gebhart/patrepeval huggingface dataset:
Demonstrating NaturalMiner: Searching Large Data Sets for Abstract Patterns Described in Natural Language (2023)

The NaturalMiner system seeks to extract facts from large relational data sets that match abstract patterns defined in natural language. For instance, this enables users to search, with regards to a specific airline, for evidence that "the airline underperforms" or "the airline outperforms'' within a data set containing flight statistics, hinting at areas for improvements or strengths to advertise.
Biocompatible Polymeric Nanoparticles Degrade and Release Cargo in Response to Biologically Relevant Levels of Hydrogen Peroxide (2012)

Oxidative stress is caused predominantly by accumulation of hydrogen peroxide and distinguishes inflamed tissue from healthy tissue. Hydrogen peroxide could potentially be useful as a stimulus for targeted drug delivery to diseased tissue. However, current polymeric systems are not sensitive to biologically relevant concentrations of H(2)O(2) (50-100 μM). Here we report a new biocompatible polymeric capsule capable of undergoing backbone degradation and thus release upon exposure to such concentrations of hydrogen peroxide. Two polymeric structures were developed differing with respect to the linkage between the boronic ester group and the polymeric backbone: either direct (1) or via an ether linkage (2). Both polymers are stable in aqueous solution at normal pH, and exposure to peroxide induces the removal of the boronic ester protecting groups at physiological pH and temperature, revealing phenols along the backbone, which undergo quinone methide rearrangement to lead to polymer degradation. Considerably faster backbone degradation was observed for polymer 2 over polymer 1 by NMR and GPC. Nanoparticles were formulated from these novel materials to analyze their oxidation triggered release properties. While nanoparticles formulated from polymer 1 only released 50% of the reporter dye after exposure to 1 mM H(2)O(2) for 26 h, nanoparticles formulated from polymer 2 did so within 10 h and were able to release their cargo selectively in biologically relevant concentrations of H(2)O(2). Nanoparticles formulated from polymer 2 showed a 2-fold enhancement of release upon incubation with activated neutrophils, while controls showed a nonspecific response to ROS producing cells. These polymers represent a novel, biologically relevant, and biocompatible approach to biodegradable H(2)O(2)-triggered release systems that can degrade into small molecules, release their cargo, and should be easily cleared by the body.
Uniform Perceptual Quantization: Applications to Digital Radiography (1987)

The principle involved in the uniform quantization of perceived lightness is considered in the context of digital radiography. Its effects on the visibility of quantization noise (contouring artifacts) are investigated both analytically and experimentally. Several visual system models of perceived lightness as a function of stimulus luminance are used. These include a logarithmic model, various power function models, and cone models. The results can be extended for other digital imaging modalities.
HIGH‐THROUGHPUT SCREENING BY TRACTION MICROSCOPY (2013)

For discovery of novel drugs impacting contractile cells, such as human airway smooth muscle (HASM) cells, a high‐throughput screening (HTS) assay based upon contractility might be useful but no such HTS assay yet exists. To fill this gap, we have developed a new method called high‐throughput traction microscopy (HTTM). HTTM measures drug‐induced changes in contractile forces (tractions) exerted by adherent cells upon elastic substrates. Used together with soft gels in 96‐well plates and a motorized microscope, HTTM provides a HTS platform to screen large drug libraries and identify as hits those molecules that change cellular tractions. To demonstrate proof of concept, we used HASM cells and screened a library of 10,000 small molecular compounds. By screening mixtures of 8 compounds simultaneously, we were able to evaluate 2,000 compounds per week in quadruplicate with the possibility of attaining substantially higher throughputs. After retesting individual compounds from initially positive wells, we identified 8 individual compounds that relaxed HASM cells. For any cell type and disease process in which contractile forces are thought to play a functional role, HTTM provides a convenient, rapid, and inexpensive platform for drug discovery based upon a physiological endpoint, namely, cell contractile force. (NIH P50HL107171, Lung tissues are the generous gift from Gift of Hope.)
Predicting individual improvement in schizophrenia symptom severity at 1‐year follow‐up: Comparison of connectomic, structural, and clinical predictors (2020)

