gebhart/patrepeval huggingface dataset:
Mobile trap algorithm for zinc detection using protein sensors (2007)

We present a mobile trap algorithm to sense zinc ions using protein-based sensors such as carbonic anhydrase (CA). Zinc is an essential biometal required for mammalian cellular functions although its intracellular concentration is reported to be very low. Protein-based sensors like CA molecules are employed to sense rare species like zinc ions. In this study, the zinc ions are mobile targets, which are sought by the mobile traps in the form of sensors. Particle motions are modeled using random walk along with the first passage technique for efficient simulations. The association reaction between sensors and ions is incorporated using a probability (p1) upon an ion-sensor collision. The dissociation reaction of an ion-bound CA molecule is modeled using a second, independent probability (p2). The results of the algorithm are verified against the traditional simulation techniques (e.g., Gillespie's algorithm). This study demonstrates that individual sensor molecules can be characterized using the probability pair (p1,p2), which, in turn, is linked to the system level chemical kinetic constants, kon and koff. Further investigations of CA-Zn reaction using the mobile trap algorithm show that when the diffusivity of zinc ions approaches that of sensor molecules, the reaction data obtained using the static trap assumption differ from the reaction data obtained using the mobile trap formulation. This study also reveals similar behavior when the sensor molecule has higher dissociation constant. In both the cases, the reaction data obtained using the static trap formulation reach equilibrium at a higher number of complex molecules (ion-bound sensor molecules) compared to the reaction data from the mobile trap formulation. With practical limitations on the number sensors that can be inserted/expressed in a cell and stochastic nature of the intracellular ionic concentrations, fluorescence from the number of complex sensor molecules at equilibrium will be the measure of the intracellular ion concentration. For reliable detection of zinc ions, it is desirable that the sensors must not bind all the zinc ions tightly, but should rather bind and unbind. Thus for a given fluorescence and with association-dissociation reactions between ions and sensors, the static trap approach will underestimate the number of zinc ions present in the system.
Alzheimer's-disease-related protein in geriatric schizophrenic patients with cognitive impairment (1993)

The authors compared Alz-50 immunoreactivity in the brain tissue of nine cognitively impaired elderly schizophrenic patients and 13 elderly comparison subjects, both without neuritic plaques or neurofibrillary tangles, and 13 patients with Alzheimer's disease. Alz-50 reactivity was absent in the schizophrenic patients, indicating that geriatric, cognitively impaired patients are unlikely to display the pathology of Alzheimer's disease.
Molecular Magnetic Resonance Imaging Using a Redox-Active Iron Complex (2019)

We introduce a redox-active iron complex, Fe-PyC3A, as a biochemically responsive MRI contrast agent. Switching between Fe<sup>3+</sup>-PyC3A and Fe<sup>2+</sup>-PyC3A yields a full order of magnitude relaxivity change that is field-independent between 1.4 and 11.7 T. The oxidation of Fe<sup>2+</sup>-PyC3A to Fe<sup>3+</sup>-PyC3A by hydrogen peroxide is very rapid, and we capitalized on this behavior for the molecular imaging of acute inflammation, which is characterized by elevated levels of reactive oxygen species. Injection of Fe<sup>2+</sup>-PyC3A generates strong, selective contrast enhancement of inflamed pancreatic tissue in a mouse model (caerulein/LPS model). No significant signal enhancement is observed in normal pancreatic tissue (saline-treated mice). Importantly, signal enhancement of the inflamed pancreas correlates strongly and significantly with ex vivo quantitation of the pro-inflammatory biomarker myeloperoxidase. This is the first example of using metal ion redox for the MR imaging of pathologic change in vivo. Redox-active Fe<sup>3+/2+</sup> complexes represent a new design paradigm for biochemically responsive MRI contrast agents.
Optimization of protoplast regeneration in the model plant Arabidopsis thaliana (2021)

The cell and tissue culture system optimized in this study for protoplast regeneration is efficient and reproducible. This method of Arabidopsis protoplast regeneration can be used for fundamental studies on pluripotency establishment and de novo tissue regeneration.
Robust regularization of the recursive least-squares algorithm (2016)

