gebhart/patrepeval huggingface dataset:
Exosomal miRNAs: Novel Players in Viral Infection (2020)

Exosomes are secreted nanovesicles that are able to transfer their cargo (such as miRNAs) between cells. To determine to what extent exosomes and exosomal miRNAs are involved in the pathogenesis, progression and diagnosis of viral infections. The scientific literature (PubMed and Google Scholar) was searched from 1970 to 2019. The complex biogenesis of exosomes and miRNAs was reviewed. Exosomes contain both viral and host miRNAs that can be used as diagnostic biomarkers for viral diseases. Viral proteins can alter miRNAs, and conversely miRNAs can alter the host response to viral infections in a positive or negative manner. It is expected that exosomal miRNAs will be increasingly used for diagnosis, monitoring and even treatment of viral infections.
Correction: Telomere Dynamics in Human Cells Reprogrammed to Pluripotency (2010)

Background: Human induced pluripotent stem cells (IPSCs) have enormous potential in the development of cellular models of human disease and represent a potential source of autologous cells and tissues for therapeutic use. A question remains as to the biological age of IPSCs, in particular when isolated from older subjects. Studies of cloned animals indicate that somatic cells reprogrammed to pluripotency variably display telomere elongation, a common indicator of cell ''rejuvenation.'' Methodology/Principal Findings: We examined telomere lengths in human skin fibroblasts isolated from younger and older subjects, fibroblasts converted to IPSCs, and IPSCs redifferentiated through teratoma formation and explant culture. In IPSCs analyzed at passage five (P5), telomeres were significantly elongated in 6/7 lines by .40% and approximated telomere lengths in human embryonic stem cells (hESCs). In cell lines derived from three IPSC-teratoma explants cultured to P5, two displayed telomeres shortened to lengths similar to input fibroblasts while the third line retained elongated telomeres.
Model Driven Development of Security Aspects (2007)

The development of security-critical large-scale distributed software systems is a difficult and error prone process. As we learnt from practical experiences, it is especially difficult to manually define security policies, for example for access control. A human security administrator is not able to cope with the high complexity of the interactions of the application and the low level, platform specific security policy. Therefore, a new approach is needed to ease the definition of appropriate security policies. This paper shows how realisation of security aspects of a system can be automated to a great extend by applying model-driven software development techniques not only on functional properties. In the presented approach, UML models of the application's functional properties are flexibly augmented with security relevant information. Together with a high level security policy defined by the security administrator, this augmented functional model is then used in an automatic model transformation to generate the platform specific security policy. With this approach, which supports the separation of concerns in model based software engineering, we can automatically generate security-critical applications for different middleware platforms like SecureMiddleware, which is an extended implementation of the CORBA Component Model with improved support for non functional properties like security. The concepts, platforms and tools presented in the paper are currently used for the development of several large-scale and secure applications, for example for building a Virtual Air-Space Management System with strong security requirements.
Reconfiguring structured light beams using nonlinear metasurfaces (2017)

We demonstrate a nonlinear metasurface made of nanostructured chalcogenide glass. We combined on- and off-resonance nanostructures to realize reconfigurable structured light beam that switches between the Hermit-Gaussian and vortex shape depending on its own intensity.
A comparison of two anti‐neuraminidase monoclonal antibodies by complement activation (1982)

The specificities of two anti-neuraminidase monoclonal antibodies have been compared by their ability to fix complement. They were found to differ to some extent in their reactivity with a range of N2 influenza virus. Thus, as in the case of anti-hemagglutinin antibodies, anti-neuraminidase monoclonal antibodies are able to detect subtle structural changes in the vital antigen. Although both monoclonal antibodies fixed complement with intact virus, neither one fixed complement when complexed with isolated neuraminidase "heads".
Implementation of New Process Models for Tailored Polymer Composite Structures into Processing Software Packages (2010)

