Miracle-dz/UniFAR-FTUs huggingface dataset:
NOP132 is required for proper nucleolus localization of DEAD-box RNA helicase DDX47

Previously, we described a novel nucleolar protein, NOP132, which interacts with the small GTP binding protein RRAG A. To elucidate the function of NOP132 in the nucleolus, we identified proteins that interact with NOP132 using mass spectrometric methods. NOP132 associated mainly with proteins involved in ribosome biogenesis and RNA metabolism, including the DEAD-box RNA helicase protein, DDX47, whose yeast homolog is Rrp3, which has roles in pre-rRNA processing. Immunoprecipitation of FLAG-tagged DDX47 co-precipitated rRNA precursors, as well as a number of proteins that are probably involved in ribosome biogenesis, implying that DDX47 plays a role in pre-rRNA processing. Introduction of NOP132 small interfering RNAs induced a ring-like localization of DDX47 in the nucleolus, suggesting that NOP132 is required for the appropriate localization of DDX47 within the nucleolus. We propose that NOP132 functions in the recruitment of pre-rRNA processing proteins, including DDX47, to the region where rRNA is transcribed within the nucleolus.
ANG II type 2 receptors and neural control of intrarenal blood flow.

We tested the hypothesis that activation of angiotensin type 2 (AT(2)) receptors, by both exogenous and endogenous ANG II, modulates neurally mediated vasoconstriction in the renal cortical and medullary circulations. Under control conditions in pentobarbital-anesthetized rabbits, electrical stimulation of the renal nerves (RNS; 0.5-8 Hz) reduced renal blood flow (RBF; -88 +/- 3% at 8 Hz) and cortical perfusion (CBF; -92 +/- 2% at 8 Hz) more than medullary perfusion (MBF; -67 +/- 6% at 8 Hz). Renal arterial infusion of ANG II, at a dose titrated to reduce RBF by approximately 40-50% (5-50 ng.kg(-1). min(-1)) blunted responses of MBF to RNS, without significantly affecting responses of RBF or CBF. Subsequent administration of PD123319 (1 mg/kg plus 1 mg.kg(-1). h(-1)) during continued renal arterial infusion of ANG II did not significantly affect responses of RBF or CBF to RNS but enhanced responses of MBF, so that they were similar to those observed under control conditions. In contrast, administration of PD123319 alone blunted responses of CBF and MBF to RNS. Subsequent renal arterial infusion of ANG II in PD123319-pretreated rabbits restored CBF responses to RNS back to control levels. In contrast, ANG II infusion in PD123319-pretreated rabbits did not alter MBF responses to RNS. These data indicate that exogenous ANG II can blunt neurally mediated vasoconstriction in the medullary circulation through activation of AT(2) receptors. However, AT(2)-receptor activation by endogenous ANG II appears to enhance neurally mediated vasoconstriction in both the cortical and medullary circulations.
Polyethyleneimine-functionalized boron nitride nanospheres as efficient carriers for enhancing the immunostimulatory effect of CpG oligodeoxynucleotides

CpG oligodeoxynucleotides (ODNs) stimulate innate and adaptive immune responses. Thus, these molecules are promising therapeutic agents and vaccine adjuvants against various diseases. In this study, we developed a novel CpG ODNs delivery system based on polyethyleneimine (PEI)-functionalized boron nitride nanospheres (BNNS). PEI was coated on the surface of BNNS via electrostatic interactions. The prepared BNNS–PEI complexes had positive zeta potential and exhibited enhanced dispersity and stability in aqueous solution. In vitro cytotoxicity assays revealed that the BNNS–PEI complexes with concentrations up to 100 μg/mL exhibited no obvious cytotoxicity. Furthermore, the positively charged surface of the BNNS–PEI complexes greatly improved the loading capacity and cellular uptake efficiency of CpG ODNs. Class B CpG ODNs loaded on the BNNS–PEI complexes enhanced the production of interleukin-6 and tumor necrosis factor-α from peripheral blood mononuclear cells compared with CpG ODNs directly loaded on BNNS. Contrary to the free CpG ODNs or CpG ODNs directly loaded on BNNS, class B CpG ODNs loaded on the BNNS–PEI complexes induced interferon-α simultaneously. PEI coating may have changed the physical form of class B CpG ODNs on BNNS, which further affected their interaction with Toll-like receptor 9 and induced interferon-α. Therefore, BNNS–PEI complexes can be used to enhance the immunostimulatory effect and therapeutic activity of CpG ODNs and the treatment of diseases requiring interleukin-6, tumor necrosis factor-α, and interferon-α.
On Relevant Dimensions in Kernel Feature Spaces