In a machine learning setting, this study aims to compare the prognostic utility of connectomic, brain structural, and clinical/demographic predictors of individual change in symptom severity in individuals with schizophrenia. Symptom severity at baseline and 1-year follow-up was assessed in 30 individuals with a schizophrenia-spectrum disorder using the Brief Psychiatric Rating Scale. Structural and functional neuroimaging was acquired in all individuals at baseline. Machine learning classifiers were trained to predict whether individuals improved or worsened with respect to positive, negative, and overall symptom severity. Classifiers were trained using various combinations of predictors, including regional cortical thickness and gray matter volume, static and dynamic resting-state connectivity, and/or baseline clinical and demographic variables. Relative change in overall symptom severity between baseline and 1-year follow-up varied markedly among individuals (interquartile range: 55%). Dynamic resting-state connectivity measured within the default-mode network was the most accurate single predictor of change in positive (accuracy: 87%), negative (83%), and overall symptom severity (77%) at follow-up. Incorporating predictors based on regional cortical thickness, gray matter volume, and baseline clinical variables did not markedly improve prediction accuracy and the prognostic utility of these predictors in isolation was moderate (<70%). Worsening negative symptoms at 1-year follow-up were predicted by hyper-connectivity and hypo-dynamism within the default-mode network at baseline assessment, while hypo-connectivity and hyper-dynamism predicted worsening positive symptoms. Given the modest sample size investigated, we recommend giving precedence to the relative ranking of the predictors investigated in this study, rather than the prediction accuracy estimates.
Laser ablation and micromachining with ultrashort laser pulses (1997)

The mechanisms of ultrashort-pulse laser ablation of materials are discussed, and the differences to that of long laser pulses are emphasized. Ultrashort laser pulses offer both high laser intensity and precise laser-induced breakdown threshold with reduced laser fluence. The ablation of materials with ultrashort pulses has a very limited heat-affected volume. The advantages of ultrashort laser pulses are applied in precision micromachining of various materials. Some femtosecond laser pulse micromachining results, including comparison with long pulses, are presented. Ultrashort-pulse laser micromachining may have a wide range of applications where micrometer and submicrometer feature sizes are required.
Analyzing three-player quantum games in an EPR type setup using geometric algebra (2010)

We use the formalism of Clifford Geometric Algebra (GA) to develop an analysis of quantum versions of three-player non-cooperative games. The quantum games we explore are played in an Einstein-Podolsky-Rosen (EPR) type setting. In this setting, the players' strategy sets remain identical to the ones in the mixed-strategy version of the classical game that is obtained as a proper subset of the corresponding quantum game. Using GA we investigate the outcome of a realization of the game by players sharing GHZ state, W state, and a mixture of GHZ and W states. As a specific example, we study the game of three-player Prisoners' Dilemma.
Automatic post-stroke lesion segmentation on MR images using 3D residual convolutional neural network (2020)

In this paper, we demonstrate the feasibility and performance of deep residual neural networks for volumetric segmentation of irreversibly damaged brain tissue lesions on T1-weighted MRI scans for chronic stroke patients. A total of 239 T1-weighted MRI scans of chronic ischemic stroke patients from a public dataset were retrospectively analyzed by 3D deep convolutional segmentation models with residual learning, using a novel zoom-in&out strategy. Dice similarity coefficient (DSC), average symmetric surface distance (ASSD), and Hausdorff distance (HD) of the identified lesions were measured by using manual tracing of lesions as the reference standard. Bootstrapping was employed for all metrics to estimate 95% confidence intervals. The models were assessed on a test set of 31 scans. The average DSC was 0.64 (0.51-0.76) with a median of 0.78. ASSD and HD were 3.6 mm (1.7-6.2 mm) and 20.4 mm (10.0-33.3 mm), respectively. The latest deep learning architecture and techniques were applied with 3D segmentation on MRI scans and demonstrated effectiveness for volumetric segmentation of chronic ischemic stroke lesions.
Anticonvulsant profile of flunarizine (1986)

Abstract The purpose of the study was to examine in a multi‐experimental profile the purported similarity between the anticonvulsant effects of flunarizine, diphenylhydantoin, and carbamazepine. The compounds were injected at different time intervals and by different routes, and their effects were examined in a genetic model of epilepsy (audiogenic seizures in mice), against maximal seizures induced by bicuculline in mice and rats and in a seizurethreshold test (bicuculline infusion) in rats. All three compounds primarily affected tonic seizures. In the bicuculline seizure test, this was an all‐or‐none effect. In this test, flunarizine differed from diphenylhydantoin and carbamazepine in that it increased the threshold for clonic‐hindpaw seizures. Thus, flunarizine, apart from antagonizing tonic seizures, also increased the threshold for generalization. Further, in agreement with previous experiments (maximal metrazol test and kindling), the duration of action of flunarizine is longer than that of diphenylhydantoin and carbamazepine. Finally, the degree of ataxia and neurological deficits caused by a high p.o. dosis of flunarizine was assessed. A slight neurological deficit and ataxia occurred 1 hr after p.o. administration of 160 mg/kg of flunarizine. By way of analogy with diphenylhydantoin, as a working hypothesis, it is suggested that the anticonvulsant actions of flunarizine result from reducing Na + currents in neurons, although a direct effect on Ca 2+ movements cannot be excluded.
Inter-species variation in monovalent anion substrate selectivity and inhibitor sensitivity in the sodium iodide symporter (NIS) (2020)

