gebhart/patrepeval huggingface dataset:
Genetic Variant Showing a Positive Interaction With β-Blocking Agents With a Beneficial Influence on Lipoprotein Lipase Activity, HDL Cholesterol, and Triglyceride Levels in Coronary Artery Disease Patients (1997)

We conclude that the LPL Ser447-Stop mutation has a significant positive effect on LPL activity and HDL cholesterol and triglyceride levels and that certain subgroups of CAD patients carrying the Ser447-Stop mutation will have less adverse metabolic effects when placed on beta-blockers. The LPL Ser447-Stop mutation therefore should have a protective effect against the development of atherosclerosis and subsequent CAD.
Squeezed-state generation by the normal modes of a coupled system (1987)

A new regime for the generation of squeezed states of the electromagnetic field is described for a collection of atoms within a high-finesse cavity. The process responsible for squeezing is a coupling-induced splitting in the normal-mode structure of the atom-field system. A theoretical analysis is presented that predicts large degrees of squeezing for modest operating conditions. An experimental investigation of this regime has produced noise reductions of 30% relative to the vacuum noise level.
A novel 0.5- mu m n/sup +/-p/sup +/ poly-gated salicide CMOS process (1989)

A novel salicided twin-tub 0.5- mu m CMOS process using germanium implantation is presented. n/sup +/ and p/sup +/ dopants are implanted after salicide formation to fabricate devices with low junction leakage and low silicide-to-diffusion contact resistance. Germanium implantation prior to silicide formation is used to control short-channel transistor characteristics. A significant reduction in the lateral n/sup -/ and p/sup -/ diffusion is observed for germanium-implanted LDD (lightly doped drain) MOSFETs, resulting in minimized overlap capacitance as well as improved short-channel behavior.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
A Tandem Mobility Spectrometer for Chemical Agent and Toxic Industrial Chemical Monitoring (2008)

Abstract Sensitivity, selectivity, and speed are the most important analytical parameters in sensing chemical warfare agents (CWAs) and toxic industrial chemicals (TICs). For homeland security applications, where protection from chemical releases in public facilities such as at airports or subway stations is desired, selectivity becomes even more critical since false alarms can cause costly societal disruptions and trigger public panic. Currently, ion mobility spectrometry (IMS) has been widely deployed in the battlefield for CWA detection because of its excellent sensitivity and speed. However, IMS alone has suffered from low selectivity, especially for lower molecular weight TICs, which results in false alarms. This article describes an emerging technology that combines differential mobility spectrometry (DMS) and IMS in one package. In this configuration, the DMS serves as an ion filter for the IMS, prescreening targets from background with a separation mechanism that is complementary to the IMS. The tandem analyzer consists of a microfabricated DMS and two miniaturized IMS detectors arranged in an orthogonal configuration, enabling the detection of positive and negative ions simultaneously. The combination of these two technologies can significantly reduce false alarm rates. The tandem DMS–IMS provides a real‐time, powerful technology to counter terrorist threats in infrastructure protection scenarios.
Electricity generation from sulfide tailings using a double-chamber microbial fuel cell (2015)

Pyrrhotite tailings have the potential to drive electricity generation accompanied by microbial leaching of valuable metals using the double-chamber MFC reactor.
TMOD-15. IDENTIFYING THE SPATIAL AND TEMPORAL DYNAMICS OF GLIOBLASTOMA SUBPOPULATIONS WITHIN INDIVIDUAL PATIENTS (2019)

