gebhart/patrepeval huggingface dataset:
Both Stat3-Activation and Stat3-Independent BCL2 Downregulation Are Important for Interleukin-6–Induced Apoptosis of 1A9-M Cells (1999)

Abstract A unique subclone of a bone marrow-derived stromal cell line, BMS2.4, produces soluble factors that inhibit proliferation of several types of hematopoietic cell lines. An understanding of these molecules may be informative about negative regulatory circuits that can potentially limit blood cell formation. We used expression cloning to identify interleukin-6 (IL-6) as one factor that suppressed growth of a pre-B–cell variant line, 1A9-M. Moreover, IL-6 induced macrophage-differentiation and apoptosis of 1A9-M cells. During this process, IL-6 downregulated expression of BCL2 in 1A9-M cells and stimulated BCL-XL expression, but had no effect on p53, Bax, or Bak gene expression. Mechanisms for transduction of IL-6–induced signals were then evaluated in IL-6–stimulated 1A9-M cells. Whereas the signal transducer and activator of transcription 3 (Stat3) was phosphorylated and activated, there was no effect on either Stat1 or Stat5. The importance of BCL2 and Stat3 on IL-6–induced macrophage-differentiation and apoptosis was studied with 1A9-M cells expressing human BCL2 or a dominant-negative form of Stat3, respectively. IL-6–induced apoptosis, but not macrophage-differentiation, was blocked by continuously expressed BCL2. A dominant-negative form of Stat3 inhibited both macrophage-differentiation and apoptosis induced by IL-6. However, diminished Stat3 activity did not prevent IL-6–induced downregulation of the BCL2 gene. Therefore, activation of Stat3 is essential for IL-6–induced macrophage-differentiation and programmed cell death in this model. Whereas overexpression of BCL2 abrogates the apoptotic response, Stat3-independent signals appear to downregulate expression of the BCL2 gene.
Cytotoxic activity of the novel small molecule AKT inhibitor SC66 in hepatocellular carcinoma cells (2014)

Hepatocellular carcinoma (HCC) is characterized by limited response to current drug therapies. Here, we report that SC66, a novel AKT inhibitor, reduced cell viability in a dose- and time-dependent manner, inhibited colony formation and induced apoptosis in HCC cells. SC66 treatment led to a reduction in total and phospho-AKT levels. This was associated with alterations in cytoskeleton organization, a reduction in expression levels of E-cadherin, β-catenin and phospho-FAK, together with up-regulation of Snail protein levels. All these alterations were coupled with anoikis cell death induction. In addition, SC66 induced the production of reactive oxygen species (ROS) and DNA damage. Pre-treatment with the ROS scavenger N-Acetyl-cysteine (NAC) prevented SC66-induced cell growth inhibition and anoikis. SC66 significantly potentiated the effects of both conventional chemotherapeutic and targeted agents, doxorubicin and everolimus, respectively. In vivo, SC66 inhibited tumor growth of Hep3B cells in xenograft models, with a similar mechanism observed in the in vitro model. Taken together, these data indicate that the AKT inhibitor SC66 had antitumor effects on HCC cells. This was mediated by ROS production, induction of anoikis-mediated cell death and inhibition of the AKT cell survival pathway. Our results provide a rational basis for the use of SC66 in HCC treatment.
Thermodynamic Binding Studies of Lectins from the Diocleinae Subtribe to Deoxy Analogs of the Core Trimannoside of Asparagine-linked Oligosaccharides (2000)

