gebhart/patrepeval huggingface dataset:
Oncogenic EGFR signaling cooperates with loss of tumor suppressor gene functions in gliomagenesis (2009)

Glioblastoma multiforme (GBM) is a highly lethal brain tumor for which little treatment is available. The epidermal growth factor receptor (EGFR) signaling pathway is thought to play a crucial role in GBM pathogenesis, initiating the early stages of tumor development, sustaining tumor growth, promoting infiltration, and mediating resistance to therapy. The importance of this pathway is highlighted in the fact that EGFR is mutationally activated in over 50% of GBM tumors. Consistent with this, we show here that concomitant activation of wild-type and/or mutant (vIII) EGFR and ablation of Ink4A/Arf and PTEN tumor suppressor gene function in the adult mouse central nervous system generates a fully penetrant, rapid-onset high-grade malignant glioma phenotype with prominent pathological and molecular resemblance to GBM in humans. Studies of the activation of signaling events in these GBM tumor cells revealed notable differences between wild-type and vIII EGFR-expressing cells. We show that wild-type EGF receptor signals through its canonical pathways, whereas tumors arising from expression of mutant EGFR(vIII) do not use these same pathways. Our findings provide critical insights into the role of mutant EGFR signaling function in GBM tumor biology and set the stage for testing of targeted therapeutic agents in the preclinical models described herein.
Machine learning approaches for small data in sensor fusion applications (2018)

Machine learning approaches like deep neural networks have proven to be very successful in many domains. However, they require training on a huge volumes of data. While these approaches work very well in a few selected domains where a large corpus of training data exists, they shift the bottleneck in development of machine learning applications to the data acquisition phase and are difficult to use in domains where training data is hard to acquire. For sensor fusion applications in coalition operations, access to good training data that will be suitable for real-life applications is hard to get. The training data sets available are limited in size. For these domains, we need to explore approaches for machine learning which can work with small amounts of data. In this paper, we will look at the current and emerging approaches which allow us to build machine learning models when access to the training data is limited. The approaches examined include statistical machine learning, transfer learning, synthetic data generation, semi-supervised learning and one-shot learning.
Tracking Cloned Electronic Components using a Consortium-based Blockchain Infrastructure (2020)

The globalized electronics supply chain relies on many untrusted entities to move components across the world. This, in turn, increases the threat of counterfeit integrated circuits (ICs) being inserted into the supply chain then installed into mission critical systems. A number of methods for detecting counterfeit ICs exist; however, applications of models to rapidly and non-destructively detect cloned ICs are lacking. Moreover, no trustworthy data storage and verification mechanism exists in the current supply chain that can provide identification and tracking of authentic and cloned ICs. In this work, we propose a novel framework to address these detection and tracking problems at each stage of the electronics supply chain. We leverage a consortium-style blockchain infrastructure to offer tamper-proof data enrollment and verification. We propose the algorithm and model for confidently identifying authentic and cloned ICs, and offer next stage tracking by verifying general and restricted datasets in the blockchain. The experimental result demonstrates how entities can verify and track the cloned chips with a given level of confidence in the presence of noise.
Functional Significance of Point Mutations in Stress Chaperone Mortalin and Their Relevance to Parkinson Disease (2015)

