Miracle-dz/UniFAR-FTUs huggingface dataset:
Prp40 pre-mRNA processing factor 40 homolog B (PRPF40B) associates with SF1 and U2AF65 and modulates alternative pre-mRNA splicing in vivo

The first stable complex formed during the assembly of spliceosomes onto pre-mRNA substrates in mammals includes U1 snRNP, which recognizes the 5′ splice site, and the splicing factors SF1 and U2AF, which bind the branch point sequence, polypyrimidine tract, and 3′ splice site. The 5′ and 3′ splice site complexes are thought to be joined together by protein–protein interactions mediated by factors that ensure the fidelity of the initial splice site recognition. In this study, we identified and characterized PRPF40B, a putative mammalian ortholog of the U1 snRNP-associated yeast splicing factor Prp40. PRPF40B is highly enriched in speckles with a behavior similar to splicing factors. We demonstrated that PRPF40B interacts directly with SF1 and associates with U2AF65. Accordingly, PRPF40B colocalizes with these splicing factors in the cell nucleus. Splicing assays with reporter minigenes revealed that PRPF40B modulates alternative splice site selection. In the case of Fas regulation of alternative splicing, weak 5′ and 3′ splice sites and exonic sequences are required for PRPF40B function. Placing our data in a functional context, we also show that PRPF40B depletion increased Fas/CD95 receptor number and cell apoptosis, which suggests the ability of PRPF40B to alter the alternative splicing of key apoptotic genes to regulate cell survival.
a Carbohydrate-Binding Module Attenuates Oxidized Cellulose Binding to Allergens with

Grass and mite allergens are of the main causes of allergy and asthma. A carbohydrate-binding module (CBM) represents a common motif to groups I ( b -expansin) and II/III (expansin-like) grass allergens and is suggested to mediate allergen-IgE binding. House dust mite group II allergen (Der p 2 and Der f 2) structures bear strong similarity to expansin’s CBM, suggesting their ability to bind carbohydrates. Thus, this study proposes the design of a carbohydrate-based treatment in which allergen binding to carbohydrate particles will promote allergen airway clearance and prevent allergic reactions. The aim of the study was to identify a polysaccharide with high allergen-binding capacities and to explore its ability to prevent allergy. Oxidized cellulose (OC) demonstrated allergen-binding capacities toward grass and mite allergens that surpassed those of any other polysaccharide examined in this study. Furthermore, inhalant preparations of OC microparticles attenuated allergic lung inﬂammation in rye grass-sensitized Brown Norway rats and OVA-sensitized BALB/c mice. Fluorescently labeled OC efﬁciently cleared from the mouse airways and body organs. Moreover, long-term administration of OC inhalant to Wistar rats did not result in toxicity. In conclusion, many allergens, such as grass and dust mite, contain a common CBM motif. OC demonstrates a strong and relatively speciﬁc allergen-binding capacity to CBM-containing allergens. OC’s ability to attenuate allergic inﬂammation, together with its documented safety record, forms a ﬁrm basis for its application as an alternative treatment for prevention and relief of allergy and asthma. The Journal of Immunology , 2011, 186: 000–000.
Computational linguistics for metadata building: Aggregating text processing technologies for enhanced image access

We present a system which applies text mining using computational linguistic techniques to automatically extract, categorize, disambiguate and filter metadata for image access. Candidate subject terms are identified through standard approaches; novel semantic categorization using machine learning and disambiguation using both WordNet and a domain specific thesaurus are applied. The resulting metadata can be manually edited by image catalogers or filtered by semi-automatic rules. We describe the implementation of this workbench created for, and evaluated by, image catalogers. We discuss the system's current functionality, developed under the Computational Linguistics for Metadata Building (CLiMB) research project. The CLiMB Toolkit has been tested with several collections, including: Art Images for College Teaching (AICT), ARTStor, the National Gallery of Art (NGA), the Senate Museum, and from collaborative projects such as the Landscape Architecture Image Resource (LAIR) and the field guides of the Vernacular Architecture Group (VAG).
Memantine lowers amyloid‐β peptide levels in neuronal cultures and in APP/PS1 transgenic mice