This paper is dedicated to the memory of Steven L. Grant for his exceptional contributions to the echo cancellation problem. The regularization is mandatory in all ill-posed problems, especially in the presence of additive noise. In this paper, we consider the regularized recursive least-squares (RLS) algorithm and present a method to find its regularization parameter, depending on the signal-to-noise ratio. We also outline the robustness features of this solution, which could make the RLS algorithm to behave well even in non-stationary environments. Simulations performed in the context of echo cancellation support these findings.
Application-controlled physical memory using external page-cache management (1992)

article Free Access Share on Application-controlled physical memory using external page-cache management Authors: Kieran Harty View Profile , David R. Cheriton View Profile Authors Info & Claims ACM SIGPLAN NoticesVolume 27Issue 9Sept. 1992 pp 187–197https://doi.org/10.1145/143371.143511Published:01 September 1992Publication History 85citation1,023DownloadsMetricsTotal Citations85Total Downloads1,023Last 12 Months53Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
Related Article from Targeting Metabolic Scavenging in Pancreatic Cancer (2023)

Related Article from Targeting Metabolic Scavenging in Pancreatic Cancer
Error neutralisation in switched current memory cells (2003)

This paper demonstrates that high performance operation of switched-current memory cells can be achieved by neutralisation of the cell's errors using gate-drain capacitive feedback. Simulation indicates that this technique can achieve 9-10 bit performance at a sampling frequency of 100 MS/s.
Carbogen-Induced Respiratory Acidosis Blocks Experimental Seizures by a Direct and Specific Inhibition of NaV1.2 Channels in the Axon Initial Segment of Pyramidal Neurons (2023)

Brain pH is a critical factor for determining neuronal activity, with alkalosis increasing and acidosis reducing excitability. Acid shifts in brain pH through the breathing of carbogen (5% CO<sub>2</sub>/95% O<sub>2</sub>) reduces seizure susceptibility in animal models and patients. The molecular mechanisms underlying this seizure protection remain to be fully elucidated. Here, we demonstrate that male and female mice exposed to carbogen are fully protected from thermogenic-triggered seizures. Whole-cell patch-clamp recordings revealed that acid shifts in extracellular pH (pHo) significantly reduce action potential firing in CA1 pyramidal neurons but did not alter firing in hippocampal inhibitory interneurons. In real-time dynamic clamp experiments, acidification reduced simulated action potential firing generated in hybrid model neurons expressing the excitatory neuron predominant Na<sub>V</sub>1.2 channel. Conversely, acidification had no effect on action potential firing in hybrid model neurons expressing the interneuron predominant Na<sub>V</sub>1.1 channel. Furthermore, knockdown of <i>Scn2a</i> mRNA <i>in vivo</i> using antisense oligonucleotides reduced the protective effects of carbogen on seizure susceptibility. Both carbogen-mediated seizure protection and the reduction in CA1 pyramidal neuron action potential firing by low pHo were maintained in an <i>Asic1a</i> knock-out mouse ruling out this acid-sensing channel as the underlying molecular target. These data indicate that the acid-mediated reduction in excitatory neuron firing is mediated, at least in part, through the inhibition of Na<sub>V</sub>1.2 channels, whereas inhibitory neuron firing is unaffected. This reduction in pyramidal neuron excitability is the likely basis of seizure suppression caused by carbogen-mediated acidification.<b>SIGNIFICANCE STATEMENT</b> Brain pH has long been known to modulate neuronal excitability. Here, we confirm that brain acidification reduces seizure susceptibility in a mouse model of thermogenic seizures. Extracellular acidification reduced excitatory pyramidal neuron firing while having no effect on interneuron firing. Acidification also reduced dynamic clamp firing in cells expressing the Na<sub>V</sub>1.2 channel but not in cells expressing Na<sub>V</sub>1.1 channels. <i>In vivo</i> knockdown of Scn2a mRNA reduced seizure protection of acidification. In contrast, acid-mediated seizure protection was maintained in the Asic1a knock-out mouse. These data suggest Na<sub>V</sub>1.2 channel as an important target for acid-mediated seizure protection. Our results have implications on how natural variations in pH can modulate neuronal excitability and highlight potential antiseizure drug development strategies based on the Na<sub>V</sub>1.2 channel.
One‐millimeter isotropic breast diffusion‐weighted imaging: Evaluation of a superresolution strategy in terms of signal‐to‐noise ratio, sharpness and apparent diffusion coefficient (2018)