Mortalin/mtHsp70/Grp75 (mot-2), a heat shock protein 70 family member, is an essential chaperone, enriched in cancers, and has been shown to possess pro-proliferative and anti-apoptosis functions. An allelic form of mouse mortalin (mot-1) that differs by two amino acids, M618V and G624R, in the C terminus substrate-binding domain has been reported. Furthermore, genome sequencing of mortalin from Parkinson disease patients identified two missense mutants, R126W and P509S. In the present study, we investigated the significance of these mutations in survival, proliferation, and oxidative stress tolerance in human cells. Using mot-1 and mot-2 recombinant proteins and specific antibodies, we performed screening to find their binding proteins and then identified ribosomal protein L-7 (RPL-7) and elongation factor-1 α (EF-1α), which differentially bind to mot-1 and mot-2, respectively. We demonstrate that mot-1, R126W, or P509S mutant (i) lacks mot-2 functions involved in carcinogenesis, such as p53 inactivation and hTERT/hnRNP-K (heterogeneous nuclear ribonucleoprotein K) activation; (ii) causes increased level of endogenous oxidative stress; (iii) results in decreased tolerance of cells to exogenous oxidative stress; and (iv) shows differential binding and impact on the RPL-7 and EF-1α proteins. These factors may mediate the transformation of longevity/pro-proliferative function of mot-2 to the premature aging/anti-proliferative effect of mutants, and hence may have significance in cellular aging, Parkinson disease pathology, and prognosis.
Rotordynamic Computational and Experimental Characterization of a Convergent Honeycomb Seal Tested With Negative Pre-Swirl, High Pressure With Static Eccentricity and Angular Misalignment (2016)

Hole-pattern or honeycomb seals have been commonly used for many years in the Oil &amp; Gas industry as damper seals for turbomachinery. The main motivation has been to introduce additional damping to improve the shaft rotordynamic stability operating under high pressure conditions. Experience has shown that the dynamic and even static characteristics of those seals are very sensitive to the operating clearance profile as well as the installation tolerances. Rotordynamic stability is related not only to the seal effective damping but to the effective stiffness as well. In fact, for this kind of seal, the effective stiffness can be high enough to alter the rotor system’s natural frequency. The seal stiffness is strictly related to the tapering contour: if the clearance profile changes from divergent to convergent, the effective stiffness may change from a strong negative to a strong positive magnitude, thus avoiding the rotor natural frequency drop as it is detrimental for the stability. Unfortunately the effective damping is reduced at the same time but this can be improved using proper devices to keep the pre-swirl low or even negative (e.g. swirl brakes, shunt holes). This paper presents the results from an extended test campaign performed in a high-speed rotor test rig equipped with active magnetic bearings working under high pressure (14krpm, 200bar gas inlet pressure), with the aim to validate the rotordynamic characteristics of a negative pre-swirl, convergent honeycomb seal and demonstrate its ability to effectively act as a gas bearing as well as a seal. The test plan included variations of inlet pressure, differential pressure (given the same inlet pressure) as well as rotational speed in order to fully validate the seal behaviour. This kind of test was performed in a “dynamic mode”, exciting the spinning test rotor through a pair of AMBs along linear orbits. Additionally the impact of the seal to rotor static eccentricity and the seal to rotor angular misalignment were both experimentally investigated and compared to relevant CFD simulations. This kind of test was performed in a “static mode”, imposing through the AMBs the required eccentricity / angular misalignment and then measuring the forces needed to keep the rotor in the original position. “Dynamic mode” test was also performed in order to check the impact of the seal static eccentricity on its dynamic behaviour. Finally the test results were compared with predictions from a state of the art bulk flow code in order to check the predictability level for future design applications.
Interlaced systems and recursive designs for global stabilization (1997)

Interlaced systems constitute a class of systems only characterized by the zero entries of their matrix configuration and a local stabilizability condition. All these systems are globally stabilizable by a recursive design procedure which combines steps of backstepping and forwarding. When a nonlinear system misses this structural characterization. other types of conditions (sign, growth) are needed to ensure global stabilization.
Total synthesis of (-)-specionin (1987)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTTotal synthesis of (-)-specioninDennis P. Curran, Patricia B. Jacobs, Richard L. Elliott, and Byeang Hyean KimCite this: J. Am. Chem. Soc. 1987, 109, 17, 5280–5282Publication Date (Print):August 1, 1987Publication History Published online1 May 2002Published inissue 1 August 1987https://pubs.acs.org/doi/10.1021/ja00251a044https://doi.org/10.1021/ja00251a044research-articleACS PublicationsRequest reuse permissionsArticle Views692Altmetric-Citations51LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose Get e-Alerts
An Implantable Centrifugal Blood Pump for Long Term Circulatory Support (1997)

