A Parametric Simplicial Formulation of Houthakker\u27s Capacity Method

The paper reformulates Houthakker’s capacity method for quadratic programming in the framework of the Simplex and dual methods for quadratic programming, thereby greatly reducing the conceptual and computational complexities of the method. It is shown that the method is applicable for all convex quadratic programming problems, including the case of a semi-definite matrix of the quadratic form and that of constraints in equality form. The method reduces in the linear programming case to a parametric version of the dual method

Hierarchical Planning and Control for Box Loco-Manipulation

Humans perform everyday tasks using a combination of locomotion and manipulation skills. Building a system that can handle both skills is essential to creating virtual humans. We present a physically-simulated human capable of solving box rearrangement tasks, which requires a combination of both skills. We propose a hierarchical control architecture, where each level solves the task at a different level of abstraction, and the result is a physics-based simulated virtual human capable of rearranging boxes in a cluttered environment. The control architecture integrates a planner, diffusion models, and physics-based motion imitation of sparse motion clips using deep reinforcement learning. Boxes can vary in size, weight, shape, and placement height. Code and trained control policies are provided

Learning Task-Agnostic Action Spaces for Movement Optimization

We propose a novel method for exploring the dynamics of physically based animated characters, and learning a task-agnostic action space that makes movement optimization easier. Like several previous papers, we parameterize actions as target states, and learn a short-horizon goal-conditioned low-level control policy that drives the agent's state towards the targets. Our novel contribution is that with our exploration data, we are able to learn the low-level policy in a generic manner and without any reference movement data. Trained once for each agent or simulation environment, the policy improves the efficiency of optimizing both trajectories and high-level policies across multiple tasks and optimization algorithms. We also contribute novel visualizations that show how using target states as actions makes optimized trajectories more robust to disturbances; this manifests as wider optima that are easy to find. Due to its simplicity and generality, our proposed approach should provide a building block that can improve a large variety of movement optimization methods and applications.Comment: Accepted as a regular paper by IEEE Transactions on Visualization and Computer Graphics (TVCG) in July 202

Linear Bellman combination for control of character animation

Controllers are necessary for physically-based synthesis of character animation. However, creating controllers requires either manual tuning or expensive computer optimization. We introduce linear Bellman combination as a method for reusing existing controllers. Given a set of controllers for related tasks, this combination creates a controller that performs a new task. It naturally weights the contribution of each component controller by its relevance to the current state and goal of the system. We demonstrate that linear Bellman combination outperforms naive combination often succeeding where naive combination fails. Furthermore, this combination is provably optimal for a new task if the component controllers are also optimal for related tasks. We demonstrate the applicability of linear Bellman combination to interactive character control of stepping motions and acrobatic maneuvers.Singapore-MIT GAMBIT Game LabNational Science Foundation (U.S.) (Grant 2007043041)National Science Foundation (U.S.) (Grant CCF-0810888)Adobe SystemsPixar (Firm

Chromosome-specific and noisy IFNB1 transcription in individual virus-infected human primary dendritic cells

The induction of interferon beta (IFNB1) is a key event in the antiviral immune response. We studied the role of transcriptional noise in the regulation of the IFNB1 locus in primary cultures of human dendritic cells (DCs), which are important ‘first responders’ to viral infection. In single cell assays, IFNB1 mRNA expression in virus-infected DCs showed much greater cell-to-cell variation than that of a housekeeping gene, another induced transcript and viral RNA. We determined the contribution of intrinsic noise by measuring the allelic origin of transcripts in each cell and found that intrinsic noise is a very significant part of total noise. We developed a stochastic model to investigate the underlying mechanisms. We propose that the surprisingly high levels of IFNB1 transcript noise originate from the complexity of IFNB1 enhanceosome formation, which leads to a range up to many minutes in the differences within each cell in the time of activation of each allele

Structures of apo IRF-3 and IRF-7 DNA binding domains: effect of loop L1 on DNA binding