This report describes the work conducted under the Cooperative Research and Development Agreement (CRADA) (Nr. 260) between the Pacific Northwest National Laboratory (PNNL) and Autodesk, Inc. to develop and implement process models for injection-molded long-fiber thermoplastics (LFTs) in processing software packages. The structure of this report is organized as follows. After the Introduction Section (Section 1), Section 2 summarizes the current fiber orientation models developed for injection-molded short-fiber thermoplastics (SFTs). Section 3 provides an assessment of these models to determine their capabilities and limitations, and the developments needed for injection-molded LFTs. Section 4 then focuses on the development of a new fiber orientation model for LFTs. This model is termed the anisotropic rotary diffusion - reduced strain closure (ARD-RSC) model as it explores the concept of anisotropic rotary diffusion to capture the fiber-fiber interaction in long-fiber suspensions and uses the reduced strain closure method of Wang et al. to slow down the orientation kinetics in concentrated suspensions. In contrast to fiber orientation modeling, before this project, no standard model was developed to predict the fiber length distribution in molded fiber composites. Section 5 is therefore devoted to the development of a fiber length attrition model in the mold. Sections 6 and 7 address the implementations of the models in AMI, and the conclusions drawn from this work is presented in Section 8.
Modelling, validating, and ranking of secure service compositions (2017)

Summary In the world of large‐scale applications, software as a service (SaaS) in general and use of microservices, in particular, is bringing service‐oriented architectures to a new level: Systems in general and systems that interact with human users (eg, sociotechnical systems) in particular are built by composing microservices that are developed independently and operated by different parties. At the same time, SaaS applications are used more and more widely by enterprises as well as public services for providing critical services, including those processing security or privacy of relevant data. Therefore, providing secure and reliable service compositions is increasingly needed to ensure the success of SaaS solutions. Building such service compositions securely is still an unsolved problem. In this paper, we present a framework for modelling, validating, and ranking secure service compositions that integrate both automated services as well as services that interact with humans. As a unique feature, our approach for ranking services integrates validated properties (eg, based on the result of formally analysing the source code of a service implementation) as well as contractual properties that are part of the service level agreement and, thus, not necessarily ensured on a technical level.
Integration of local pattern elements into a global shape in human vision (1997)

The spatial extent of the cortical filters selective for different spatial frequencies and orientations is limited. We studied psychophysically how information from the local filters is integrated into global pattern shapes, i.e., whether performance in the identification of a global pattern consisting of small, locally oriented Gabor elements depends on the orientations of those elements. The observer was presented with an E-like stimulus pattern shape comprised of oriented Gabor patches on a blank background, and the performance measure was the threshold contrast for identifying the orientation of the E pattern (four possible rotated orientations). The results showed that contrast thresholds were significantly lower when the local elements all shared the same orientation (e.g., all horizontal) compared with the condition in which the elements had mixed orientations (both horizontal and vertical). The enhancement effect due to uniform local orientations can be explained by two factors: One is local facilitatory interactions between the orientation selective filters, and the other is second-order information integration across the filters.
Network reconstruction of platelet metabolism identifies metabolic signature for aspirin resistance (2014)

Recently there has not been a systematic, objective assessment of the metabolic capabilities of the human platelet. A manually curated, functionally tested, and validated biochemical reaction network of platelet metabolism, iAT-PLT-636, was reconstructed using 33 proteomic datasets and 354 literature references. The network contains enzymes mapping to 403 diseases and 231 FDA approved drugs, alluding to an expansive scope of biochemical transformations that may affect or be affected by disease processes in multiple organ systems. The effect of aspirin (ASA) resistance on platelet metabolism was evaluated using constraint-based modeling, which revealed a redirection of glycolytic, fatty acid, and nucleotide metabolism reaction fluxes in order to accommodate eicosanoid synthesis and reactive oxygen species stress. These results were confirmed with independent proteomic data. The construction and availability of iAT-PLT-636 should stimulate further data-driven, systems analysis of platelet metabolism towards the understanding of pathophysiological conditions including, but not strictly limited to, coagulopathies.
A Stochastic Geometry Analysis of Large-scale Cooperative Wireless Networks Powered by Energy Harvesting (2015)

