNCT02306096), an ongoing study elucidating the tumor transcriptomic profiles for thousands of breast cancers prospectively, we developed an optimized pipeline for detection of single nucleotide variants and small insertions and deletions from RNA sequencing (RNA-seq) data, and profiled a large real-world population-based cohort of 3,217 breast tumors. We use it to describe the mutational landscape of primary breast cancer viewed through the transcriptome of a large population-based cohort of patients, and relate it to patient overall survival. We demonstrate that RNA-seq can be used to call mutations in important breast cancer genes such asPIK3CA,TP53, andERBB2, as well as the status of key molecular pathways and tumor mutational burden, and identify potentially druggable genes in 86.8% percent of tumors. To make this rich and growing mutational portraiture of breast cancer available for the wider research community, we developed an open source web-based application, the SCAN-B MutationExplorer, accessible athttp://oncogenomics.bmc.lu.se/MutationExplorer. These results add another dimension to the use of RNA-seq as a potential clinical tool, where both gene expression-based and gene mutation-based biomarkers can be interrogated simultaneously and in real-time within one week of tumor sampling.
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8. |
- Brueffer, Christian, et al.
(author)
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The mutational landscape of the SCAN‐B real‐world primary breast cancer transcriptome
- 2020
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In: EMBO Molecular Medicine. - : EMBO. - 1757-4684 .- 1757-4676. ; 12:10
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Journal article (peer-reviewed)abstract
- Breast cancer is a disease of genomic alterations, of which the panorama of somatic mutations and how these relate to subtypes and therapy response is incompletely understood. Within SCAN‐B (ClinicalTrials.gov: NCT02306096), a prospective study elucidating the transcriptomic profiles for thousands of breast cancers, we developed a RNA‐seq pipeline for detection of SNVs/indels and profiled a real‐world cohort of 3,217 breast tumors. We describe the mutational landscape of primary breast cancer viewed through the transcriptome of a large population‐based cohort and relate it to patient survival. We demonstrate that RNA‐seq can be used to call mutations in genes such as PIK3CA, TP53, and ERBB2, as well as the status of molecular pathways and mutational burden, and identify potentially druggable mutations in 86.8% of tumors. To make this rich dataset available for the research community, we developed an open source web application, the SCAN‐B MutationExplorer (http://oncogenomics.bmc.lu.se/MutationExplorer). These results add another dimension to the use of RNA‐seq as a clinical tool, where both gene expression‐ and mutation‐based biomarkers can be interrogated in real‐time within 1 week of tumor sampling.
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9. |
- Budroni, Costantino, et al.
(author)
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Kochen-Specker contextuality
- 2022
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In: Reviews of Modern Physics. - : AMER PHYSICAL SOC. - 0034-6861 .- 1539-0756. ; 94:4
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Research review (peer-reviewed)abstract
- A central result in the foundations of quantum mechanics is the Kochen-Specker theorem. In short, it states that quantum mechanics is in conflict with classical models in which the result of a measurement does not depend on which other compatible measurements are jointly performed. Here compatible measurements are those that can be implemented simultaneously or, more generally, those that are jointly measurable. This conflict is generically called quantum contextuality. In this review, an introduction to this subject and its current status is presented. Several proofs of the Kochen-Specker theorem and different notions of contextuality are reviewed. How to experimentally test some of these notions is explained, and connections between contextuality and nonlocality or graph theory are discussed. Finally, some applications of contextuality in quantum information processing are reviewed.
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10. |
- Campbell, PJ, et al.
(author)
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Pan-cancer analysis of whole genomes
- 2020
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In: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 578:7793, s. 82-
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Journal article (peer-reviewed)abstract
- Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1–3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10–18.
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