Interferon regulatory factors IRF-3 and IRF-7 are transcription factors essential in the activation of interferon-β (IFN-β) gene in response to viral infections. Although, both proteins recognize the same consensus IRF binding site AANNGAAA, they have distinct DNA binding preferences for sites in vivo. The X-ray structures of IRF-3 and IRF-7 DNA binding domains (DBDs) bound to IFN-β promoter elements revealed flexibility in the loops (L1–L3) and the residues that make contacts with the target sequence. To characterize the conformational changes that occur on DNA binding and how they differ between IRF family members, we have solved the X-ray structures of IRF-3 and IRF-7 DBDs in the absence of DNA. We found that loop L1, carrying the conserved histidine that interacts with the DNA minor groove, is disordered in apo IRF-3 but is ordered in apo IRF-7. This is reflected in differences in DNA binding affinities when the conserved histidine in loop L1 is mutated to alanine in the two proteins. The stability of loop L1 in IRF-7 derives from a unique combination of hydrophobic residues that pack against the protein core. Together, our data show that differences in flexibility of loop L1 are an important determinant of differential IRF-DNA binding

Evidence for an evolutionary antagonism between Mrr and Type III modification systems

The Mrr protein of Escherichia coli is a laterally acquired Type IV restriction endonuclease with specificity for methylated DNA. While Mrr nuclease activity can be elicited by high-pressure stress in E. coli MG1655, its (over)expression per se does not confer any obvious toxicity. In this study, however, we discovered that Mrr of E. coli MG1655 causes distinct genotoxicity when expressed in Salmonella typhimurium LT2. Genetic screening enabled us to contribute this toxicity entirely to the presence of the endogenous Type III restriction modification system (StyLTI) of S. typhimurium LT2. The StyLTI system consists of the Mod DNA methyltransferase and the Res restriction endonuclease, and we revealed that expression of the LT2 mod gene was sufficient to trigger Mrr activity in E. coli MG1655. Moreover, we could demonstrate that horizontal acquisition of the MG1655 mrr locus can drive the loss of endogenous Mod functionality present in S. typhimurium LT2 and E. coli ED1a, and observed a strong anti-correlation between close homologues of MG1655 mrr and LT2 mod in the genome database. This apparent evolutionary antagonism is further discussed in the light of a possible role for Mrr as defense mechanism against the establishment of epigenetic regulation by foreign DNA methyltransferases

Structural Basis for Cyclic Py-Im Polyamide Allosteric Inhibition of Nuclear Receptor Binding

Pyrrole-imidazole polyamides are a class of small molecules that can be programmed to bind a broad repertoire of DNA sequences, disrupt transcription factor−DNA interfaces, and modulate gene expression pathways in cell culture experiments. In this paper we describe a high-resolution X-ray crystal structure of a β-amino turn-linked eight-ring cyclic Py-Im polyamide bound to the central six base pairs of the sequence d(5′-CCAGTACTGG-3′)_2, revealing significant modulation of DNA shape. We compare the DNA structural perturbations induced by DNA-binding transcripton factors, androgen receptor and glucocorticoid receptor, in the major groove to those induced by cyclic polyamide binding in the minor groove. The cyclic polyamide is an allosteric modulator that perturbs the DNA structure in such a way that nuclear receptor protein binding is no longer compatible. This allosteric perturbation of the DNA helix provides a molecular basis for disruption of transcription factor−DNA interfaces by small molecules, a minimum step in chemical control of gene networks

Induction of IFN-β and the Innate Antiviral Response in Myeloid Cells Occurs through an IPS-1-Dependent Signal That Does Not Require IRF-3 and IRF-7