Energy harvesting is a technology for enabling green, sustainable, and autonomous wireless networks. In this paper, a large-scale wireless network with energy harvesting transmitters is considered, where a group of transmitters forms a cluster to cooperatively serve a desired receiver amid interference and noise. To characterize the link-level performance, closed-form expressions are derived for the transmission success probability at a receiver in terms of key parameters such as node densities, energy harvesting parameters, channel parameters, and cluster size, for a given cluster geometry. The analysis is further extended to characterize a network-level performance metric, capturing the tradeoff between link quality and the fraction of receivers served. Numerical simulations validate the accuracy of the analytical model. Several useful insights are provided. For example, while more cooperation helps improve the link-level performance, the network-level performance might degrade with the cluster size. Numerical results show that a small cluster size (typically 3 or smaller) optimizes the network-level performance. Furthermore, substantial performance can be extracted with a relatively small energy buffer. Moreover, the utility of having a large energy buffer increases with the energy harvesting rate as well as with the cluster size in sufficiently dense networks.
Modulation-Based Harmonic Elimination (2007)

A modulation-based method for generating pulse waveforms with selective harmonic elimination is proposed. Harmonic elimination, traditionally digital, is shown to be achievable by comparison of a sine wave with modified triangle carrier. The method can be used to calculate easily and quickly the desired waveform without solution of coupled transcendental equations
Predictivity of the kinetic direct peptide reactivity assay (kDPRA) for sensitizer potency assessment and subclassification_suppl2 (2020)

Several in vitro OECD test guidelines address key events 1-3 of the adverse outcome pathway for skin sensitization, but none are validated for sensitizer potency assessment. The reaction of sensitizing molecules with skin proteins is the molecular initiating event and appears to be rate-limiting, as chemical reactivity strongly correlates with sensitizer potency. The kinetic direct peptide reactivity assay (kDPRA), a modification of the DPRA (OECD TG 442C), allows derivation of rate constants of the depletion of the cysteine-containing model peptide upon reaction with the test item. Its reproducibility was demonstrated in an inter-laboratory study. Here, we present a database of rate constants, expressed as log kmax, for 180 chemicals to define the prediction threshold to identify strong sensitizers (classified as GHS 1A). A threshold of log kmax -2 offers a balanced accuracy of 85% for predicting GHS 1A sensitizers according to the local lymph node assay. The kDPRA is proposed as a stand-alone assay for identification of GHS 1A sensitizers among chemicals identified as sensitizers by other tests or defined approaches. It may also be used for the prediction of sensitizer potency on a continuous scale, ideally in combination with continuous parameters from other in vitro assays. We show how the rate constant could be combined with read-outs of other in vitro assays in a defined approach. A decision model based on log kmax alone has, however, a high predictivity and can be used as stand-alone model for identification of GHS 1A sensitizers among chemicals predicted as sensitizers.
Reconstructing by Deconvolution Plasma Glucose from Continuous Glucose Monitoring Sensor Data (2006)

In the recent past, several sensors have been developed which allow continuous glucose monitoring (CGM) for several days. CGM can improve diabetes management and in particular decrease the risk of hypoglycemic events. However, CGM sensors measure glucose concentration in the interstitial fluid (ISF) rather than in plasma and ISF lags plasma glucose. The purpose of this work is to investigate if plasma glucose can be reconstructed from ISF CGM data by using a deconvolution approach, based on the knowledge of the model of plasma-interstitium kinetics. Results obtained in 6 volunteers monitored for 2 days with simultaneous plasma and ISF glucose by the Freestyle Navigator CGM sensor measurements show that calibration is a critical component for a reliable reconstruction of plasma glucose from ISF data.
Relationship between IgE Levels Specific for Ragweed Pollen Extract, Amb a 1 and Cross-Reactive Allergen Molecules (2023)

