Miracle-dz/UniFAR-FTUs huggingface dataset:
Extracellular Domain of the Transforming Growth Factor-β Receptor Negatively Regulates Ligand-independent Receptor Activation*

We have previously proposed that transforming growth factor (TGF)-β receptor activation occurs via a relative rotation between the receptors. This model suggests that in the absence of the ligand the receptor extracellular domain negatively regulates the activation of the receptor complex. To investigate this proposition, four TGF-β type I and II receptor extracellular/transmembrane-cytoplasmic and extracellular-transmembrane/cytoplasmic chimeras, TβRII-I-I and TβRI-II-II as well as TβRII-II-I and TβRI-I-II, and two extracellular domain truncated receptors TβRI-STC and TβRII-STC were generated. In either mutant mink lung R1B (lacking functional type I receptor) or DR26 (where the type II receptor is nonfunctional) cells, coexpression of two chimeric receptors, which are complementary in extracellular and cytoplasmic domains, transduced TGF-β induced signaling, as measured by the transcriptional activation of a p3TP-Lux reporter gene. Coexpression of this type of chimeric receptor with a wild-type receptor containing the opposite cytoplasmic domain exhibited a varied level of constitutive activity depending on the particular combination of the extracellular domains. In general, the type I-type I extracellular domain combination gave higher constitutive activity than the type I-type II or type II-type II combinations. Furthermore, coexpression of the extracellular domain truncated receptor with any receptor containing the opposite cytoplasmic domain always resulted in ligand independent receptor signaling. Immunoprecipitation studies showed that the formation of the receptor complexes paralleled the ligand independent activation of p3TP-Lux. Our results support the conclusion that the TGF-β receptor extracellular domain plays a negative regulatory role in receptor activation in the absence of ligand.
Basics of DNA biosensors and cancer diagnosis

The human genome is exposed to mutations during the life cycle because of many types of changes in the DNA. Viruses, radiation, transposons, mutagenic chemicals, or any errors that happen during DNA replication or the meiotic process in the cell, may cause the mutation. Many mutations have no effect on phenotype or health, while some mutations cause crucial diseases such as cancer or cardiac diseases; therefore, a better understanding of the effects of mutation on phenotype is a very important part of genetic studies. Biosensors based on DNA, RNA, and peptide nucleic acids are the most sensitive tools, due to a strong pairing of lined up nucleotide strands between bases in their complementary parts. These methods can provide information to assist clinicians in making successful treatment decisions and increase the patient survival rate. In this review, we discuss DNA biosensors based on peptide nucleic acids that have an important role in cancer diagnosis.
Human CYP2A13 and CYP2F1 Mediate Naphthalene Toxicity in the Lung and Nasal Mucosa of CYP2A13/2F1-Humanized Mice

Background: The potential carcinogenicity of naphthalene (NA), a ubiquitous environmental pollutant, in human respiratory tract is a subject of intense debate. Chief among the uncertainties in risk assessment for NA is whether human lung CYP2A13 and CYP2F1 can mediate NA’s respiratory tract toxicity. Objectives: We aimed to assess the in vivo function of CYP2A13 and CYP2F1 in NA bioactivation and NA-induced respiratory tract toxicity in mouse models. Methods: Rates of microsomal NA bioactivation and the effects of an anti-CYP2A antibody were determined for lung and nasal olfactory mucosa (OM) from Cyp2abfgs-null, CYP2A13-humanized, and CYP2A13/2F1-humanized mice. The extent of NA respiratory toxicity was compared among wild-type, Cyp2abfgs-null, and CYP2A13/2F1-humanized mice following inhalation exposure at an occupationally relevant dose (10 ppm for 4 hr). Results: In vitro studies indicated that the NA bioactivation activities in OM and lung of the CYP2A13/2F1-humanized mice were primarily contributed by, respectively, CYP2A13 and CYP2F1. CYP2A13/2F1-humanized mice showed greater sensitivity to NA than Cyp2abfgs-null mice, with greater depletion of nonprotein sulfhydryl and occurrence of cytotoxicity (observable by routine histology) in the OM, at 2 or 20 hr after termination of NA exposure, in humanized mice. Focal, rather than gross, lung toxicity was observed in Cyp2abfgs-null and CYP2A13/2F1-humanized mice; however, the extent of NA-induced lung injury (shown as volume fraction of damaged cells) was significantly greater in the terminal bronchioles of CYP2A13/2F1-humanized mice than in Cyp2abfgs-null mice. Conclusion: CYP2F1 is an active enzyme. Both CYP2A13 and CYP2F1 are active toward NA in the CYP2A13/2F1-humanized mice, where they play significant roles in NA-induced respiratory tract toxicity. https://doi.org/10.1289/EHP844
Glucocorticoid-Induced Apoptosis and Regulation of NF-κB Activity in Human Leukemic T Cells.