Abstract Glioblastomas (GBMs) are known to be complex tumors comprising multiple subpopulations of genetically-distinct cancer cells; it is thought that this genetic variation is a major factor in the lack of observed survival benefit of treatment regimes that target one of these subpopulations. The field of radiogenomics seeks to study correlations between MRI patterns and genetic features of GBM tumors. Spatial radiogenomic maps produced using machine-learning (ML) methods that are trained against information from image-localized patient biopsies identify regions where particular cancer sub-populations are predicted to occur within a GBM, thus non-invasively characterizing the regional genetic variability of these tumors. These tumor subpopulations may also interact with one another, in ways which may be of a competitive or cooperative nature to varying degrees. It is important to ascertain the nature of these interactions, as they may have implications for treatment response to targeted therapies, and characterization of the spatio-temporal dynamics of these co-evolving sub-populations will shed light on why some therapies fail. Here we combine mathematical modeling techniques and spatially-resolved radiogenomic maps to study the nature of these interactions between molecularly-distinct GBM subpopulations. We model the interactions between cell populations using a partial differential equation based formalism. The model is parameterized using radiogenomic ML maps from which we infer the nature of interactions between subpopulations. Furthermore, using maps as inputs, the model turns static maps into dynamic information, thus providing insight into how these subpopulations composing the tumor change over time and the effect this has on observed treatment response for individual patients.
SU‐E‐T‐574: Novel Chance‐Constrained Optimization in Intensity‐Modulated Proton Therapy Planning to Account for Range and Patient Setup Uncertainties (2015)

Purpose: We propose to apply a probabilistic framework, namely chanceconstrained optimization, in the intensity‐modulated proton therapy (IMPT) planning subject to range and patient setup uncertainties. The purpose is to hedge against the influence of uncertainties and improve robustness of treatment plans. Methods: IMPT plans were generated for a typical prostate patient. Nine dose distributions are computed — the nominal one and one each for ±5mm setup uncertainties along three cardinal axes and for ±3.5% range uncertainty. These nine dose distributions are supplied to the solver CPLEX as chance constraints to explicitly control plan robustness under these representative uncertainty scenarios with certain probability. This probability is determined by the tolerance level. We make the chance‐constrained model tractable by converting it to a mixed integer optimization problem. The quality of plans derived from this method is evaluated using dose‐volume histogram (DVH) indices such as tumor dose homogeneity (D5% – D95%) and coverage (D95%) and normal tissue sparing like V70 of rectum, V65, and V40 of bladder. We also compare the results from this novel method with the conventional PTV‐based method to further demonstrate its effectiveness Results: Our model can yield clinically acceptable plans within 50 seconds. The chance‐constrained optimization produces IMPT plans with comparable target coverage, better target dose homogeneity, and better normal tissue sparing compared to the PTV‐based optimization [D95% CTV: 67.9 vs 68.7 (Gy), D5% – D95% CTV: 11.9 vs 18 (Gy), V70 rectum: 0.0 % vs 0.33%, V65 bladder: 2.17% vs 9.33%, V40 bladder: 8.83% vs 21.83%]. It also simultaneously makes the plan more robust [Width of DVH band at D50%: 2.0 vs 10.0 (Gy)]. The tolerance level may be varied to control the tradeoff between plan robustness and quality. Conclusion: The chance‐constrained optimization generates superior IMPT plan compared to the PTV‐based optimization with explicit control of plan robustness. NIH/NCI K25CA168984, Eagles Cancer Research Career Development, The Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, Mayo ASU Seed Grant, and The Kemper Marley Foundation.
Incorporation of fuzzy preferences into evolutionary multiobjective optimization (2002)

A method for incorporating fuzzy preferences into evolutionary multiobjective optimization is proposed. After introducing three commonly used models for describing fuzzy preferences, a method to convert fuzzy preferences into realvalued weight intervals is suggested. It is argued that to convert fuzzy preferences into interval-based weights is more consistent with the motivation of using fuzzy preferences than to convert them into single-valued crisp weights. The weight intervals are combined with the evolutionary dynamic weighted aggregation to obtain the preferred Pareto-optimal solutions. Simulation examples are given to show how the desired Pareto-optimal solutions can be obtained.
Design, Synthesis, and Evaluation of β‐Galactosylceramide Mimics Promoting β‐Glucocerebrosidase Activity in Keratinocytes. (2003)

Abstract For Abstract see ChemInform Abstract in Full Text.
Structural Changes in the Arginine Vasopressin Molecule that Prolong Its Antidiuretic Action (1974)

