Convex Optimisation for Inverse Kinematics

We consider the problem of inverse kinematics (IK), where one wants to find the parameters of a given kinematic skeleton that best explain a set of observed 3D joint locations. The kinematic skeleton has a tree structure, where each node is a joint that has an associated geometric transformation that is propagated to all its child nodes. The IK problem has various applications in vision and graphics, for example for tracking or reconstructing articulated objects, such as human hands or bodies. Most commonly, the IK problem is tackled using local optimisation methods. A major downside of these approaches is that, due to the non-convex nature of the problem, such methods are prone to converge to unwanted local optima and therefore require a good initialisation. In this paper we propose a convex optimisation approach for the IK problem based on semidefinite programming, which admits a polynomial-time algorithm that globally solves (a relaxation of) the IK problem. Experimentally, we demonstrate that the proposed method significantly outperforms local optimisation methods using different real-world skeletons

HDSDF: Hybrid Directional and Signed Distance Functions for Fast Inverse Rendering

Implicit neural representations of 3D shapes form strong priors that areuseful for various applications, such as single and multiple view 3Dreconstruction. A downside of existing neural representations is that theyrequire multiple network evaluations for rendering, which leads to highcomputational costs. This limitation forms a bottleneck particularly in thecontext of inverse problems, such as image-based 3D reconstruction. To addressthis issue, in this paper (i) we propose a novel hybrid 3D objectrepresentation based on a signed distance function (SDF) that we augment with adirectional distance function (DDF), so that we can predict distances to theobject surface from any point on a sphere enclosing the object. Moreover, (ii)using the proposed hybrid representation we address the multi-view consistencyproblem common in existing DDF representations. We evaluate our novel hybridrepresentation on the task of single-view depth reconstruction and show thatour method is several times faster compared to competing methods, while at thesame time achieving better reconstruction accuracy.<br

i3DMM: Deep Implicit 3D Morphable Model of Human Heads

We present the first deep implicit 3D morphable model (i3DMM) of full heads. Unlike earlier morphable face models it not only captures identity-specific geometry, texture, and expressions of the frontal face, but also models the entire head, including hair. We collect a new dataset consisting of 64 people with different expressions and hairstyles to train i3DMM. Our approach has the following favorable properties: (i) It is the first full head morphable model that includes hair. (ii) In contrast to mesh-based models it can be trained on merely rigidly aligned scans, without requiring difficult non-rigid registration. (iii) We design a novel architecture to decouple the shape model into an implicit reference shape and a deformation of this reference shape. With that, dense correspondences between shapes can be learned implicitly. (iv) This architecture allows us to semantically disentangle the geometry and color components, as color is learned in the reference space. Geometry is further disentangled as identity, expressions, and hairstyle, while color is disentangled as identity and hairstyle components. We show the merits of i3DMM using ablation studies, comparisons to state-of-the-art models, and applications such as semantic head editing and texture transfer. We will make our model publicly available

Assessing copy number aberrations and copy neutral loss of heterozygosity across the genome as best practice: An evidence based review of clinical utility from the cancer genomics consortium (CGC) working group for myelodysplastic syndrome, myelodysplastic/myeloproliferative and myeloproliferative neoplasms

Multiple studies have demonstrated the utility of chromosomal microarray (CMA) testing to identify clinically significant copy number alterations (CNAs) and copy-neutral loss-of-heterozygosity (CN-LOH) in myeloid malignancies. However, guidelines for integrating CMA as a standard practice for diagnostic evaluation, assessment of prognosis and predicting treatment response are still lacking. CMA has not been recommended for clinical work-up of myeloid malignancies by the WHO 2016 or the NCCN 2017 guidelines but is a suggested test by the European LeukaemiaNet 2013 for the diagnosis of primary myelodysplastic syndrome (MDS). The Cancer Genomics Consortium (CGC) Working Group for Myeloid Neoplasms systematically reviewed peer-reviewed literature to determine the power of CMA in (1) improving diagnostic yield, (2) refining risk stratification, and (3) providing additional genomic information to guide therapy. In this manuscript, we summarize the evidence base for the clinical utility of array testing in the workup of MDS, myelodysplastic/myeloproliferative neoplasms (MDS/MPN) and myeloproliferative neoplasms (MPN). This review provides a list of recurrent CNAs and CN-LOH noted in this disease spectrum and describes the clinical significance of the aberrations and how they complement gene mutation findings by sequencing. Furthermore, for new or suspected diagnosis of MDS or MPN, we present suggestions for integrating genomic testing methods (CMA and mutation testing by next generation sequencing) into the current standard-of-care clinical laboratory testing (karyotype, FISH, morphology, and flow)

Assessing copy number abnormalities and copy-neutral loss-of-heterozygosity across the genome as best practice in diagnostic evaluation of acute myeloid leukemia: An evidence-based review from the cancer genomics consortium (CGC) myeloid neoplasms working group