We show that the relevant information of a supervised learning problem is contained up to negligible error in a finite number of leading kernel PCA components if the kernel matches the underlying learning problem in the sense that it can asymptotically represent the function to be learned and is sufficiently smooth. Thus, kernels do not only transform data sets such that good generalization can be achieved using only linear discriminant functions, but this transformation is also performed in a manner which makes economical use of feature space dimensions. In the best case, kernels provide efficient implicit representations of the data for supervised learning problems. Practically, we propose an algorithm which enables us to recover the number of leading kernel PCA components relevant for good classification. Our algorithm can therefore be applied (1) to analyze the interplay of data set and kernel in a geometric fashion, (2) to aid in model selection, and (3) to denoise in feature space in order to yield better classification results.
Bayesian Ensemble Learning for Nonlinear Factor Analysis Text Mining with the Websom

An active research topic in machine learning is the development of model structures which would be rich enough to represent relevant aspects of the observations but would still allow efficient learning and inference. Linear factor analysis and related methods such as principal component analysis and independent component analysis are widely used feature extraction and data analysis techniques. They are computationally efficient but are restricted to linear models. Many natural phenomena are nonlinear and therefore several attempts have been made to gen-eralise the model by relaxing the linearity assumption. The suggested approaches have suffered from overfitting and the computational complexity of many of the algorithms scales exponentially with respect to the number of factors, which makes the application of these methods to high dimensional factor spaces infeasible. This thesis describes the development of a nonlinear extension of factor analysis. The learning algorithm is based on Bayesian probability theory and solves many of the problems related to overfitting. The unknown nonlinear generative mapping is modelled by a multi-layer perceptron network. The computational complexity of the algorithm scales quadratically with respect to the dimension of the factor space which makes it possible to use a significantly larger number of factors than with the previous algorithms. The feasibility of the algorithm is demonstrated in experiments with artificial and natural data sets. Extensions which combine the nonlinear model with non-Gaussian and dynamic models for the factors are introduced. Abstract: The emerging field of text mining applies methods from data mining and exploratory data analysis to analyzing text collections and to conveying information to the user in an intuitive manner. Visual, map-like displays provide a powerful and fast medium for portraying information about large collections of text. Relationships between text items and collections , such as similarity, clusters, gaps and outliers can be communicated naturally using spatial relationships, shading, and colors. In the WEBSOM method the self-organizing map (SOM) algorithm is used to automatically organize very large and high-dimensional collections of text documents onto two-dimensional map displays. The map forms a document landscape where similar documents appear close to each other at points of the regular map grid. The landscape can be labeled with automatically identified descriptive words that convey properties of each area and also act as landmarks during exploration. With the help of an HTML-based interactive tool the ordered landscape can be used in browsing the document collection and in performing searches on the …
Human Capital and Externalities in Cities

We combine growth theory with US Census data on individual schooling and wages to estimate the aggregate return to human capital and human capital externalities in cities. Our estimates imply that a one year increase in average schooling in cities increases their aggregate labour productivity by 8 to 11%. We find no evidence for aggregate human capital externalities in cities however, although we use three different approaches. Our main theoretical contribution is to show how human capital externalities can be identified (non-parametrically) even if workers with different levels of human capital are imperfect substitutes in production.
Ku is involved in cell growth, DNA replication and G1-S transition

The Ku protein (Ku70-Ku80) is involved in various genome-maintenance processes such as DNA replication and repair, telomere maintenance, and chromosomal stability. We previously found that Ku80 is implicated in the loading of members of the pre-replicative complex (pre-RC) onto replication origins. Here, we report that acute reduction of Ku80 to 10% of its normal levels leads to impaired DNA replication and activation of a replication stress checkpoint. In the absence of Ku80, decreased levels of the initiator proteins Orc1 and Orc6 as well as reduced chromatin binding of Orc1, Orc4 and Cdc45 were observed, leading to decreased origin firing, whereas Orc2 and Orc3 were unaffected. Prolonged perturbation of DNA replication caused the block of cell-cycle progression in late G1 phase with low Cdk2 activity due to increased p21 expression and decreased Cdc25A and Cdk2 levels. The data suggest the interplay between the DNA-replication and cell-cycle machineries and shed light on a new role of Ku in G1-S transition.
Incremental Learning in Deep Convolutional Neural Networks Using Partial Network Sharing