Lectins from seven different species of the Diocleinae subtribe have been recently isolated and characterized in terms of their carbohydrate binding specificities (Dam, T. K., Cavada, B. S., Grangeiro, T. B., Santos, C. F., de Sousa, F. A. M., Oscarson, S., and Brewer, C. F. (1998) J. Biol. Chem. 273, 12082-12088). The lectins included those from Canavalia brasiliensis, Cratylia floribunda, Dioclea rostrata, Dioclea virgata, Dioclea violacea, and Dioclea guianensis. All of the lectins exhibited specificity for Man and Glc residues, but much higher affinities for the branched chain trimannoside, 3,6-di-O-(alpha-d-mannopyranosyl)-d-mannose, which is found in the core region of all asparagine-linked carbohydrates. In the present study, isothermal titration microcalorimetry is used to determine the binding thermodynamics of the above lectins, including a new lectin from Canavalia grandiflora, to a complete series of monodeoxy analogs of the core trimannoside. From losses in the affinity constants and enthalpies of binding of certain deoxy analogs, assignments are made of the hydroxyl epitopes on the trimannoside that are involved in binding to the lectins. The pattern of binding of the deoxy analogs is similar for all seven lectins, and similar to that of concanavalin A which is also a member of the Diocleinae subtribe. However, differences in the magnitude of the thermodynamic binding parameters of the lectins are observed, even though the lectins possess conserved contact residues in many cases, and highly conserved primary sequences. The results indicate that non-contact residues in the lectins, even those distant from the binding sites, modulate their thermodynamic binding parameters.
A Universal Training Algorithm for Quantum Deep Learning (2019)

We introduce the Backwards Quantum Propagation of Phase errors (Baqprop) principle, a central theme upon which we construct multiple universal optimization heuristics for training both parametrized quantum circuits and classical deep neural networks on a quantum computer. Baqprop encodes error information in relative phases of a quantum wavefunction defined over the space of network parameters; it can be thought of as the unification of the phase kickback principle of quantum computation and of the backpropagation algorithm from classical deep learning. We propose two core heuristics which leverage Baqprop for quantum-enhanced optimization of network parameters: Quantum Dynamical Descent (QDD) and Momentum Measurement Gradient Descent (MoMGrad). QDD uses simulated quantum coherent dynamics for parameter optimization, allowing for quantum tunneling through the hypothesis space landscape. MoMGrad leverages Baqprop to estimate gradients and thereby perform gradient descent on the parameter landscape; it can be thought of as the quantum-classical analogue of QDD. In addition to these core optimization strategies, we propose various methods for parallelization, regularization, and meta-learning as augmentations to MoMGrad and QDD. We introduce several quantum-coherent adaptations of canonical classical feedforward neural networks, and study how Baqprop can be used to optimize such networks. We develop multiple applications of parametric circuit learning for quantum data, and show how to perform Baqprop in each case. One such application allows for the training of hybrid quantum-classical neural-circuit networks, via the seamless integration of Baqprop with classical backpropagation. Finally, for a representative subset of these proposed applications, we demonstrate the training of these networks via numerical simulations of implementations of QDD and MoMGrad.
Elastic, piezoelectric, dielectric properties of La/sub 3/Ga/sub 5.5/Ta/sub 0.5/O/sub 14/ single crystals (2002)

La/sub 3/Ga/sub 5.5/Ta/sub 0.5/O/sub 14/ (LGT) crystals could be useful for frequency control applications because the combination of electromechanical coupling constant and thermal stability is very promising. Y-cut directly have zero value of first order temperature coefficient. Second order temperature coefficient is near of La/sub 3/Ga/sub 3/SiO/sub 14/ (LGS) figure. The present paper is devoted to measurements of elastic, piezoelectric and dielectric properties of LGT at room temperature and temperature dependencies of some sound mode velocities.
Fiber Twisting- and Bending-Induced Adiabatic/Nonadiabatic Super-Mode Transition in Coupled Multicore Fiber (2015)