A compact centrifugal blood pump was developed as an implantable left ventricular assist system. The impeller diameter is 40 mm and the pump dimensions are 55 x 64 mm. This first prototype was fabricated from titanium alloy, resulting in a pump weight of 400 g including a brushless DC motor. Weight of the second prototype pump was reduced to 280 g. The entire blood contacting surface is coated with diamond like carbon to improve blood compatibility. Flow rates of over 7 L/min against 100 mmHg pressure at 2,500 rpm with 9 W total power consumption have been measured. A newly designed mechanical seal with a recirculating purge system ("Cool-Seal") is used as a shaft seal. In this seal system, seal temperature is kept under 40 degrees C to prevent heat denaturation of blood proteins. Purge fluid also cools the pump motor coil and journal bearing. The purge fluid is continuously purified and sterilized by an ultrafiltration filter incorporated into the paracorporeal drive console. In vitro experiments with bovine blood demonstrated an acceptably low hemolysis rate (normalized index of hemolysis = 0.005 +/- 0.002 g/100 L). In vivo experiments are currently ongoing using calves. Via left thoracotomy, left ventricular apex-descending aorta bypass was performed utilizing a PTFE (Polytetrafluoroethylene) vascular graft, with the pump placed in the left thoracic cavity. In two in vivo experiments, pump flow rate was maintained at 5-8 L/min, and pump power consumption remained stable at 9-10 W. All plasma free hemoglobin levels were measured at < 15 mg/dl. The seal system has demonstrated good seal capability with negligible purge fluid consumption (< 0.5 ml/ day). Both animals remain under observation after 162 and 91 days of continuous pump function.
Comparison of the simulation and experiments of the nitride-based UV light emitting diodes (2007)

In attempt to prepare a high performance Al<sub>x</sub>Ga<sub>1-x</sub>N based UV-B LED, a computer simulation has been performed on a typical UV-LED structure to find out the effect of threading dislocations on non-radiative recombination process. UVB LED structures were formed on using GaN and AlN based layers for comparison. Cracks were generated in the device structure formed on GaN underlayer. No cracks were observed on the device structure formed on AlN under layer. Much better structure was formed when the base AlN was grown by high temperature MOVPE.
ChemInform Abstract: MAGNETIC RESONANCE STUDY OF TITANIUM(IV) OXIDE, VANADIUM(V) OXIDE/TITANIUM(IV) OXIDE, AND VANADIUM(V) OXIDE SUPPORTED RHODIUM CATALYSTS (1985)

Abstract Die Ergebnisse von ESR‐ und NMR‐Untersuchungen der Reduktion von Rh/V2O5‐ und Rh/TiO2‐ Vzos‐Katalysatoren durch H 2 bei Temp. g 298 K sind mit der Bildung von H ‐Spezies während der Metallreduktion sowie von spillover‐H‐Atomen während der Trägerreduktion vereinbar.
MicroRNA-196b Regulates the Homeobox B7-Vascular Endothelial Growth Factor Axis in Cervical Cancer (2013)

The down-regulation of microRNA-196b (miR-196b) has been reported, but its contribution to cervical cancer progression remains to be investigated. In this study, we first demonstrated that miR-196b down-regulation was significantly associated with worse disease-free survival (DFS) for cervical cancer patients treated with combined chemo-radiation. Secondly, using a tri-modal approach for target identification, we determined that homeobox-B7 (HOXB7) was a bona fide target for miR-196b, and in turn, vascular endothelial growth factor (VEGF) was a downstream transcript regulated by HOXB7. Reconstitution of miR-196b expression by transient transfection resulted in reduced cell growth, clonogenicity, migration and invasion in vitro, as well as reduced tumor angiogenesis and tumor cell proliferation in vivo. Concordantly, siRNA knockdown of HOXB7 or VEGF phenocopied the biological effects of miR-196b over-expression. Our findings have demonstrated that the miR-196b/HOXB7/VEGF pathway plays an important role in cervical cancer progression; hence targeting this pathway could be a promising therapeutic strategy for the future management of this disease.
Multiple Functions of Aromatic-Carbohydrate Interactions in a Processive Cellulase Examined with Molecular Simulation (2011)