A number of structural analogues of neurohypophysial peptides produce antidiuretic responses of varying duration when injected SC into conscious rats with hereditary hypothalamic diabetes insipidus. Analogues containing arginine in the 8-position and lacking an N-terminal amino group all have markedly prolonged antidiuretic effects. Deamino analogues with other basic amino acids in the 8-position have effectsthat are prolonged to a lesser degree. Deamino-mesotocin has a slightly prolonged antidiuretic effect but deamino-oxytocin does not. Substituting amino acids with more lipophilic side-chains for the 4-glutamine in deamino-arginine-vasopressin further enhances the persistence of its antidiuretic action. Substituting 8-D-arginine for 8-L-arginine in vasopressin does not influence duration of action. Deamination is thus clearly the primary molecular change that endows arginine vasopressin analogues with greatly prolonged antidiuretic effects, while introducing more lipophilic side-chains in the 4-position may prolong these further. Substituting either a more lipophilic side-chain in position 4 or D-arginine in position 8 decreases vasopressor activity but not antidiuretic activity. When both types of substitution are made in deamino-arginine-vasopressin, the resultant analogue, l-deamino-[4-valine, 8-D-arginine]-vasopressin (dVDAVP) is highly active, the most specific antidiuretic peptide ever reported, and has greatly prolonged antidiuretic effectsEndocrinology95: 140, 1974)
Recovery of the magnetic particle imaging system matrix using compressed sensing reconstruction (2013)

In magnetic particle imaging the system matrix is commonly obtained by performing a tedious calibration scan, which requires measuring the system response at various positions in the field-of-view. In this work, a method for significantly reducing the number of required calibration scans is proposed. It exploits the fact that the MPI system matrix can be sparsified using certain basis transformations such as the discrete Fourier transformation and applies compressed sensing reconstruction techniques. Experiments show that the calibration scan can be accelerated by a factor of ten with only marginal loss of image quality.
Saffron-Based Crocin Prevents Early Lesions of Liver Cancer: In vivo, In vitro and Network Analyses (2015)

Taken together, our findings introduce crocin as a candidate chemopreventive agent against HCC.
Experimental immunization of rats with a Streptococcus mutans 59-kilodalton glucan-binding protein protects against dental caries (1996)

Glucan-binding proteins (GBPs) are theoretically important in the molecular pathogenesis of dental caries caused by Streptococcus mutans. The present study evaluated the ability of antibody induced by the S. mutans 59-kDa GBP (GBP59) to affect dental caries caused by experimental infection with S. mutans in a rodent model. Groups of 20-day-old rats were injected twice at 9-day intervals subcutaneously in the salivary gland vicinity with GBP59, glucosyltransferase (GTF), or phosphate-buffered saline (sham injection), each incorporated in an adjuvant. Two weeks after the second injection, GBP59- and GTF-injected rats contained significant levels of salivary immunoglobulin A and serum immunoglobulin G antibody to the respective injected antigens. However, cross-reacting antibody to S. mutans GTF or GBP59 was not induced by the respective antigen. Rats were then orally infected with S. mutans. After 71 days of infection, GBP59- and GTF-injected groups had smaller numbers of S. mutans on their molar surfaces, compared with the sham-injected infected group. Total, sulcal, and smooth-surface molar caries in the GBP59- and GTF-immunized S. mutans-infected groups were each significantly lower (P < or = 0.003) than the respective measures of caries in the sham injected infected group. The results of this investigation demonstrate that immunization with S. mutans GBP59 induces an immune response in rats that can interfere with the accumulation of S. mutans and can reduce the level of dental caries caused by this cariogenic streptococcus. Furthermore, the protective immunity induced by either GBP59 or GTF appears to result from antibodies to independent epitopes since these two S. mutans components do not have a close antigenic relationship.
Generating Annotated Graphs using the NLG Pipeline Architecture (2014)