Deep convolutional neural network (DCNN) based supervised learning is a widely practiced approach for large-scale image classification. However, retraining these large networks to accommodate new, previously unseen data demands high computational time and energy requirements. Also, previously seen training samples may not be available at the time of retraining. We propose an efficient training methodology and incrementally growing DCNN to learn new tasks while sharing part of the base network. Our proposed methodology is inspired by transfer learning techniques, although it does not forget previously learned tasks. An updated network, for learning new set of classes, is formed using previously learned convolutional layers (shared from initial part of base network) with addition of few newly added convolutional kernels included in the later layers of the network. We employed a ‘clone-and-branch’ technique with calibration, which allows the network to learn new tasks (containing classes with similar features as old tasks) one after another without any performance loss in old tasks. We evaluated the proposed scheme on several recognition applications. The classification accuracy achieved by our approach is comparable to the regular incremental learning approach (where networks are updated with new training samples only, without any network sharing), while achieving energy efficiency, reduction in storage requirements, memory access and training time.
The expression of myosin genes in developing skeletal muscle in the mouse embryo

Using in situ hybridization, we have investigated the temporal sequence of myosin gene expression in the developing skeletal muscle masses of mouse embryos. The probes used were isoform-specific, 35S-labeled antisense cRNAs to the known sarcomeric myosin heavy chain and myosin alkali light chain gene transcripts. Results showed that both cardiac and skeletal myosin heavy chain and myosin light chain mRNAs were first detected between 9 and 10 d post coitum (p.c.) in the myotomes of the most rostral somites. Myosin transcripts appeared in more caudal somites at later stages in a developmental gradient. The earliest myosin heavy chain transcripts detected code for the embryonic skeletal (MHCemb) and beta-cardiac (MHC beta) isoforms. Perinatal myosin heavy chain (MHCpn) transcripts begin to accumulate at 10.5 d p.c. , which is much earlier than previously reported. At this stage, MHCemb is the major MHC transcript. By 12.5 d p.c. , MHCpn and MHCemb mRNAs are present to an equal extent, and by 15.5 d p.c. the MHCpn transcript is the major MHC mRNA detected. Cardiac MHC beta transcripts are always present as a minor component. In contrast, the cardiac MLC1A mRNA is initially more abundant than that encoding the skeletal MLC1F isoform. By 12.5 d p.c. the two MLC mRNAs are present at similar levels, and by 15.5 d p.c. , MLC1F is the predominant MLC transcript detected. Transcripts for the ventricular/slow (MLC1V) and another fast skeletal myosin light chain (MLC3F) are not detected in skeletal muscle before 15 d p.c. , which marks the beginning of the fetal stage of muscle development. This is the first stage at which we can detect differences in expression of myosin genes between developing muscle fibers. We conclude that, during the development of the myotome and body wall muscles, different myosin genes follow independent patterns of activation and accumulation. The data presented are the first detailed study of myosin gene expression at these early stages of skeletal muscle development.
Dynamics of Neutrophils-to-Lymphocyte Ratio Predict Outcomes of PD-1/PD-L1 Blockade