Interferon regulatory factors (IRF)-3 and IRF-7 are master transcriptional factors that regulate type I IFN gene (IFN-α/β) induction and innate immune defenses after virus infection. Prior studies in mice with single deletions of the IRF-3 or IRF-7 genes showed increased vulnerability to West Nile virus (WNV) infection. Whereas mice and cells lacking IRF-7 showed reduced IFN-α levels after WNV infection, those lacking IRF-3 or IRF-7 had relatively normal IFN-b production. Here, we generated IRF-3−/−× IRF-7−/− double knockout (DKO) mice, analyzed WNV pathogenesis, IFN responses, and signaling of innate defenses. Compared to wild type mice, the DKO mice exhibited a blunted but not abrogated systemic IFN response and sustained uncontrolled WNV replication leading to rapid mortality. Ex vivo analysis showed complete ablation of the IFN-α response in DKO fibroblasts, macrophages, dendritic cells, and cortical neurons and a substantial decrease of the IFN-β response in DKO fibroblasts and cortical neurons. In contrast, the IFN-β response was minimally diminished in DKO macrophages and dendritic cells. However, pharmacological inhibition of NF-κB and ATF-2/c-Jun, the two other known components of the IFN-β enhanceosome, strongly reduced IFN-β gene transcription in the DKO dendritic cells. Finally, a genetic deficiency of IPS-1, an adaptor involved in RIG-I- and MDA5-mediated antiviral signaling, completely abolished the IFN-β response after WNV infection. Overall, our experiments suggest that, unlike fibroblasts and cortical neurons, IFN-β gene regulation after WNV infection in myeloid cells is IPS-1-dependent but does not require full occupancy of the IFN-β enhanceosome by canonical constituent transcriptional factors

Human Gene Coexpression Landscape: Confident Network Derived from Tissue Transcriptomic Profiles

This is an open-access article distributed under the terms of the Creative Commons Attribution License.[Background]: Analysis of gene expression data using genome-wide microarrays is a technique often used in genomic studies to find coexpression patterns and locate groups of co-transcribed genes. However, most studies done at global >omic> scale are not focused on human samples and when they correspond to human very often include heterogeneous datasets, mixing normal with disease-altered samples. Moreover, the technical noise present in genome-wide expression microarrays is another well reported problem that many times is not addressed with robust statistical methods, and the estimation of errors in the data is not provided. [Methodology/Principal Findings]: Human genome-wide expression data from a controlled set of normal-healthy tissues is used to build a confident human gene coexpression network avoiding both pathological and technical noise. To achieve this we describe a new method that combines several statistical and computational strategies: robust normalization and expression signal calculation; correlation coefficients obtained by parametric and non-parametric methods; random cross-validations; and estimation of the statistical accuracy and coverage of the data. All these methods provide a series of coexpression datasets where the level of error is measured and can be tuned. To define the errors, the rates of true positives are calculated by assignment to biological pathways. The results provide a confident human gene coexpression network that includes 3327 gene-nodes and 15841 coexpression-links and a comparative analysis shows good improvement over previously published datasets. Further functional analysis of a subset core network, validated by two independent methods, shows coherent biological modules that share common transcription factors. The network reveals a map of coexpression clusters organized in well defined functional constellations. Two major regions in this network correspond to genes involved in nuclear and mitochondrial metabolism and investigations on their functional assignment indicate that more than 60% are house-keeping and essential genes. The network displays new non-described gene associations and it allows the placement in a functional context of some unknown non-assigned genes based on their interactions with known gene families. [Conclusions/Significance]: The identification of stable and reliable human gene to gene coexpression networks is essential to unravel the interactions and functional correlations between human genes at an omic scale. This work contributes to this aim, and we are making available for the scientific community the validated human gene coexpression networks obtained, to allow further analyses on the network or on some specific gene associations. The data are available free online at http://bioinfow.dep.usal.es/coexpression/. © 2008 Prieto et al.Funding and grant support was provided by the Ministery of Health, Spanish Government (ISCiii-FIS, MSyC; Project reference PI061153) and by the Ministery of Education, Castilla-Leon Local Government (JCyL; Project reference CSI03A06).Peer Reviewe