Glucocorticoid-induced apoptosis was investigated in glucocorticoid-sensitive 6TG1.1 and resistant ICR27TK.3 human leukemic T cells. Following glucocorticoid treatment of 6TG1.1 cells, chromatin fragmentation was observed after a delay of 24 h. Fragmentation was not observed in ICR27TK.3 cells containing mutant glucocorticoid receptors (L753F) that are activation-deficient but retain the ability to repress AP-1 activity. Nor was fragmentation observed after treatment with RU38486, indicating that repression of AP-1 activity is not involved. As described in other systems, fragmentation required ongoing protein synthesis. However, inhibition of protein synthesis with cycloheximide anytime during the first 18 h of steroid treatment was as effective in blocking chromatin fragmentation as inhibition for the entire period, suggesting that synthesis of a component with a rapid turnover rate is required. Dexamethasone treatment completely blocked 12-O-tetradecanoylphorbol 13-acetate induction of nuclear factor-κB.
CD28 Deficiency Exacerbates Joint Inflammation upon Borrelia burgdorferi Infection, Resulting in the Development of Chronic Lyme Arthritis1

Lyme disease, caused by the tick-borne spirochete Borrelia burgdorferi (Bb), is a multisystem illness, affecting many organs, such as the heart, the nervous system, and the joints. Months after Bb infection, ∼60% of patients experience intermittent arthritic attacks, a condition that in some individuals progresses to chronic joint inflammation. Although mice develop acute arthritis in response to Bb infection, the joint inflammation clears after 2 wk, despite continuous infection, only very rarely presenting with chronic Lyme arthritis. Thus, the lack of an animal system has so far prevented the elucidation of this persistent inflammatory process that occurs in humans. In this study, we report that the majority of Bb-infected CD28−/− mice develop chronic Lyme arthritis. Consistent with observations in chronic Lyme arthritis patients, the infected mutant, but not wild-type mice present recurring monoarticular arthritis over an extended time period, as well as anti-outer surface protein A of Bb serum titers. Furthermore, we demonstrate that anti-outer surface protein A Abs develop in these mice only after establishment of chronic Lyme arthritis. Thus, the Bb-infected CD28−/− mice provide a murine model for studying chronic Lyme arthritis.
Advancing Cell Biology and Functional Genomics in Maize Using Fluorescent Protein-Tagged Lines1

Genomic resources have significantly impacted plant biology research in recent years. Cell biology has been further enabled by an ongoing revolution in visualization technologies. Using fluorescent proteins (FPs), we now have unprecedented views of cellular architecture, and we can study real-time dynamics of cell structure, function, and protein localization. To date, these technologies have been most widely used in Arabidopsis (Arabidopsis thaliana); however, the grasses provide a unique opportunity to study the underlying mechanisms and inter-related controls of cell growth, morphogenesis, and physiology in leading crop models. Here, we present a resource that leverages the emerging maize (Zea mays) genome sequence to develop tools to study protein structure and function in a cellular context. Traditionally, such studies relied on fixed tissue or FP fusions driven by constitutive promoters, which can lead to significant artifacts. The maize genome sequence now provides access to regulatory regions that can be used to drive native expression. We have developed streamlined methods to generate maize FP-tagged lines using these regulatory elements, allowing analysis of tissue-specific expression and localized function. Identification of diverse proteins that function in specific subcellular compartments will provide the tools for understanding basic developmental, biochemical, and physiological processes in maize, with direct application potential for crop improvement.
The Call for Recall PI :