Introduction Baseline neutrophil-to-lymphocyte ratio (NLR) has been repeatedly reported as a significant prognostic factor in advanced cancer patients. We explored whether changes in NLR may predict outcome of advanced cancer patients enrolled into phase 1 trials and treated with PD-1/PD-L1 inhibitors. Patients and Methods Advanced cancer patients enrolled into phase 1 trials between September 2013 and May 2016 and treated with anti-PD-1/PD-L1 agents were included in this retrospective study. NLR was calculated at baseline and after 2 cycles of treatment. Royal Marsden Hospital (RMH) prognostic score and Eastern Cooperative Group (ECOG) performance status (PS) were determined at baseline. Kaplan-Meier estimation and Cox regression analyses were used to assess the impact of NLR dynamics on PFS. Results Among the 55 patients eligible, 26 (47%) were treated with anti-PD-L1 monotherapy, 22 (40%) received single agent anti-PD-1, and 7 (13%) were given a tyrosine kinase inhibitor (TKI) plus a PD-1 inhibitor. Neither ECOG PS nor RMH prognostic score was significantly associated with PFS in our cohort, whereas changes in NLR significantly impacted on PFS. Conclusion Changes in the NLR may be a useful predicting factor in advanced cancer patients treated with anti-PD-1/PD-L1 agents. Further prospective trials are needed to verify these findings.
Influence of heat treatment and particle shape on mechanical properties of infiltrated Al2O3 particle reinforced Al-2 wt-%Cu

Abstract Al-2 wt-%Cu composites were produced by gas pressure infiltration of powder beds with a high volume fraction (45 to 60 vol.-%) of angular or polygonal alumina particles. The tensile behaviour and fracture toughness of the composites were characterised in as cast, solutionised and peak aged (T6) conditions. It was shown that coarse intermetallics that are formed during solidification and located preferentially at the particle/matrix interface lead to lower toughness compared with the same composites in solutionised and T6 conditions. The particle nature and shape exert a strong influence on the properties of the composites: polygonal particles are intrinsically stronger than angular particles and yield stronger, tougher, and more ductile composites. Composite toughness variations are explained in terms of fracture micromechanisms.
Experimental Strategies for Investigating Psychostimulant Drug Actions and Prefrontal Cortical Function in ADHD and Related Attention Disorders

Amphetamine‐like psychostimulant drugs have been used for decades to treat a variety of clinical conditions. Methylphenidate (MPH)—RitalinR, a compound that blocks reuptake of synaptically released norepinephrine (NE) and dopamine (DA) in the brain, has been used for more than 30 years in low dose, long‐term regimens to treat attention deficit‐hyperactive disorder (ADHD) in juveniles, adolescents, and adults. Now, these agents are also becoming increasingly popular among healthy individuals from all walks of life (e.g., military, students) and age groups (teenagers thru senior citizens) to promote wakefulness and improve attention. Although there is agreement regarding the primary biochemical action of MPH, the physiological basis for its efficacy in normal individuals and ADHD patients is lacking. Study of the behavioral and physiological actions of clinically and behaviorally relevant doses of MPH in normal animals provides an opportunity to explore the role of catecholamine transmitters in prefrontal cortical function and attentional processes as they relate to normal operation of brain circuits and ADHD pathology. The goal of ongoing studies has been to: (1) assess the effects of low dose MPH on rodent performance in a well characterized sensory‐guided sustained attention task, (2) examine the effects of the same low‐dose chronic MPH administration on task‐related discharge of prefrontal cortical (PFC) neurons, and (3) investigate the effects of NE and DA on membrane response properties and synaptic transmission in identified subsets of PFC neurons. Combinations of these approaches can be used in adolescent, adult, and aged animals to identify the parameters of cell and neural circuit function that are regulated by MPH and to establish an overarching explanation of how MPH impacts PFC operations from cellular through behavioral functional domains. Anat Rec,, 2011. © 2011 Wiley‐Liss, Inc.
Securing Web Service by Automatic Robot Detection

Web sites are routinely visited by automated agents known as Web robots, that perform acts ranging from the beneficial, such as indexing for search engines, to the malicious, such as searching for vulnerabilities, attempting to crack passwords, or spamming bulletin boards. Previous work to identify malicious robots has relied on ad-hoc signature matching and has been performed on a per-site basis. As Web robots evolve and diversify, these techniques have not been scaling. We approach the problem as a special form of the Turing test and defend the system by inferring if the traffic source is human or robot. By extracting the implicit patterns of human Web browsing, we develop simple yet effective algorithms to detect human users. Our experiments with the CoDeeN content distribution network show that 95% of human users are detected within the first 57 requests, and 80% can be identified in only 20 requests, with a maximum false positive rate of 2.4%. In the time that this system has been deployed on CoDeeN, robot-related abuse complaints have dropped by a factor of 10.
MIMO radar receiver design