Ragweed (<i>Ambrosia artemisiifolia</i>) pollen is a major endemic allergen source responsible for severe allergic manifestations in IgE-sensitized allergic patients. It contains the major allergen Amb a 1 and cross-reactive allergen molecules, such as the cytoskeletal protein profilin, Amb a 8 and calcium-binding allergens Amb a 9 and Amb a 10. To assess the importance of Amb a 1, profilin and calcium-binding allergen, the IgE reactivity profiles of clinically well-characterized 150 ragweed pollen-allergic patients were analysed regarding specific IgE levels for Amb a 1 and cross-reactive allergen molecules by quantitative ImmunoCAP measurements, IgE ELISA and by basophil activation experiments. By quantifying allergen-specific IgE levels we found that Amb a 1-specific IgE levels accounted for more than 50% of ragweed pollen-specific IgE in the majority of ragweed pollen-allergic patients. However, approximately 20% of patients were sensitized to profilin and the calcium-binding allergens, Amb a 9 and Amb a 10, respectively. As shown by IgE inhibition experiments, Amb a 8 showed extensive cross-reactivity with profilins from birch (Bet v 2), timothy grass (Phl p 12) and mugwort pollen (Art v 4) and was identified as a highly allergenic molecule by basophil activation testing. Our study indicates that molecular diagnosis performed by the quantification of specific IgE to Amb a 1, Amb a 8, Amb a 9 and Amb a 10 is useful to diagnose genuine sensitization to ragweed pollen and to identify patients who are sensitized to highly cross-reactive allergen molecules present in pollen from unrelated plants, in order to enable precision medicine-based approaches for the treatment and prevention of pollen allergy in areas with complex pollen sensitization.
Deposition of Pure Hydrogenated Amorphous Silicon by Plasma-Enhanced Chemical Vapor Deposition for Polycrystalline Silicon Thin Film Transistors (2005)

A high-purity hydrogenated amorphous silicon film has been successfully deposited using an advanced plasma-enhanced chemical vapor deposition system that is available for mass-production use. Oxygen and carbon concentrations in the film were as low as 1.3×10 17 and 2.6×10 16 atoms/cm 3 , respectively, i.e., about hundredth part of the typical values achieved using a recent large-area deposition system and as low as those in CZ-Si wafers. The film was characterized as a function of SiH 4 gas flow rate and outgas rate from the reaction chamber, and the results suggest that oxygen and carbon in the film comes predominantly from H 2 O and CO 2 out-gassing from the chamber wall, respectively.
Urine metabolomic analysis to detect metabolites associated with the development of contrast induced nephropathy (2016)

Differences in metabolomics patterns in patients who do and do not develop CIN exist. Metabolites may be potential early identifiers of CIN and identify patients at high-risk for developing this condition prior to imaging.
Data from Effect of Target Dynamics on Pharmacokinetics of a Novel Therapeutic Antibody against the Epidermal Growth Factor Receptor: Implications for the Mechanisms of Action (2023)

&lt;div&gt;Abstract&lt;p&gt;The epidermal growth factor receptor (EGFR) is overexpressed on many solid tumors and represents an attractive target for antibody therapy. Here, we describe the effect of receptor-mediated antibody internalization on the pharmacokinetics and dose-effect relationship of a therapeutic monoclonal antibody (mAb) against EGFR (2F8). This mAb was previously found therapeutically active in mouse tumor models by two dose-dependent mechanisms of action: blockade of ligand binding and induction of antibody-dependent cell-mediated cytotoxicity. &lt;i&gt;In vitro&lt;/i&gt; studies showed 2F8 to be rapidly internalized by EGFR-overexpressing cells. &lt;i&gt;In vivo&lt;/i&gt;, accelerated 2F8 clearance was observed in cynomolgus monkeys at low doses but not at high doses. This enhanced clearance seemed to be receptor dependent and was included in a pharmacokinetic model designed to explain its nonlinearity. Receptor-mediated clearance was also found to affect &lt;i&gt;in situ&lt;/i&gt; antibody concentrations in tumor tissue. &lt;i&gt;Ex vivo&lt;/i&gt; analyses of xenograft tumors of 2F8-treated nude mice revealed that relatively high antibody plasma concentrations were required for maximum EGFR saturation in high-EGFR-expressing human A431 tumors, in contrast to lower-EGFR-expressing human xenograft tumors. In summary, receptor-mediated antibody internalization and degradation provides a saturable route of clearance that significantly affects pharmacokinetics, particularly at low antibody doses. EGFR saturation in normal tissues does not predict saturation in tumor tissue as local antibody concentrations in EGFR-overexpressing tumors may be more rapidly reduced by antibody internalization. Consequently, antibody saturation of the receptor may be affected, thereby affecting the local mechanism of action. (Cancer Res 2006; 66(15): 7630-8)&lt;/p&gt;&lt;/div&gt;
Adsorptive Recovery of Crude Oil Microdroplets from Wastewater Using Surface Engineered Sponges (2019)