Memantine is a moderate‐affinity, uncompetitive N‐methyl‐D‐aspartate (NMDA) receptor antagonist that stabilizes cognitive, functional, and behavioral decline in patients with moderate to severe Alzheimer's disease (AD). In AD, the extracellular deposition of fibrillogenic amyloid‐β peptides (Aβ) occurs as a result of aberrant processing of the full‐length Aβ precursor protein (APP). Memantine protects neurons from the neurotoxic effects of Aβ and improves cognition in transgenic mice with high brain levels of Aβ. However, it is unknown how memantine protects cells against neurodegeneration and affects APP processing and Aβ production. We report the effects of memantine in three different systems. In human neuroblastoma cells, memantine, at therapeutically relevant concentrations (1–4 μM), decreased levels of secreted APP and Aβ1–40. Levels of the potentially amylodogenic Aβ1–42 were undetectable in these cells. In primary rat cortical neuronal cultures, memantine treatment lowered Aβ1–42 secretion. At the concentrations used, memantine treatment was not toxic to neuroblastoma or primary cultures and increased cell viability and/or metabolic activity under certain conditions. In APP/presenilin‐1 (PS1) transgenic mice exhibiting high brain levels of Aβ1–42, oral dosing of memantine (20 mg/kg/day for 8 days) produced a plasma drug concentration of 0.96 μM and significantly reduced the cortical levels of soluble Aβ1–42. The ratio of Aβ1–40/Aβ1–42 increased in treated mice, suggesting effects on the γ‐secretase complex. Thus, memantine reduces the levels of Aβ peptides at therapeutic concentrations and may inhibit the accumulation of fibrillogenic Aβ in mammalian brains. Memantine's ability to preserve neuronal cells against neurodegeneration, to increase metabolic activity, and to lower Aβ level has therapeutic implications for neurodegenerative disorders. © 2009 Wiley‐Liss, Inc.
Graphical Tools for Network Meta-Analysis in STATA

Network meta-analysis synthesizes direct and indirect evidence in a network of trials that compare multiple interventions and has the potential to rank the competing treatments according to the studied outcome. Despite its usefulness network meta-analysis is often criticized for its complexity and for being accessible only to researchers with strong statistical and computational skills. The evaluation of the underlying model assumptions, the statistical technicalities and presentation of the results in a concise and understandable way are all challenging aspects in the network meta-analysis methodology. In this paper we aim to make the methodology accessible to non-statisticians by presenting and explaining a series of graphical tools via worked examples. To this end, we provide a set of STATA routines that can be easily employed to present the evidence base, evaluate the assumptions, fit the network meta-analysis model and interpret its results.
Theory and Computation of Line Defect Fields in Solids and Liquid Crystals

Theory and computation of line defect fields in solids and liquid crystals The theory and computation of line defects are discussed in the context of both solids and liquid crystals. This dissertation includes four parts. The Generalized Disclination theory is discussed and applied to numerous interfacial and bulk line defect problems. An augmented Oseen-Frank energy as well as a novel 2D-model is proposed and demonstrated for disclination dynamics in liquid crystal. A model based on kinematics and thermodynamics is devised to predict tactoid dynamics during the process of the isotropic-nematic phase transition in LCLC. In the first part of the thesis, the utility of the notion of generalized disclinations in materials science is discussed within the physical context of modeling interfacial and bulk line defects. The Burgers vector of a disclination dipole in linear elasticity is derived, clearly demonstrating the equivalence of its stress field to that of an edge dislocation. An explicit formula for the displacement jump of a single localized composite defect line in terms of given g.disclination and dislocation strengths is deduced based on the Weingarten theorem for g.disclination theory at finite deformation. The Burgers vector of a g.disclination dipole at finite deformation is also derived. In the second part, a numerical method is developed to solve for the stress and distortion fields of g.disclination systems. Problems of small and finite deformation theory are considered. The fields of various line defects and grain/phase boundary problems are approximated. It is demonstrated that while the farfield topological identity of a dislocation of appropriate strength and a disclinationdipole plus a slip dislocation comprising a disconnection are the same, the latter microstructure is energetically favorable. This underscores the complementary
THIN-PLATE SPLINE MODELLING OF ELASTIC DEFORMATIONS IN FINGERPRINTS