General-purpose knowledge bases (KBs) such as YAGO, Wikidata or the Google Knowledge Graph usually contain facts that have a high precision. In contrast, little is known about the recall of such KBs, and anecdotal evidence indicates that knowledge bases have a low recall on many topics. This project aims to develop techniques to evaluate and improve the recall of knowledge bases. We aim to use focus on text extraction in this approach, and to compare the result with a complementary approach using rule mining. In cooperation with the Wikimedia Foundation, the output from both techniques shall lead to an extension for Wikidata which uses the retrieved recall information in order to help users in viewing, adding and managing recall information.
Interactive Exploration of Protein Cavities

We present a novel application for the interactive exploration of cavities within proteins in dynamic data sets. Inside a protein, cavities can often be found close to the active center. Therefore, when analyzing a molecular dynamics simulation trajectory it is of great interest to find these cavities and determine if such a cavity opens up to the environment, making the binding site accessible to the surrounding substrate. Our user‐driven approach enables expert users to select a certain cavity and track its evolution over time. The user is supported by different visualizations of the extracted cavity to facilitate the analysis. The boundary of the protein and its cavities is obtained by means of volume ray casting, where the volume is computed in real‐time for each frame, therefore allowing the examination of time‐dependent data sets. A fast, partial segmentation of the volume is applied to obtain the selected cavity and trace it over time. Domain experts found our method useful when they applied it exemplarily on two trajectories of lipases from Rhizomucor miehei and Candida antarctica. In both data sets cavities near the active center were easily identified and tracked over time until they reached the surface and formed an open substrate channel.
An Efficient Fair Resource Allocation in Multicast Networks

A decentralized algorithm is presented that enables the different rate-adaptive receivers in different multicast sessions to adjust their rates to satisfy some fairness criterion. The problem of congestion control in networks, which supports both multirate multicast sessions and unicast sessions. A one-bit Explicit Congestion Notification (ECN) marking strategy to be used at the nodes is also proposed. The congestion control mechanism does not require any per-flow state information for unicast flows at the nodes. At the junction nodes of each multicast tree, some state information about the rates along the branches at the node may be required. This Paper calculates the throughput and rates of unicast and multicast packets for the given topology network receivers. The congestion control mechanism takes in to account the diverse user requirements when different receivers within a multicast session have different utility functions, but does not require the network to have any knowledge about the receiver utility functions. This paper compared the performance and fairness of unicast and multicast sessions.
Exploring Locally Rigid Discriminative Patches for Learning Relative Attributes

Relative attributes help in comparing two images based on their visual properties. These are of great interest as they have been shown to be useful in several vision related problems such as recognition, retrieval, and understanding image collections in general. In the recent past, quite a few techniques have been proposed for the relative attribute learning task that give reasonable performance. However, these have focused either on the algorithmic aspect or the representational aspect. In this work, we revisit these approaches and integrate their broader ideas to develop simple baselines. These not only take care of the algorithmic aspects, but also take a step towards analyzing a simple yet domain independent patch-based representation for this task. This representation can capture local shape in an image, as well as spatially rigid correspondences across regions in an image pair. The baselines are extensively evaluated on three challenging relative attribute datasets (OSR, LFW-10 and UT-Zap50K). Experiments demonstrate that they achieve promising results on the OSR and LFW-10 datasets, and perform better than the current state-of-the-art on the UT-Zap50K dataset. Moreover, they also provide some interesting insights about the problem, that could be helpful in developing the future techniques in this domain.
Established HPLC Fraction Analysis to Predict Furanocoumarin‐Based Herb–Drug Metabolic Interactions