Structural genomic abnormalities, including balanced chromosomal rearrangements, copy number gains and losses and copy-neutral loss-of-heterozygosity (CN-LOH) represent an important category of diagnostic, prognostic and therapeutic markers in acute myeloid leukemia (AML). Genome-wide evaluation for copy number abnormalities (CNAs) is at present performed by karyotype analysis which has low resolution and is unobtainable in a subset of cases. Furthermore, examination for possible CN-LOH in leukemia cells is at present not routinely performed in the clinical setting. Chromosomal microarray (CMA) analysis is a widely available assay for CNAs and CN-LOH in diagnostic laboratories, but there are currently no guidelines how to best incorporate this technology into clinical testing algorithms for neoplastic diseases including AML. The Cancer Genomics Consortium Working Group for Myeloid Neoplasms performed an extensive review of peer-reviewed publications focused on CMA analysis in AML. Here we summarize evidence regarding clinical utility of CMA analysis in AML extracted from published data, and provide recommendations for optimal utilization of CMA testing in the diagnostic workup. In addition, we provide a list of CNAs and CN-LOH regions which have documented clinical significance in diagnosis, prognosis and treatment decisions in AML

High Mutability of the Tumor Suppressor Genes RASSF1 and RBSP3 (CTDSPL) in Cancer

BACKGROUND:Many different genetic alterations are observed in cancer cells. Individual cancer genes display point mutations such as base changes, insertions and deletions that initiate and promote cancer growth and spread. Somatic hypermutation is a powerful mechanism for generation of different mutations. It was shown previously that somatic hypermutability of proto-oncogenes can induce development of lymphomas. METHODOLOGY/PRINCIPAL FINDINGS:We found an exceptionally high incidence of single-base mutations in the tumor suppressor genes RASSF1 and RBSP3 (CTDSPL) both located in 3p21.3 regions, LUCA and AP20 respectively. These regions contain clusters of tumor suppressor genes involved in multiple cancer types such as lung, kidney, breast, cervical, head and neck, nasopharyngeal, prostate and other carcinomas. Altogether in 144 sequenced RASSF1A clones (exons 1-2), 129 mutations were detected (mutation frequency, MF = 0.23 per 100 bp) and in 98 clones of exons 3-5 we found 146 mutations (MF = 0.29). In 85 sequenced RBSP3 clones, 89 mutations were found (MF = 0.10). The mutations were not cytidine-specific, as would be expected from alterations generated by AID/APOBEC family enzymes, and appeared de novo during cell proliferation. They diminished the ability of corresponding transgenes to suppress cell and tumor growth implying a loss of function. These high levels of somatic mutations were found both in cancer biopsies and cancer cell lines. CONCLUSIONS/SIGNIFICANCE:This is the first report of high frequencies of somatic mutations in RASSF1 and RBSP3 in different cancers suggesting it may underlay the mutator phenotype of cancer. Somatic hypermutations in tumor suppressor genes involved in major human malignancies offer a novel insight in cancer development, progression and spread

Convex Optimisation for Inverse Kinematics

We consider the problem of inverse kinematics (IK), where one wants to find the parameters of a given kinematic skeleton that best explain a set of observed 3D joint locations. The kinematic skeleton has a tree structure, where each node is a joint that has an associated geometric transformation that is propagated to all its child nodes. The IK problem has various applications in vision and graphics, for example for tracking or reconstructing articulated objects, such as human hands or bodies. Most commonly, the IK problem is tackled using local optimisation methods. A major downside of these approaches is that, due to the non-convex nature of the problem, such methods are prone to converge to unwanted local optima and therefore require a good initialisation. In this paper we propose a convex optimisation approach for the IK problem based on semidefinite programming, which admits a polynomial-time algorithm that globally solves (a relaxation of) the IK problem. Experimentally, we demonstrate that the proposed method significantly outperforms local optimisation methods using different real-world skeletons

Epstein-Barr virus encoded EBNA-3 binds to vitamin D receptor and blocks activation of its target genes.

Epstein-Barr virus (EBV) is a human gamma herpes virus that infects B cells and induces their transformation into immortalized lymphoblasts that can grow as cell lines (LCLs) in vitro. EBNA-3 is a member of the EBNA-3-protein family that can regulate transcription of cellular and viral genes. The identification of EBNA-3 cellular partners and a study of its influence on cellular pathways are important for understanding the transforming action of the virus. In this work, we have identified the vitamin D receptor (VDR) protein as a binding partner of EBNA-3. We found that EBNA3 blocks the activation of VDR-dependent genes and protects LCLs against vitamin-D3-induced growth arrest and/or apoptosis. The presented data shed some light on the anti-apoptotic EBV program and the role of the EBNA-3-VDR interaction in the viral strategy