A combination of rs-EPI and SR allows 3D, 1-mm isotropic breast DWI data to be obtained with better SNR than a native 1-mm isotropic acquisition. The proposed DWI protocol might be of interest for breast cancer monitoring/screening without injection.
Versatile Routes to Marine Sponge Metabolites through Benzylidene Rhodanines (2012)

The first total synthesis of the marine natural products Psammaplin C and Tokaradine A is described. Benzylidene rhodanines were utilized as versatile intermediates toward the synthesis of seven brominated marine sponge metabolites through the optimization of protection group strategies. Spermatinamine demonstrated good inhibition of all cancer cell lines tested, in particular the leukemia K562 and colon cancer HT29 cell lines.
Leucine Aminopeptidase Is Not Essential for Trimming Peptides in the Cytosol or Generating Epitopes for MHC Class I Antigen Presentation (2005)

To detect viral infections and tumors, CD8+ T lymphocytes monitor cells for the presence of antigenic peptides bound to MHC class I molecules. The majority of MHC class I-presented peptides are generated from the cleavage of cellular and viral proteins by the ubiquitin-proteasome pathway. Many of the oligopeptides produced by this process are too long to stably bind to MHC class I molecules and require further trimming for presentation. Leucine aminopeptidase (LAP) is an IFN-inducible cytosolic aminopeptidase that can trim precursor peptides to mature epitopes and has been thought to play an important role in Ag presentation. To examine the role of LAP in generating MHC class I peptides in vivo, we generated LAP-deficient mice and LAP-deficient cell lines. These mutant mice and cells are viable and grow normally. The trimming of peptides in LAP-deficient cells is not reduced under basal conditions or after stimulation with IFN. Similarly, there is no reduction in presentation of peptides from precursor or full-length Ag constructs or in the overall supply of peptides from cellular proteins to MHC class I molecules even after stimulation with IFN. After viral infection, LAP-deficient mice generate normal CTL responses to seven epitopes from three different viruses. These data demonstrate that LAP is not an essential enzyme for generating most MHC class I-presented peptides and reveal redundancy in the function of cellular aminopeptidases.
Efficient Nonlinear Frequency Conversion in an All-Resonant Double-ΛSystem (2000)

We demonstrate efficient, pulsed, gas-phase, nonlinear frequency conversion in a quadruply resonant, double- Lambda system and, simultaneously, verify theoretical predictions of Rabi-frequency matching unique to absorbing nonlinear media. This system is used to up-convert ultraviolet light at 233 nm to the vacuum ultraviolet at 186 nm in atomic Pb vapor with small-signal conversion efficiencies exceeding 30% and with modest atomic density-length (NL) products (scale 10(14) cm(-2)) and optical power densities (10-100 kW/cm(2)).
Treatment of chronic hepatitis B virus infection via oral immune regulation toward hepatitis B virus proteins (2003)

Objectives
Hepatitis B virus (HBV) is a noncytopathic virus, and hepatocellular injury is mediated by a defective host antiviral immune response. We have previously shown that antiviral immunity can be modulated through oral feeding of viral proteins. The aims of this study were to determine the safety and efficacy of treatment of patients with chronic HBV by means of p.o. administration of HBV envelope proteins.
Focusing free-electron radiation with source-embedded metalenses (2022)

We experimentally study simultaneous generation and focusing of free-electron radiation by a metalens, and explore theoretically metasurface lenses showing polarization control. Our work paves the way towards versatile and tunable free-electron metasurface light sources.
Development and Qualification of a Subsea Compressor (2016)