The Arria NLG Engine has been extended to generate annotated graphs: data graphs that contain computer-generated textual annotations to explain phenomena in those graphs.These graphs are generated alongside text-only data summaries.
First-in-Human, Phase I Dose-Escalation Study of CGM097, a HDM2 Inhibitor in Adult Patients With p53 Wild-type Advanced Solid Malignancies (2021)

Background: CGM097 inhibits p53-HDM2 interaction, thus activates p53 downstream effector pathways inducing cell cycle arrest and/or apoptosis. This phase I study aimed at assessing the safety, MTD, PK/PD, and preliminary antitumor activity of CGM097 in advanced solid tumors patients (NCT01760525).\nMethods: Fifty-one patients received oral treatment with CGM097 10-400mg 3qw (n=31) and on an alternative regimen of 3qw 2 weeks on/1 week off (300-700mg; n=20). Choice of dose regimen was guided by PD biomarkers, PK/PD relationship, and modeling of drug-induced changes in platelet kinetics.\nResults: No dose-limiting toxicities were reported in any regimens. Grade 3/4 AEs suspected to be drug-related were reported in 21 patients. Main reason for discontinuation was disease progression (n=41). CGM097 plasma concentrations increased in a dose proportional manner. Disease control rate was 39%, including one partial response (300mg, 3qw) and 19 patients in stable disease (10-700mg 3qw). Forty patients had a cumulative treatment duration of >16 weeks, with 8 patients on treatment for >32 weeks. The MTD was not determined.\nConclusions: Despite delayed-onset thrombocytopenia frequently observed, the tolerability of CGM097 appears manageable. Although CGM097 is not being further developed, this study led to important modeling-derived learnings to optimize dose scheduling of next generation HDM2 inhibitors.
Color Image Enhancement Using Single-Scale Retinex Based On An Improved Image Formation Model (2008)

Publication in the conference proceedings of EUSIPCO, Lausanne, Switzerland, 2008
Parathyroid Hormone-Related Protein (1995)

We review the current state of knowledge of the molecular properties and actions of parathyroid hormone-related protein (PTHrP) both in cancer patients and in normal physiology. PTHrP is a common product of squamous cancers and is the major mediator of the syndrome of humoral hypercalcemia of malignancy (HHM) by its actions through parathyroid hormone receptors in bone and kidney. Recently developed radioimmunoassays and tissue localization techniques indicate that PTHrP is produced by many more cancers than was originally indicated by clinical studies and that it contributes significantly to malignancy-related hypercalcemia associated with other etiologies, for example, cancers metastatic to bone and hematological malignancies. The gene encoding PTHrP is complex, with multiple exons coding for up to 12 alternate transcripts and three different length proteins, potentially in a tissue-specific manner, by the use of three promoters. Its expression is regulated by hormones and growth factors, and the untranslated exons display features in common with many cytokine genes. Although potential endocrine actions of PTHrP are evident in fetal development, further evidence suggesting that the normal physiological role of PTHrP is predominantly as a locally produced regulator/cytokine comes from localization studies and investigations of its actions in a variety of tissues. Such studies indicate that in addition to its parathyroid hormone-like actions, PTHrP has multiple activities, including those in fetal development, placental calcium transfer, lactation, smooth muscle relaxation, and on epithelial cell growth. Although PTHrP was discovered because of its production by cancers, evidence for its actions as a local regulator highlights the importance of understanding its roles not only in the etiology of HHM in cancer patients but also in normal tissues.
Ranking Twitter discussion groups (2014)

A discussion group is a repeated, synchronized conversation organized around a specific topic. Groups are extremely valuable to the attendees, creating a sense of community among like-minded users. While groups may involve many users, there are many outside the group that would benefit from participation. However, finding the right group is not easy given their quantity and given topic overlap. We study the following problem: given a search query, find a good ranking of discussion groups. We describe a random walk model for how users select groups: starting with a group relevant to the query, a hypothetical user repeatedly selects an authoritative user in the group and then moves to a group according to what the authoritative user prefers. The stationary distribution of this walk yields a group ranking. We analyze this random walk model, demonstrating that it enjoys many natural properties of a desirable ranking algorithm. We study groups on Twitter where conversations can be organized via pre-designated hashtags. These groups are an emerging phenomenon and there are at least tens of thousands in existence today according to our calculations. Via an extensive collection of experiments on one year of tweets, we show that our model effectively ranks groups, outperforming several baseline solutions.
Visible-Light-Emitting TS Lasers (1980)