The sodium iodide symporter (NIS) transports iodide, which is necessary for thyroid hormone production. NIS also transports other monovalent anions such as tetrafluoroborate (BF4-), pertechnetate (TcO4-), and thiocyanate (SCN-), and is competitively inhibited by perchlorate (ClO4-). However, the mechanisms of substrate selectivity and inhibitor sensitivity are poorly understood. Here, a comparative approach was taken to determine whether naturally evolved NIS proteins exhibit variability in their substrate transport properties. The NIS proteins of thirteen animal species were initially assessed, and three species from environments with differing iodide availability, freshwater species Danio rerio (zebrafish), saltwater species Balaenoptera acutorostrata scammoni (minke whale), and non-aquatic mammalian species Homo sapiens (human) were studied in detail. NIS genes from each of these species were lentivirally transduced into HeLa cells, which were then characterized using radioisotope uptake assays, 125I- competitive substrate uptake assays, and kinetic assays. Homology models of human, minke whale and zebrafish NIS were used to evaluate sequence-dependent impact on the organization of Na+ and I- binding pockets. Whereas each of the three proteins that were analyzed in detail concentrated iodide to a similar degree, their sensitivity to perchlorate inhibition varied significantly: minke whale NIS was the least impacted by perchlorate inhibition (IC50 = 4.599 μM), zebrafish NIS was highly sensitive (IC50 = 0.081 μM), and human NIS showed intermediate sensitivity (IC50 = 1.566 μM). Further studies with fifteen additional substrates and inhibitors revealed similar patterns of iodide uptake inhibition, though the degree of 125I- uptake inhibition varied with each compound. Kinetic analysis revealed whale NIS had the lowest Km-I and the highest Vmax-I. Conversely, zebrafish NIS had the highest Km and lowest Vmax. Again, human NIS was intermediate. Molecular modeling revealed a high degree of conservation in the putative ion binding pockets of NIS proteins from different species, which suggests the residues responsible for the observed differences in substrate selectivity lie elsewhere in the protein. Ongoing studies are focusing on residues in the extracellular loops of NIS as determinants of anion specificity. These data demonstrate significant transport differences between the NIS proteins of different species, which may be influenced by the unique physiological needs of each organism. Our results also identify naturally-existing NIS proteins with significant variability in substrate transport kinetics and inhibitor sensitivity, which suggest that the affinity and selectivity of NIS for certain substrates can be altered for biotechnological and clinical applications. Further examination of interspecies differences may improve understanding of the substrate transport mechanism.
A Modified DC Power Electronic Transformer Based on Series Connection of Full-Bridge Converters (2018)

This paper proposes a novel dc power electronic transformer (DCPET) topology for locomotive, ac/dc hybrid grid, dc distribution grid, and other isolated medium-voltage and high-power applications. Compared with conventional PET topology, the proposed DCPET has fewer power semiconductor devices and high-frequency isolation transformers, which can improve the power density and reliability. Fault handling or redundancy design can be achieved to further improve the reliability when some dc-dc modules break down. Also, input voltage sharing control can be omitted to simplify the control system and improve the stability. Meanwhile, soft switching is guaranteed for all the switches, which is beneficial to increase switching frequency and improve power density. In this paper, the principle, evolution, and control of the proposed DCPET are respectively presented and studied in detail. Finally, a prototype of the proposed DCPET is built and the experimental results verify the validity and superiority of the proposed topology.
α-Trifluoromethyl-β-Ureido-Propionic Acid (F3MUPA): A New Metabolite of Trifluridine (F3TdR) (1993)