Compared to traditional phased-array radar, multiple-input multiple-output (MIMO) radar can offer better parameter identifiability and higher resolution, enable the direct applicability of adaptive techniques for effective interference and jamming suppression, and allow for much flexibility for transmit beampattern design and waveform optimization. Reaping the full benefit of the superior performance enabled by the MIMO radar requires a novel design of its receive filters to minimize the impact of scatterers in nearby range bins on the received signals from the range bin of interest (the so-called range compression problem). Recently, an instrumental variables (IV) approach to MIMO radar receive filter design was proposed and shown to outperform the conventional matched filter approach. In this paper, we will present a least squares (LS) based MIMO radar receiver design. We will compare the performances of the IV and LS approaches with that of the matched filter method under a variety of test conditions.
Surface expression of alpha 4 integrin by CD4 T cells is required for their entry into brain parenchyma

Cloned CD4 T cell lines that recognize the Ac1-16 peptide of myelin basic protein bound to I-Au were isolated and used to analyze the immunopathogenesis of experimental autoimmune encephalomyelitis (EAE). T helper type 1 (Th1) clones induced disease, while Th2 clones did not. Using variants of a single cloned Th1 line, the surface expression of alpha 4 integrins (very late antigen 4 [VLA-4]) was identified as a major pathogenic factor. Encephalitogenic clones and nonencephalitogenic variants differ by 10-fold in their level of surface expression of alpha 4 integrin and in their ability to bind to endothelial cells and recombinant vascular cell adhesion molecule 1 (VCAM-1). The alpha 4 integrin-high, disease-inducing cloned Th1 T cells enter brain parenchyma in abundance, while alpha 4 integrin-low, nonencephalitogenic Th1 cells do not. Moreover, antibodies to alpha 4 integrin, its ligand VCAM-1, and intercellular adhesion molecule 1 all influence the pathogenicity of this encephalitogenic clone in vivo. The importance of the expression of VLA-4 for encephalitogenicity is not unique to cloned T cell lines, as similar results were obtained using myelin basic protein-primed lymph node T cells. alpha 4 integrin levels did not affect antigen responsiveness or production of the Th1 cytokines interleukin 2, interferon gamma, and lymphotoxin/tumor necrosis factor beta; and antibodies against alpha 4 integrin did not block antigen recognition in vitro. Thus, we conclude that surface expression of alpha 4 integrin is important in CD4 T cell entry into brain parenchyma. A general conclusion of these studies is that alpha 4 integrins may be crucial in allowing activated effector T cells to leave blood and enter the brain and other tissues to clear infections.
rstB Regulates Expression of the Photobacterium damselae subsp. damselae Major Virulence Factors Damselysin, Phobalysin P and Phobalysin C

The marine pathogenic bacterium Photobacterium damselae subsp. damselae causes septicemia in marine animals and in humans. The pPHDD1 plasmid-encoded hemolysins damselysin (Dly) and phobalysin P (PhlyP), and the chromosome-encoded hemolysin phobalysin C (PhlyC) constitute its main virulence factors. However, the mechanisms by which expression of these three hemolysins is regulated remain unknown. Here we report the isolation of a mini-Tn10 transposon mutant which showed a strong impairment in its hemolytic activity. The transposon disrupted a putative sensor histidine kinase gene vda_000600 (rstB), which together with vda_000601 (rstA) is predicted to encode a putative two-component regulatory system. This system showed to be homologous to the Vibrio cholerae CarSR/VprAB and Escherichia coli RstAB systems. Reconstruction of the mutant by allelic exchange of rstB showed equal impairment in hemolysis, and complementation with a plasmid expressing rstAB restored hemolysis to wild-type levels. Remarkably, we demonstrated by promoter expression analyses that the reduced hemolysis in the rstB mutant was accompanied by a strong decrease in transcription activities of the three hemolysin genes dly (damselysin), hlyApl (phobalysin P) and hlyAch (phobalysin C). Thus, RstB, encoded in the small chromosome, regulates plasmid and chromosomal virulence genes. We also found that reduced expression of the three virulence genes correlated with a strong decrease in virulence in a sea bass model, demonstrating that RstB constitutes a master regulator of the three P. damselae subsp. damselae hemolysins and plays critical roles in the pathogenicity of this bacterium. This study represents the first evidence of a direct role of a RstAB-like system in the regulation of bacterial toxins.