Some characteristics of (GaAl)As TS (Terraced Substrate) lasers which emit visible radiation are reported. The threshold current density is found to depend little on the lasing wavelength down to 740 nm. The lasers exhibit a stable, single longitudinal mode oscillation with no kinks in the output-current curves over a wide range.
Large-Scale Parametrized Metasurface Design Using Adjoint Optimization (2021)

Optical metasurfaces are planar arrangements of subwavelength meta-atoms that implement a wide range of transformations on incident light. The design of efficient metasurfaces requires that the responses of and interactions among meta-atoms are accurately modeled. Conventionally, each meta-atom’s response is approximated by that of a meta-atom located in a periodic array. Although this approximation is accurate for metastructures with slowly varying meta-atoms, it does not accurately model the complex interactions among meta-atoms in more rapidly varying metasurfaces. Optimization-based design techniques that rely on full-wave simulations mitigate this problem but thus far have been mostly applied to topology optimization of small metasurfaces. Here, we describe an adjoint-optimization-based design technique that uses parametrized meta-atoms. Our technique has a lower computational cost than topology optimization approaches, enabling the design of large-scale metasurfaces that can be readily fabricated. As proof of concept, we present the design and experimental demonstration of high numerical aperture metalenses with significantly higher efficiencies than their conventionally designed counterparts.
vFtree - A Fat-Tree Routing Algorithm Using Virtual Lanes to Alleviate Congestion (2011)

It is a well known fact that multiple virtual lanes can improve performance in interconnection networks, but this knowledge has had little impact on real clusters. Currently, a large number of clusters using InfiniBand is based on fat-tree topologies that can be routed deadlock-free using only one virtual lane. Consequently, all the remaining virtual lanes are left unused. In this paper we suggest an enhancement to the fat-tree algorithm that utilizes virtual lanes to improve performance when hot-spots are present. Even though the bisection bandwidth in a fat-tree is constant, hot-spots are still possible and they will degrade performance for flows not contributing to them due to head-of-line blocking. Such a situation may be alleviated through adaptive routing or congestion control, however, these methods are not yet readily available in InfiniBand technology. To remedy this problem, we have implemented an enhanced fat-tree algorithm in OpenSM that distributes traffic across all available virtual lanes without any configuration needed. We evaluated the performance of the algorithm on a small cluster and did a large-scale evaluation through simulations. In a congested environment, results show that we are able to achieve throughput increases up to 38% on a small cluster and from 221% to 757% depending on the hot-spot scenario for a 648-port simulated cluster.
Learning Model Parameters for Decentralized Schedule-Driven Traffic Control (2020)

Model-based intersection optimization strategies that produce signal timings over a specified optimization horizon have been widely investigated for urban traffic signal control, and recent work in this area produced a scalable approach to real-time traffic control based on a decentralized schedule-driven optimization model. In this approach, a scheduling agent is associated with each intersection. Each agent senses the traffic approaching its intersection through local sensors and in real-time constructs a schedule that minimizes the cumulative wait time of vehicles approaching the intersection over the current look-ahead horizon. Intersections then exchange schedule information with their neighbors to achieve network level coordination. Although the approach is general and has demonstrated substantial success, its effectiveness in a given road network depends on the extent to which various parameters of the model, e.g, maximum green time, are adjusted to match that network's actual flow conditions over time. To address this problem, we propose a two-stage hierarchical structure that combines online planning and reinforcement learning. Reinforcement learning is applied to adjust the parameters of the model over a longer time-scale. On the other hand, online planning is used to compute the schedule for managing the traffic signals in the shorter term. We demonstrate how this hybrid approach outperforms the original approach in real-time traffic signal control problems.