Proteins employ aromatic residues for carbohydrate binding in a wide range of biological functions. Glycoside hydrolases, which are ubiquitous in nature, typically exhibit tunnels, clefts, or pockets lined with aromatic residues for processing carbohydrates. Mutation of these aromatic residues often results in significant activity differences on insoluble and soluble substrates. However, the thermodynamic basis and molecular level role of these aromatic residues remain unknown. Here, we calculate the relative ligand binding free energy by mutating tryptophans in the Trichoderma reesei family 6 cellulase (Cel6A) to alanine. Removal of aromatic residues near the catalytic site has little impact on the ligand binding free energy, suggesting that aromatic residues immediately upstream of the active site are not directly involved in binding, but play a role in the glucopyranose ring distortion necessary for catalysis. Removal of aromatic residues at the entrance and exit of the Cel6A tunnel, however, dramatically impacts the binding affinity, suggesting that these residues play a role in chain acquisition and product stabilization, respectively. The roles suggested from differences in binding affinity are confirmed by molecular dynamics and normal mode analysis. Surprisingly, our results illustrate that aromatic-carbohydrate interactions vary dramatically depending on the position in the enzyme tunnel. As aromatic-carbohydrate interactions are present in all carbohydrate-active enzymes, these results have implications for understanding protein structure-function relationships in carbohydrate metabolism and recognition, carbon turnover in nature, and protein engineering strategies for biomass utilization. Generally, these results suggest that nature employs aromatic-carbohydrate interactions with a wide range of binding affinities for diverse functions.
Hijacking antibody-induced CTLA-4 lysosomal degradation for safer and more effective cancer immunotherapy (2019)

It remains unclear why the clinically used anti-CTLA-4 antibodies, popularly called checkpoint inhibitors, have severe immunotherapy-related adverse effects (irAEs) and yet suboptimal cancer immunotherapeutic effects (CITE). Here we report that while irAE-prone Ipilimumab and TremeIgG1 rapidly direct cell surface CTLA-4 for lysosomal degradation, the non-irAE-prone antibodies we generated, HL12 or HL32, dissociate from CTLA-4 after endocytosis and allow CTLA-4 recycling to cell surface by the LRBA-dependent mechanism. Disrupting CTLA-4 recycling results in robust CTLA-4 downregulation by all anti-CTLA-4 antibodies and confers toxicity to a non-irAE-prone anti-CTLA-4 mAb. Conversely, increasing the pH sensitivity of TremeIgG1 by introducing designed tyrosine-to-histidine mutations prevents antibody-triggered lysosomal CTLA-4 downregulation and dramatically attenuates irAE. Surprisingly, by avoiding CTLA-4 downregulation and due to their increased bioavailability, pH-sensitive anti-CTLA-4 antibodies are more effective in intratumor regulatory T-cell depletion and rejection of large established tumors. Our data establish a new paradigm for cancer research that allows for abrogating irAE while increasing CITE of anti-CTLA-4 antibodies.
The effect of carrier gas pressure on vapor phase nucleation experiments using a thermal diffusion cloud chamber (1999)

Recent measurements of critical supersaturations for the vapor phase homogeneous nucleation of several substances using a diffusion cloud chamber technique exhibit a dependence on the pressure of the carrier gas used in the experiments. A model of droplet growth and motion in a diffusion cloud chamber, combined with the density and temperature profiles of the chamber is presented to explain the pressure dependent results. The model demonstrates that at higher carrier gas pressures the growth of the droplets is retarded and the optical scattering signal from the particles is reduced. It is concluded that the observed effect may not result from a pressure dependence of the nucleation rate, but from a pressure dependence of the droplet growth and motion.
High resolution x-ray tomography in an electron microprobe (1996)