Abstract Oil and gas production in the Norwegian Sea has been ongoing for decades. The Åsgard B platform produces gas and condensate from the Mikkel and Midgard reservoirs from subsea wellheads with 50 to 80 km long pipeline tie-backs. Because the production started to decline, several innovative technologies were investigated to extend the production and increase the total recovery from the field. Artificial lift, by applying compressors installed on the seabed close to the wellheads, was the most favorable solution. An all-electric hermetically sealed integrated motor-compressor was selected to fulfil this duty and an extensive technology qualification program over 10 years was initiated. Machine qualification activities included both component and full scale testing levels with the aim to arrive at a low risk subsea compressor solution with utmost robustness and reliability. The component testing level placed major focus on screening available materials to withstand exposure to the raw wellstream fluid from the Åsgard field. Full scale motor compressor testing was performed in a dedicated test facility with hydrocarbon fluids to investigate overall machine performance and enhancement via the introduction of new machine components from the material screening testing. Valuable operational experience from the qualification efforts were collected and used to establish the design and material selection boundary conditions for the final dedicated subsea compression solution. A particular negative operational experience was fouling induced machine thermodynamic and rotordynamic performance degradation and the need to introduce integrated online washing and machine wet gas compression compatibility to reduce operational risks. To preserve machine robustness and mitigate potential corrosion and erosion problems, a machine concept with unconventional low operating speed and enhanced materials was selected. The world’s first subsea compressor with the above concept attributes was successfully manufactured, tested, installed, and operated subsea at a depth of 260 meters. The qualified machine has been designed and tested for presence of free liquids such as water, hydrocarbon condensate, and glycol in the gas stream and demonstrated full capability to operate within the complete compressor performance map with liquid content exceeding levels found in normal gas-condensate fields. An available high performance wellstream compressor can reduce the complexity and cost of future subsea compression systems.
Polynomial Chaos modeling for jitter estimation in high-speed links (2018)

Determination of the data dependent jitter and its effect on the eye diagram is a challenging task in modern high-speed links; therefore, novel statistical approaches are required to expedite this task. Most of the current methods for jitter estimation are only applicable to linear systems, while nonlinear components play an essential role in the high-speed link response. Therefore, this paper introduces a new data dependent jitter estimation approach by using stochastic analysis. In this approach generalized Polynomial Chaos theory is utilized, where linear regression is used to create surrogate models for the link. Statistics of the output signal and jitter calculation are then directly obtained from these models. Two numerical examples are provided to evaluate the efficiency and accuracy of the proposed approach showing good match with the traditional transient eye analysis with good speedup.
Preamble-Based Adaptive Channel Estimation for IEEE 802.11p (2019)

Recently, research into autonomous driving and traffic safety has been drawing a great deal of attention. To realize autonomous driving and solve traffic safety problems, wireless access in vehicular environments (WAVE) technology has been developed, and IEEE 802.11p defines the physical (PHY) layer and medium access control (MAC) layer in the WAVE standard. However, the IEEE 802.11p frame structure, which has low pilot density, makes it difficult to predict the properties of wireless channels in a vehicular environment with high vehicle speeds; thus, the performance of the system is degraded in realistic vehicular environments. The motivation for this paper is to improve the channel estimation and tracking performance without changing the IEEE 802.11p frame structure. Therefore, we propose a channel estimation technique that can perform well over the entire SNR range of values by changing the method of channel estimation accordingly. The proposed scheme selectively uses two channel estimation schemes, each with outstanding performance for either high-SNR or low-SNR signals. To implement this, an adaptation algorithm based on a preamble is proposed. The preamble is a signal known to the transmitter-receiver, so that the receiver can obtain channel estimates without demapping errors, evaluating performance of the channel estimation schemes. Simulation results comparing the proposed method to other schemes demonstrate that the proposed scheme can selectively switch between the two schemes to improve overall performance.
Directly modulated DBR lasers for long-haul transmission at 1.7 Gbit/s (1992)