An attempt was made in this study to predict the potential for metabolic interactions of herbal extracts of drugs from their chromatographic profiles in reverse‐phase high‐performance liquid chromatography (RP‐HPLC). Twenty‐nine structurally related furanocoumarin compounds with known inhibitory interactions with cytochrome P450 3A (CYP3A), which is important for phase‐I drug metabolism, were selected as a model system. A sigmoidal relationship was established between the CYP3A inhibitory potency (y) and the RP‐HPLC total peak response unit (Ru, x) as y = 85.36 x (14.86 + x)‐1 with a correlation coefficient of 0.63. The sigmoidal curve could be divided into three ranges designated low, medium and high risk that were used to indicate the relative inhibitory potency of the metabolic interactions of herbs or traditional Chinese herb medicines with CYP3A. These predictive classifications provide information or might be useful for ‘risk category’ decisions concerning herb–drug interactions. Copyright © 2011 John Wiley & Sons, Ltd.
Distortion Analysis of a Three-Terminal MOS-Based Discrete-Time Parametric Amplifier

Distortion associated with a three-terminal MOS parametric amplifier has been analyzed using Volterra series. A prototype design of an nMOS-based parametric amplifier with supporting circuits was integrated on a standard 0.13-μm CMOS technology. The measurement results and the theoretical characterization show a mean percentage error of 16% and 1.25% for second harmonic (A2) and third harmonic (A3), respectively.
Application of carbon felt dosimetry to field studies distant from analytical laboratory.

The applicability of carbon felt to the solvent dosimetry has been evaluated in different workplaces with several kinds of organic solvents such as toluene1-4) methyl ethyl ketone,5) n-hexane,6) tetrachloroethylene,7) and styrene. 8) The advantage of carbon felt dosimetry, e.g., lightness, smallness and simplicity, would be best evaluated in case of a long distance field study (in which the sampling site and the analytical laboratory are separated by a distance requiring time and expense for transportation between them) if the stability of the solvents absorbed on the carbon felt be proved in relation to the storage condition and storage duration. Studies were intiated to find the best feasible conditions for the storage of the carbon felt exposed. An example of a long distance study will also be described. Pieces (3 cm •~ 5 cm) of carbon felt K filter 1500 (Toyobo Co., Osaka, Japan) were housed in dosimeter cases,6) and were exposed either experimentally to a most popular mixture9,10) of n-hexane (ca. 200 ppm) and toluene (ca. 200 ppm) for 2 hours utilizing a servomechanized exposure system11,12) or as personal sam-
A cooperation-based approach to energy optimization in wireless ad hoc networks

A well known and still open issue for wireless ad hoc networks is the unfair energy consumption among the nodes. The specific position of certain nodes composing an ad hoc network makes them more involved in network operations than others, causing a faster drain of their energy. To better distribute the energy level and increase the lifetime of the whole network, we propose to periodically force the cooperation of less cooperative nodes while overwhelmed ones deliberately stop their service. A dedicated ad hoc network routing protocol is introduced to discover alternative paths without degradation in the overall network performance. Received on 13 January 2015; accepted on 06 August 2015; published on 11 August 2015
Learning in spiking neural networks

Artificial neural network simulators are a research field which attracts the interest of researchers from various fields, from biology to computer science. The final objectives are the understanding of the mechanisms underlying the human brain, how to reproduce them in an artificial environment, and how drugs interact with them. Multiple neural models have been proposed, each with their peculiarities, from the very complex and biologically realistic Hodgkin-Huxley neuron model to the very simple ``leaky integrate-and-fire'' neuron. However, despite numerous attempts to understand the learning behaviour of the synapses, few models have been proposed. Spike-Timing-Dependent Plasticity (STDP) is one of the most relevant and biologically plausible models, and some variants (such as the triplet-based STDP rule) have been proposed to accommodate all biological observations. The research presented in this thesis focuses on a novel learning rule, based on the spike-pair STDP algorithm, which provides a statistical approach with the advantage of being less computationally expensive than the standard STDP rule, and is therefore suitable for its implementation on stand-alone computational units. The environment in which this research work has been carried out is the SpiNNaker project, which aims to provide a massively parallel computational substrate for neural simulation. To support such research, two other topics have been addressed: the first is a way to inject spikes into the SpiNNaker system through a non-real-time channel such as the Ethernet link, synchronising with the timing of the SpiNNaker system. The second research topic is focused on a way to route spikes in the SpiNNaker system based on populations of neurons. The three topics are presented in sequence after a brief introduction to the SpiNNaker project. Future work could include structural plasticity (also known as synaptic rewiring); here, during the simulation of neural networks on the SpiNNaker system, axons, dendrites and synapses may be grown or pruned according to biological observations.
Data-driven efficient production of cartoon character animation