This paper presents a novel minutiae matching method that describes elastic distortions by means of a thin-plate spline model and uses that model to normalize the shape of the test ngerprint with respect to the template. The method rst determines possible matching minutiae pairs by means of comparing local neighborhoods of the minutiae. Next, a thin-plate spline model is used to describe the non-linear distortions between the two sets of possible pairs. One of the ngerprints is deformed and registered according to the estimated model, and then the number of matching minutiae is counted. This method is able to model all possible non-linear distortions and therefore to use very tight bounding boxes. Experiments show considerable improvement with respect to minutiae matching based on translation, rotation and scaling only. Furthermore, it turns out that the nature of elastic distortion in practice is quite different from the theoretical models proposed in literature.
Loss of agency in apraxia

The feeling of acting voluntarily is a fundamental component of human behavior and social life and is usually accompanied by a sense of agency. However, this ability can be impaired in a number of diseases and disorders. An important example is apraxia, a disturbance traditionally defined as a disorder of voluntary skillful movements that often results from frontal-parietal brain damage. The first part of this article focuses on direct evidence of some core symptoms of apraxia, emphasizing those with connections to agency and free will. The loss of agency in apraxia is reflected in the monitoring of internally driven action, in the perception of specifically self-intended movements and in the neural intention to act. The second part presents an outline of the evidences supporting the functional and anatomical link between apraxia and agency. The available structural and functional results converge to reveal that the frontal–parietal network contributes to the sense of agency and its impairment in disorders such as apraxia. The current knowledge on the generation of motor intentions and action monitoring could potentially be applied to develop therapeutic strategies for the clinical rehabilitation of voluntary action.
Improving Control of Dexterous Hand Prostheses Using Adaptive Learning

At the time of this writing, the main means of control for polyarticulated self-powered hand prostheses is surface electromyography (sEMG). In the clinical setting, data collected from two electrodes are used to guide the hand movements selecting among a finite number of postures. Machine learning has been applied in the past to the sEMG signal (not in the clinical setting) with interesting results, which provide more insight on how these data could be used to improve prosthetic functionality. Researchers have mainly concentrated so far on increasing the accuracy of sEMG classification and/or regression, but, in general, a finer control implies a longer training period. A desirable characteristic would be to shorten the time needed by a patient to learn how to use the prosthesis. To this aim, we propose here a general method to reuse past experience, in the form of models synthesized from previous subjects, to boost the adaptivity of the prosthesis. Extensive tests on databases recorded from healthy subjects in controlled and noncontrolled conditions reveal that the method significantly improves the results over the baseline nonadaptive case. This promising approach might be employed to pretrain a prosthesis before shipping it to a patient, leading to a shorter training phase.
Peculiar citric acid cycle of hydrothermal vent chemolithoautotroph Hydrogenovibrio crunogenus, and insights into carbon metabolism by obligate autotrophs