With the recent advances of erbium-doped fiber amplifiers (EDFAs) the total unrepeatered distance for fiber-optic transmission near 1.55 pm has increased dramatically. In conventional (nondispersion- shifted) fiber systems the primary limitation is now dispersion, requiring sources with low chirp. For these systems, the simplicity of direct modulation of single-mode lasers is an attractive alternative to external modulation. We have used nine directly modulated distributed-Bragg reflector (DBR) lasers for 1.7-Gbit/s transmission through 257 km of conventional fiber with &lt;2-dB dispersion penalty. This results in the best bit rate x distance product (437 km-Gbit/s) to date to our knowledge for directly modulated monolithic lasers between 1 and 3 Gbit/s through conventional single-mode fiber.
Similarity Learning for Motion Estimation (2011)

Motion estimation necessitates an appropriate choice of similarity function. Because generic similarity functions derived from simple assumptions are insufficient to model complex yet structured appearance variations in motion estimation, the authors propose to learn a discriminative similarity function to match images under varying appearances by casting image matching into a binary classification problem. They use the LogitBoost algorithm to learn the classifier based on an annotated database that exemplifies the structured appearance variations: An image pair in correspondence is positive and an image pair out of correspondence is negative. To leverage the additional distance structure of negatives, they present a location-sensitive cascade training procedure that bootstraps negatives for later stages of the cascade from the regions closer to the positives, which enables viewing a large number of negatives and steering the training process to yield lower training and test errors. The authors apply the learned similarity function to estimating the motion for the endocardial wall of left ventricle in echocardiography and to performing visual tracking. They obtain improved performances when comparing the learned similarity function with conventional ones.
Gland segmentation from histology images using informative morphological scale space (2016)

Grading of cancer offers insight to the occurrence and progress of the disease. The course of treatment is planned depending on the grade of cancer. Segmentation of the glandular structure of tissue is a prerequisite for grading of colon, prostate and breast cancers. Manual segmentation method is time-consuming and suffers from the curse of observer bias. We propose an automated solution for gland segmentation from hematoxylin & eosin (H&E) stained histology images. Our method relies on the biological cue rather than gland specific signatures that may vary across the slides. We construct a novel informative morphological scale space for gland segmentation. The scale space uses the entropy of the connected components in a novel manner to prevent over segmentation of objects. Our solution is fast, accurate and applicable in a clinical setup. Experiments show an average F1 score of 0.68 for 85 histology images in 20x magnification. We obtain ~ 30% improvement in F1 score compared to the area morphological scale space method.
n-m-Variant Systems: Adversarial-Resistant Software Rejuvenation for Cloud-Based Web Applications (2019)

Web servers are a popular target for adversaries as they are publicly accessible and often vulnerable to compromise. Compromises can go unnoticed for months, if not years, and recovery often involves a complete system rebuild. In this paper, we propose n-m-Variant Systems, an adversarial-resistant software rejuvenation framework for cloud-based web applications. We improve the state-of-the-art by introducing a variable m that provides a knob for administrators to tune an environment to balance resource usage, performance overhead, and security guarantees. Using m, security guarantees can be tuned for seconds, minutes, days, or complete resistance. We design and implement an n-m-Variant System prototype to protect a Mediawiki PHP application serving dynamic content from an external SQL persistent storage. Our performance evaluation shows a throughput reduction of 65% for 108 seconds of resistance and 83% for 12 days of resistance to sophisticated adversaries, given appropriate resource allocation. Furthermore, we use theoretical analysis and simulation to characterize the impact of system parameters on resilience to adversaries. Through these efforts, our work demonstrates how properties of cloud-based servers can enhance the integrity of Web servers.
Observation of CP Violation in B± → D K± Decays (2012)

An analysis of B± → D K± and B± → D π± decays is presented where the D meson is reconstructed in the two-body final states: K± π∓, K+ K− and π+ π−. Using 1.0 fb^−1 of √s = 7 TeV pp collisions, measurements of several observables are made including the first observation of the suppressed mode B± → [π± K∓]_D K±. CP violation in B± → D K± decays is observed with 5.8σ significance.