In this paper, we outline two new 3DCG technologies, MoCaToon and AniFace, which have been developed to improve the efficiency of the movie production process in the labor-intensive world of Japanese Anime, where much of the work is still done by hand. MoCaToon is a technology which enables motion capture systems to be used in the anime production process, and AniFace enables anime characters' lips to be synchronized with pre-scored voices. To verify the feasibility of these technologies, we reproduced the popular Japanese TV anime series, The Galaxy Railways, with 3D character animation utilizing both MoCaToon and AniFace. As a result of this experiment, it seems that the two technologies can be effectively used by animators to customize 3DCG characters according to their specific requirements, especially in terms of character style and motion.
Non-interference in JML

This paper deals with the specification of non-interference properties in the behavioral specification language JML. The notion of a specification pattern for JML is introduced and it is shown how such patterns can be used to specify non-interference properties such as confidentiality and integrity. The main contribution of this paper is an algorithm that takes a Java source file as input and generates a source file annotated with specification patterns for confidentiality in JML. The algorithm works for input programs written in a non-trivial subset of sequential Java. We prove that the specifications generated by the algorithm are correct and express confidentiality. In case of loops, the specifications will have to be over-approximations. Fortunately, the generated specifications can easily be refined and combined with existing hand-written JML specifications. The resulting specifications can be verified using any of the JML tools.
Automated detection of structured coarse-grained parallelism in sequential legacy applications

The e cient execution of sequential legacy applications on modern, parallel computer architectures is one of today’s most pressing problems. Automatic parallelization has been investigated as a potential solution for several decades but its success generally remains restricted to small niches of regular, array-based applications. This thesis investigates two techniques that have the potential to overcome these limitations. Beginning at the lowest level of abstraction, the binary executable, it presents a study of the limits of Dynamic Binary Parallelization (Dbp), a recently proposed technique that takes advantage of an underlying multicore host to transparently parallelize a sequential binary executable. While still in its infancy, Dbp has received broad interest within the research community. This thesis seeks to gain an understanding of the factors contributing to the limits of Dbp and the costs and overheads of its implementation. An extensive evaluation using a parameterizable Dbp system targeting a Cmp with light-weight architectural Tls support is presented. The results show that there is room for a significant reduction of up to 54% in the number of instructions on the critical paths of legacy Spec Cpu2006 benchmarks, but that it is much harder to translate these savings into actual performance improvements, with a realistic hardware-supported implementation achieving a speedup of 1.09 on average. While automatically parallelizing compilers have traditionally focused on data parallelism, additional parallelism exists in a plethora of other shapes such as task farms, divide & conquer, map/reduce and many more. These algorithmic skeletons, i.e. high-level abstractions for commonly used patterns of parallel computation, differ substantially from data parallel loops. Unfortunately, algorithmic skeletons are largely informal programming abstractions and are lacking a formal characterization in terms of established compiler concepts. This thesis develops compilerfriendly characterizations of popular algorithmic skeletons using a novel notion of commutativity based on liveness. A hybrid static/dynamic analysis framework for the context-sensitive detection of skeletons in legacy code that overcomes limitations of static analysis by complementing it with profiling information is described. A proof-of-concept implementation of this framework in the Llvm compiler infrastructure is evaluated against Spec Cpu2006 benchmarks for the detection of a