Conversion of an electron microprobe for use as an x-ray microtomograph is described. Only minor modifications are required, indeed several of the utilities of the microprobe can be used to ensure high resolution radiography and tomography. System performance was evaluated by analysis of glass fiber reinforced polymer composites and of a carbonate reservoir rock. Individual glass fibers of 10 and 20 μm diameter are clearly visible in the former. In the latter, comparison with scanning electron micrographs shows reliable reconstruction of external morphology. In addition, internal pore structure can be studied a posteriori using the tomography data. Spatial resolutions in radiography of better than 3 μm and in tomography of 10 μm have been demonstrated. Further improvements to the detector system and increased data handling capacity are possible to achieve 1 μm resolution tomographic images.
Rational Design of New Binding Specificity by Simultaneous Mutagenesis of Calmodulin and a Target Peptide (2006)

ABSTRACT: Calcium-saturated calmodulin (CaM) binds and influences the activity of a varied collection of target proteins in most cells. This promiscuity underlies the role of CaM as a shared participant in calcium-dependent signal transduction pathways but imposes a handicap on popular CaM-based calcium biosensors, which display an undesired tendency to cross-react with cellular proteins. Designed CaM/ target pairs that retain high affinity for one another but lack affinity for wild-type CaM and its natural interaction partners would therefore be useful as sensor components and possibly also as elements of “synthetic ” cellular-signaling networks. Here, we have adopted a rational approach to creating suitably modified CaM/target complexes by using computational design methods to guide parallel site-directed mutagenesis of both binding partners. A hierarchical design procedure was applied to suggest a small number of complementary mutations on CaM and on a peptide ligand derived from skeletal-muscle lightchain kinase (M13). Experimental analysis showed that the procedure was successful in identifying CaM and M13 mutants with novel specificity for one another. Importantly, the designed complexes retained an affinity comparable to the wild-type CaM/M13 complex. These results represent a step toward the creation of CaM and M13 derivatives with specificity fully orthogonal to the wild-type proteins and show that qualitatively accurate predictions may be obtained from computational methods applied simultaneously
DQLearn : A Toolkit for Structured Data Quality Learning (2020)

Data Quality (DQ) has been one of the key focuses as Data Analytics and Artificial Intelligence (AI) fields continue to grow. Yet, data quality analysis has mostly been a disjointed, ad-hoc, and cumbersome process in the overall data analysis workflow. There have been ongoing attempts to formalize this process, but the solutions that have come out are not universally applicable. Most of the proposed solutions try to address the problem of data quality from a limited perspective and suc-cessfully address only a subset of all challenges. These solutions fail to translate to other domains due to a lack of structure. In this paper, we present DQLearn, a toolkit for structured data quality learning. We start by presenting the core principle on which we build our library and introduce the four components that provide a solid base to address the needs of the data quality problem. Then, we showcase our automation structure - "Workflows", and the two optimization techniques equipped with it, that help the users to structure their learning problem very easily. Next, we discuss four important scenarios of the DQ Workflows in the overall life-cycle. Finally, we demonstrate the utility of the proposed toolkit with public datasets and show benchmark results from optimization experiments.
Differential Camera Tracking through Linearizing the Local Appearance Manifold (2007)

The appearance of a scene is a function of the scene contents, the lighting, and the camera pose. A set of n-pixel images of a non-degenerate scene captured from different perspectives lie on a 6D nonlinear manifold in R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> . In general, this nonlinear manifold is complicated and numerous samples are required to learn it globally. In this paper, we present a novel method and some preliminary results for incrementally tracking camera motion through sampling and linearizing the local appearance manifold. At each frame time, we use a cluster of calibrated and synchronized small baseline cameras to capture scene appearance samples at different camera poses. We compute a first-order approximation of the appearance manifold around the current camera pose. Then, as new cluster samples are captured at the next frame time, we estimate the incremental camera motion using a linear solver. By using intensity measurements and directly sampling the appearance manifold, our method avoids the commonly-used feature extraction and matching processes, and does not require 3D correspondences across frames. Thus it can be used for scenes with complicated surface materials, geometries, and view-dependent appearance properties, situations where many other camera tracking methods would fail.