The characteristics of power transfer between super-modes in coupled multicore fiber are investigated numerically and experimentally. We reveal that fiber twisting and macrobending cause mode coupling through an adiabatic/nonadiabatic process, which is different from the mode coupling caused by structural perturbation, namely microbending. We also investigate the impulse response characteristics of coupled two-core fibers, and find that there is an optimum core pitch for minimizing the complexity of the MIMO processing. Finally, we conduct a 4 × 4 MIMO transmission experiment using two-core fibers to evaluate their transmission characteristics. We show that strongly coupled multicore fiber can reduce the quality difference between the received signals even when the transmission line has large core-dependent gain/loss values.
Content extraction signatures using XML digital signatures and custom transforms on-demand (2003)

Content Extraction Signatures (CES) enable selective disclosure of verifiable content, provide privacy for blinded content, and enable the signer to specify the content the document owner is allowed to extract or blind. Combined, these properties give what we call CES functionality. In this paper we describe our work in developing custom transform algorithms to expand the functionality of an XML Signature to include CES functionality in XML Signature Core Validation.We also describe a custom revocation mechanism and our implementation for non-XML content where the custom transforms are dynamically loaded demonstrating that custom signing and verification is not constrained to a 'closed system'. Through the use of dynamic loading we show that a verifier can still verify an XML Signature-compliant signature even though a custom signature was produced.
Credit risk assessment model of small and medium-sized enterprise based on logistic regression (2015)

Small and medium-sized enterprises play a very important role in China's economic and social development. Their development is inseparable from the financial support, and the development of credit business is also an important aspect of bank's operation. At the time of solving the problem of financing difficulties of small and medium-sized enterprises, how to manage credit risk will become an important subject to study. In this paper, we choose 50 money-borrowing enterprises' financial data in a commercial bank as samples to construct logistic risk assessment model. We make regression analysis, Hosmer-Lemeshow test and Hosmer-Lemeshow randomness test. The empirical results show that the logistic risk assessment model has good fitness of the data.
Artifact vs. Anatomy: Dealing with Conflict of Geometric Modeling Descriptions (2007)

<div class="htmlview paragraph">In applications ranging from design of customized vehicle interiors to virtual testing of biomedical devices, the processes of modeling, design and analysis involve the simultaneous treatment of artifacts (i.e., parts designed by humans) and anatomical structures. An inherent conflict arises because the geometric descriptions are completely different. Artifact descriptions are typically the output of computer-aided design (CAD) software and consist of a collection of parametric patches that comprise the boundary of the artifact. In stark contrast, the native description of an anatomical structure typically consists of an image stack obtained using a volumetric scanning technology such as computed tomography (CT) or magnetic resonance imaging (MRI). Current practice for simultaneously dealing with both categories of entities involves working primarily in the world of CAD. The scanner data must be processed to determine segmentation (i.e., to decide which voxel belongs to each object of interest), and then the segmented results are converted to traditional boundary representation (b-rep) CAD models. However, the CAD models consist of such large numbers of triangles (often on the order of 10<sup>6</sup> or 10<sup>7</sup>) that performing standard CAD operations becomes problematic. Most traditional CAD systems are designed to deal with environments composed of at most 1000's of individual objects with tens of thousands of individual surfaces (beyond which many CAD systems- performance is so slow as to have effectively failed).The question then arises whether forcing everything into the traditional CAD environment is really the best approach. If anatomical structures have more complicated geometry than CAD artifacts, does it make sense to work with anatomy in the CAD environment? In this paper we present a modeling representation whose basic data is much closer to the natural representation of scanned objects in that the representation is based on a 3D grid of data. While the raw scan data is too noisy to be directly useful, the grid of signed distance values that are obtained by recently developed segmentation algorithms is well behaved and amenable to accurate interpolation by wavelets. Thus we present a modeling approach that employs wavelets to interpolate signed distance values resulting in useful function-based representations (f-reps). We present examples to show how this approach produces models of scanned structures, provides for import of artifacts, and supports simultaneous modeling of artifacts and anatomy.</div>
Effects of the magnetic resonance contrast medium ferrioxamine methanesulfonate on systemic and renal hemodynamics in the anesthetized dog. (1988)