In the US, the oil industry produces over 15 billion barrels of wastewater contaminated with crude oil microdroplets annually. Current technologies are unable to remove these microdroplets at different pH conditions. Herein, an innovative surface engineered sponge (SenS) was designed by combining surface chemistry, surface charge, roughness, and surface energy. Under all pH conditions, the SEnS rapidly adsorbed oil microdroplets with 95-99% removal efficiency. The adsorbed oil was recovered at ambient conditions while the cleaned SEnS was reused for five times for crude oil adsorption. Due to the process efficacy, sponge reuse, and oil recovery, this adsorptive-recovery method using SEnS demonstrates great potential for the industrial recovery of oil from wastewater.
Enzyme-Based Hybrid Macroporous Foams as Highly Efficient Biocatalysts Obtained through Integrative Chemistry (2010)

Integrative chemistry-based rational design has been used to synthesize the first lipase [C-CRl]@Glymo-Si(HIPE) and [C-TAl]@Glymo-Si(HIPE) hybrid macrocellular biocatalysts, where immobilization of crude enzymes is optimized, while circumventing the reactants’ low kinetic diffusion, by the use of silica macroporous hosts. As a direct consequence, these new hybrid biocatalysts display unprecedented cycling catalysis performance, as demonstrated by the syntheses of butyloleate ester (used as biodiesel lubricant), hydrolysis of linoleic-glycero ester derivatives (end products used for detergent and soap generations), and trans-esterification (reaction involved in the synthesis of low viscosity biodiesel). Considering that the catalytic performances are given in terms of absolute conversion percentage and not just relative enzyme activity, the enzyme@Glymo-Si(HIPE) hybrid macrocellular biocatalysts presented in this study display unprecedented high yield cycling catalysis performances, where turnover numbers (TON) and turnover frequencies (TOF) show promise for real industrial applications. This study can be considered as a milestone for enzyme-based heterogeneous catalyzes, thereby enhancing their competitiveness with the supported-catalysts commonly used in industry, in total agreement with current sustainable development issues. Also, the new macrocellular biocatalysts are well-suited for large-scale industrial production because of their above-mentioned performance characteristics, further enhanced by their monolithic character, which eases the separation of the catalysts from other reaction components.
Face Recognition Using 3-D Models: Pose and Illumination Novel face recognition algorithms, based on three-dimensional information, promise to improve automated face recognition by dealing with different viewing and lighting conditions. (2006)

Unconstrained illumination and pose variation lead to significant variation in the photographs of faces and constitute a major hurdle preventing the widespread use of face recognition systems. The challenge is to generalize from a limited number of images of an individual to a broad range of conditions. Recently, advances in modeling the effects of illumination and pose have been accomplished using three- dimensional (3-D) shape information coupled with reflectance models. Notable developments in understanding the effects of illumination include the nonexistence of illumination invar- iants, a characterization of the set of images of objects in fixed pose under variable illumination (the illumination cone), and the introduction of spherical harmonics and low-dimensional linear subspaces for modeling illumination. To generalize to novel conditions, either multiple images must be available to reconstruct 3-D shape or, if only a single image is accessible, prior information about the 3-D shape and appearance of faces in general must be used. The 3-D Morphable Model was introduced as a generative model to predict the appearances of an individual while using a statistical prior on shape and texture allowing its parameters to be estimated from single image. Based on these new understandings, face recognition algorithms have been developed to address the joint chal- lenges of pose and lighting. In this paper, we review these developments and provide a brief survey of the resulting face recognition algorithms and their performance.