The genome sequence of the obligate chemolithoautotroph Hydrogenovibrio crunogenus paradoxically predicts a complete oxidative citric acid cycle (CAC). This prediction was tested by multiple approaches including whole cell carbon assimilation to verify obligate autotrophy, phylogenetic analysis of CAC enzyme sequences and enzyme assays. Hydrogenovibrio crunogenus did not assimilate any of the organic compounds provided (acetate, succinate, glucose, yeast extract, tryptone). Enzyme activities confirmed that its CAC is mostly uncoupled from the NADH pool. 2-Oxoglutarate:ferredoxin oxidoreductase activity is absent, though pyruvate:ferredoxin oxidoreductase is present, indicating that sequence-based predictions of substrate for this oxidoreductase were incorrect, and that H. crunogenus may have an incomplete CAC. Though the H. crunogenus CAC genes encode uncommon enzymes, the taxonomic distribution of their top matches suggests that they were not horizontally acquired. Comparison of H. crunogenus CAC genes to those present in other 'Proteobacteria' reveals that H. crunogenus and other obligate autotrophs lack the functional redundancy for the steps of the CAC typical for facultative autotrophs and heterotrophs, providing another possible mechanism for obligate autotrophy.
Enriching the Output of a Parser Using Memory-based Learning

We describe a method for enriching the output of a parser with information available in a corpus. The method is based on graph rewriting using memory-based learning, applied to dependency structures. This general framework allows us to accurately recover both grammatical and semantic information as well as non-local dependencies. It also facilitates dependency-based evaluation of phrase structure parsers. Our method is largely independent of the choice of parser and corpus, and shows state of the art performance.
Convexity-based algorithms for design centering

Two new geometrical algorithms for design centering are presented. In each case, the feasible region is first approximated by a convex polytope. The first algorithm inscribes the largest Hessian ellipsoid within the approximating polytope. The second assumes Gaussian parameter distributions, formulates the problem as a convex programming problem, and uses an efficient algorithm to perform the optimization.
Application Mapping Onto Mesh-Based Network-on-Chip Using Discrete Particle Swarm Optimization

This paper presents a discrete particle swarm optimization (PSO)-based strategy to map applications on both 2-D and 3-D mesh-connected Networks-on-Chip. The basic PSO formulation has been augmented by: 1) running multiple PSOs and 2) deterministically generating a part of the initial population for PSO. The mapping results, in terms of the overall communication metric, have been compared with well-known techniques reported in the literature and also with exact methods built around integer linear programming (ILP). Our PSO-based results are superior to those from reported techniques. For smaller benchmarks, the results obtained are same as those corresponding to the ILP formulation, establishing the quality of the solution strategy.
Modelling of evolving microstructures at different scales

This thesis deals with the development of novel material models that capture the evolution of microstructures. The analysis of microstructures is essential for the description of metallic material properties, which are considered in this thesis. Depending on the underlying application, microstructures are analysed on the technological relevant macroscale or on the materials science relevant microscale. Independent of the underlying scale, mechanical and thermal loadings are the most dominating factors of evolving microstructures. The objective of this work is to capture evolving microstructures for the technologically relevant macroscale as well as for the materials science relevant microscale. A key aspect of a macroscopically motivated modelling is related to the temperature prediction in metals which are induced by plastic deformations. By means of a novel and generalised coupling, which is based on an adopted decomposition of stored and dissipative energy parts, a more realistic temperature prediction compared to standard coupling approaches is achieved. Furthermore, the anisotropic texture evolution in hardening processes is incorporated by a generalised distortional hardening model, which takes account of the distortion of a yield surface. Based on the novel thermomechanical coupling and distortional hardening, the relevant mechanisms are captured on the macroscale. In addition to the macroscopic modelling and in order to obtain a more detailed insight into microstructures, the heterogeneity of microstructures and the underlying transformation of phases is described by means of phase field theories. A problem in existing phase field models pertains the determination of effective properties in the diffuse interface. In order to describe microstructures as exactly as possible, a generalised phase field model is developed incorporating state-of-the-art as well as novel and more efficient homogenisation assumptions. For the phase transformations, Allen-Cahn-type and Cahn-Hilliard-type models are applied so that the most important effects of the evolution of microstructures are included. All material models are derived three-dimensionally at finite strains and are based on thermodynamically consistent formulations. Considering an overall variational modelling, the balance and evolution equations follow jointly from underlying minimisation principles. The derived formulations are efficiently implemented in finite elements and are implicitly and monolithically solved. Demonstrative examples show the capability of the derived models.
Enhancing the Context-Enhanced Additive Heuristic with Precedence Constraints