Ferrioxamine methanesulfonate (S-FDF) is a new magnetic resonance (MR) contrast agent developed to improve magnetic resonance imaging of the abdomen and pelvis. This stable complex of deferoxamine methanesulfonate and iron is excreted in the urine by glomerular filtration modified by active renal tubular resorption. This study examines the acute systemic and renal hemodynamic responses to this agent after intravenous administration either as an infusion of 25 mg/kg over 5 minutes or as a rapid bolus at a dose of 50 mg/kg. In eight anesthetized dogs, renal plasma flow (RPF) was measured with an electromagnetic flowmeter, and GFR was determined by the renal extraction of technetium-99m-DTPA. Mean arterial pressure (MAP), pulse rate, and a lead II ECG were assessed. At a dose of 25 mg/kg over 5 minutes, MAP decreased significantly (control 146.0 +/- 6.5 mm Hg vs. 107 +/- 18 mm Hg at 2 minutes; P less than .05). In two of the eight animals, the MAP dropped below 60 mm Hg. Significant decreases in GFR and RPF also were noted. All four of the animals receiving the rapid injection of S-FDF experienced profound hypotension (MAP less than 50 mm Hg). The drop in heart rate from 152 +/- 11.6 bpm to 121 +/- 4.9 bpm was associated with a marked depression of the ST wave in the lead II ECG. Further animal studies are needed to assess the mechanism of toxicity and a potential synergism of action with pentobarbital anesthesia.
Fabrication of petrochemical and viral resistant membranes (2012)

Physical interaction between two bulk media occurs mainly at the surface interface. The surface properties of materials therefore dictate how a system will respond to different influences, while being just a fraction of the entire volume. Alteration of a surface can therefore have a significant effect on a system. In this thesis the functionalization of surfaces via covalent attachment of short chained molecules was undertaken to manipulate surface-surface interactions for different outcomes. The separation and purification of bulk media of impurities has always been undertaken. Many different processes exist, however the removal of impurities from dynamic or open systems remains a problem. The use of filtration technologies remains the best option in this type of system. In filtration technology membranes are employed to selectively remove one or more elements from another generally under a driving force. The selectivity of a membrane has either traditionally relied on either physical attributes such as pore size or chemical attributes such as charge, van der Waals etc. In this thesis we propose the use of organically functionalized ceramic nanoparticles alumoxanes to act as a coating of the side walls of the fibers of a base bulk fabric material Nomex Â© . The side chain of cysteic acid has been found to be extremely hydrophilic due in part to its Zwitter ionic properties. The use of hydrophilic cysteic acid alumoxane was used as part of a composite membrane to screening hydrocarbons. Doping of this membrane with cysteic acid ferroxane the iron analogue of alumoxane was used as a membrane to screen MS2 bacteriophage.
Functional expression of a novel human neurokinin-3 receptor homolog that binds [ <sup>3</sup> H]senktide and [ <sup>125</sup> I-MePhe <sup>7</sup> ]neurokinin B, and is responsive to tachykinin peptide agonists (1997)

In 1992, Xie et al. identified a cDNA sequence in the expression cloning search for the kappa opioid receptor. When the cDNA was expressed in Cos-7 cells, binding of opioid compounds was observed to be of low affinity and without kappa, mu, or delta selectivity [Xie, G.-X., Miyajima, A. and Goldstein, A. (1992) Proc. Natl. Acad. Sci. USA 89, 4124-4128]. This cDNA was highly homologous to the human neurokinin-3 (NK-3) receptor sequence, and displayed lower homology to NK-1 and NK-2 sequences. This sequence was stably expressed in Chinese hamster ovary cells, which do not express neurokinin receptors naturally, and ligand binding and second messenger characteristics were compared with a human NK-3 receptor. The NK-3 receptor homolog bound [3H] senktide with a Kd of 39 nM, similar to that of the NK-3 receptor. The rank order of tachykinin peptides competing for [3H]senktide binding at the NK-3 receptor homolog was [MePhe7]neurokinin B > senktide > substance P = neurokinin A > neurokinin B. This cell line also bound [125I-MePhe7]neurokinin B; however, neurokinin B was an effective competitor. Tachykinin peptides stimulated both inositol phospholipid hydrolysis and arachidonic acid release at NK-3 and NK-3 receptor homolog cell lines, with similar rank orders of potency of [MePhe7] neurokinin B = neurokinin B = senktide > NKA = substance P. These results indicate that expression of the NK-3 receptor homolog cDNA in the Chinese hamster ovary cell system induces the expression of a receptor site with many similarities but certain key differences from that of the human NK-3 receptor. The results are discussed with reference to the existence of a novel human tachykinin receptor.
Growth and metastasis of tumor in organ culture (1963)