Recently, Helmert and Geffner proposed the context-enhanced additive heuristic, where fact costs are evaluated relative to context states that arise from achieving first a pivot condition of each operator. As Helmert and Geffner pointed out, the method can be generalized to consider contexts arising from arbitrary precedence constraints over operator conditions instead. Herein, we provide such a generalization. We extend Helmert and Geffner's equations, and discuss a number of design choices that arise. Drawing on previous work on goal orderings, we design a family of methods for automatically generating precedence constraints. We run large-scale experiments, showing that the technique can help significantly, depending on the choice of precedence constraints. We shed some light on this by profiling the behavior of all possible precedence constraints, using a sampling technique.
Activating mutations in PTPN3 promote cholangiocarcinoma cell proliferation and migration and are associated with tumor recurrence in patients.

BACKGROUND & AIMS The pathogenesis of intrahepatic cholangiocarcinoma (ICC), the second most common hepatic cancer, is poorly understood, and the incidence of ICC is increasing worldwide. We searched for mutations in human ICC tumor samples and investigated how they affect ICC cell function. METHODS We performed whole exome sequencing of 7 pairs of ICC tumors and their surrounding nontumor tissues to detect somatic alterations. We then screened 124 pairs of ICC and nontumor samples for these mutations, including 7 exomes. We compared mutations in PTPN3 with tumor recurrence in 124 patients and PTPN3 expression levels with recurrence in 322 patients (the combination of both in 86 patients). The functional effects of PTPN3 variations were determined by RNA interference and transgenic expression in cholangiocarcinoma cell lines (RBE, HCCC-9810, and Huh28). RESULTS Based on exome sequencing, pathways that regulate protein phosphorylation were among the most frequently altered in ICC samples and genes encoding protein tyrosine phosphatases (PTPs) were among the most frequently mutated. We identified mutations in 9 genes encoding PTPs in 4 of 7 ICC exomes. In the prevalence screen of 124 paired samples, 51.6% of ICCs contained somatic mutations in at least 1 of 9 PTP genes; 41.1% had mutations in PTPN3. Transgenic expression of PTPN3 in cell lines increased cell proliferation, colony formation, and migration. PTPN3(L232R) and PTPN3(L384H), which were frequently detected in ICC samples, were found to be gain-of-function mutations; their expression in cell lines further increased cell proliferation, colony formation, and migration. ICC-associated variants of PTPN3 altered phosphatase activity. Patients whose tumors contained activating mutations or higher levels of PTPN3 protein than nontumor tissues had higher rates of disease recurrence than patients whose tumors did not have these characteristics. CONCLUSIONS Using whole exome sequencing of ICC samples from patients, we found that more than 40% contain somatic mutations in PTPN3. Activating mutations in and high expression levels of PTPN3 were associated with tumor recurrence.
A basis-background subtraction method using non-negative matrix factorization

In this paper, we proposed a basis-background subtraction method using non-negative matrix factorization (NMF). The core idea is to learn the parts of complex background environments by NMF algorithm and exploit the discrimination information in the training set to boost the reconstruction capability of the background efficiently. The method utilize the distance between an observed image and the reconstructed background image for segmenting foreground objects. The principle component analysis (PCA) is used for the enhanced initialization of NMF algorithm. A kind of off-line basis-background maintenance scheme is introduced instead of an incremental learning. A variety of experiments are conducted and illustrate the effectiveness in background subtraction. Quantitative evaluation and comparison with the existing methods show that the proposed method provides good improved results.