A vitro growth of malignant tumors in their normal solid configuration would be an invaluable aid in the study of factors influencing metastases, cancer chemotherapy, and relationships between tumor and host tissue. Such a system would also open studies of functioning tumors and their relationship with circulating stimulatory substances. A system for the perfusion of isolated, small organs was developed in this laboratory as a by-product of an investigation originally designed to test the efficacy of hemoglobin-plasma solutions as a blood substitute for prolonged extracorporeal perfusion. Crystalline hemoglobin in plasma or serum was perfused through isolated organs, (thyroid, kidney, intestine) for several days in a small apparatus using a 50-cc.
Nonlinear adaptive prediction of speech with a pipelined recurrent neural network (1998)

New learning algorithms for an adaptive nonlinear forward predictor that is based on a pipelined recurrent neural network (PRNN) are presented. A computationally efficient gradient descent (GD) learning algorithm, together with a novel extended recursive least squares (ERLS) learning algorithm, are proposed. Simulation studies based on three speech signals that have been made public and are available on the World Wide Web (WWW) are used to test the nonlinear predictor. The gradient descent algorithm is shown to yield poor performance in terms of prediction error gain, whereas consistently improved results are achieved with the ERLS algorithm. The merit of the nonlinear predictor structure is confirmed by yielding approximately 2 dB higher prediction gain than a linear structure predictor that employs the conventional recursive least squares (RLS) algorithm.
Solar irradiance forecasting at multiple time horizons and novel methods to evaluate uncertainty (2012)

As an energy resource, solar energy provides a cleaner alternative to the conventional power\ngeneration systems and therefore solar energy has the potential to help achieve lower emissions\nstandards as well to help provide domestic energy security. A major challenge, however, is the nondispatchability and variability of the solar resource which makes it necessary to develop forecasting methodologies in order to safely integrate with the electric grid. As dictated by current electricity markets, power generation is dispatched according to day-ahead unit commitment as well as 1-hour ahead and 15-minutes for load-following services. In order to integrate large penetration levels of solar energy into the current systems, forecasting at these time intervals are necessary. In this work, we develop and evaluate several solar irradiance forecast models for multiple-time horizons. The 1-day ahead forecasting models are based on forecasted elements from the National Weather System's (NWS) forecasting database (NDFD). The 1-hour ahead forecasting models are based on sky cover indices derived from ground measurements including solar and infrared radiometers as well as a sky imager and we also develop satellite-based models that utilize neural networks for time-series predictions. For very short-term forecasts of &lt; 15-minutes ahead, we present a solar forecasting application using detailed image processing of a sky imager. Where possible, these models are compared to existing models in the literature. Because various authors use different benchmarks and forecast model quality measures, we also outline procedure that allows the comparisons of different forecasting models and discuss why the procedure is a robust indicator of forecasting skill. In determining forecasting skill, it is necessary to quantify variability. Quantifying variability is also important for analyzing the economic impacts which are introduced by the addition of variability from a solar power system, which is discussed here in some detail. A case study of the economic impacts due to solar high-frequency variability is presented for the University of California Merced and a 1-MW photovoltaic plant.