Abstract The metabolism of 5-trifluro-2′-deoxythymidine (trifluridine; F3TdR) in male BALB/c mice bearing EMT-6 tumors has been investigated using 19F NMR spectroscopy. We previously (Tandon et al, 1992) reported the detection and identification of 5,6-dihydro-5-trifluorothymine (DHF3T, 3) and 5,6-dihydroxy-5-trifluorothymine (DOHF3T) as new metabolites of F3TdR in mice urine. Further exploration of the metabolism of trifluridine has led to the identification of α-trifluoromethyl-β-ureido-propionic acid (F3MUPA, 4) as a previously unreported metabolite in the urine of F3TdR treated mice. Authentic F3MUPA was obtained by synthesis via an established route. A comparison of chemical shift and the H-F coupling constant of an authentic sample, with the 19F signal from urine, indicated the presence of F3MUPA in murine urine. Mixing crude urine with authentic F3MUPA resulted in the enhancement of the corresponding fluorine signal without affecting or introducing others, thereby confirming the presence of F3MUPA as a urinary metabolite.
Combining SELEX with quantitative assays to rapidly obtain accurate models of protein-DNA interactions (2005)

Models for the specificity of DNA-binding transcription factors are often based on small amounts of qualitative data and therefore have limited accuracy. In this study we demonstrate a simple and efficient method of affinity chromatography-SELEX followed by a quantitative binding (QuMFRA) assay to rapidly collect the data necessary for more accurate models. Using the zinc finger protein EGR as an e.g. we show that many bindings sites can be obtained efficiently with affinity chromatography-SELEX, but those sequences alone provide a weight matrix model with limited accuracy. Using a QuMFRA assay to determine the quantitative relative affinity for only a subset of the sequences obtained by SELEX leads to a much more accurate model. Application of this method to variants of a transcription factor would allow us to generate a large collection of quantitative data for modeling protein-DNA interactions that could facilitate the determination of recognition codes for different transcription factor families.
A Computerized Recognition System for the Home-Based Physiotherapy Exercises Using an RGBD Camera (2014)

Computerized recognition of the home based physiotherapy exercises has many benefits and it has attracted considerable interest among the computer vision community. However, most methods in the literature view this task as a special case of motion recognition. In contrast, we propose to employ the three main components of a physiotherapy exercise (the motion patterns, the stance knowledge, and the exercise object) as different recognition tasks and embed them separately into the recognition system. The low level information about each component is gathered using machine learning methods. Then, we use a generative Bayesian network to recognize the exercise types by combining the information from these sources at an abstract level, which takes the advantage of domain knowledge for a more robust system. Finally, a novel postprocessing step is employed to estimate the exercise repetitions counts. The performance evaluation of the system is conducted with a new dataset which contains RGB (red, green, and blue) and depth videos of home-based exercise sessions for commonly applied shoulder and knee exercises. The proposed system works without any body-part segmentation, bodypart tracking, joint detection, and temporal segmentation methods. In the end, favorable exercise recognition rates and encouraging results on the estimation of repetition counts are obtained.
A Novel Radical SAM mechanism mediated by the Interferon‐Inducible Protein Viperin (2018)

To survive infection the immune system deploys an arsenal of defensive measures to combat invading pathogens. The type I interferon (IFN) response presents an early host defense by generating an intracellular environment that restricts virus replication and signals the presence of a viral pathogen to the adaptive arm of the immune response. Viperin ( v irus i nhibitory p rotein, e ndoplasmic r eticulum‐associated, in terferon‐inducible) is an interferon stimulated gene (ISG), that is induced by type I, II, and III IFNs, or after infection by a broad range of DNA and RNA viruses. Viperin contains an S‐adenosyl‐L‐methionine (SAM) domain and an N‐terminal amphipathic helix that contributes to its antiviral activity by localizing viperin to ER membranes or lipid droplets. Viperin has been found to require ER localization for full antiviral activity and mutation of the cysteine residues (CX 3 CX 2 C motif) ligating the Fe‐S cluster in the central radical SAM domain entirely abolished antiviral activity. Viperin induces a cascade of signaling events to mount an immune response against the viral replication; however, the exact molecular basis for viperin's cellular activity and the role of SAM‐dependent reactions in inhibiting viral synthesis remains unknown. Our studies suggest that the radical SAM activity of viperin is critical for activation of innate immune signaling. The enzyme localizes the E3 ubiquitin ligase TRAF6 and the interleukin 1 receptor‐associated kinase (IRAK1) to the endoplasmic reticulum and activates TRAF6 to catalyze polyubiquitylation of IRAK1, key step in the Toll‐like receptor‐7 (TLR) and TLR‐9 signaling pathways. Our data implicates the radical SAM activity of viperin is essential in this activation step. We found that in presence of IRAK1 and TRAF6 the reductive cleavage of SAM to form 5′‐deoxyadenosine is increased ~ 4‐fold. Thus, our data provides the first evidence that viperin's radical SAM activity is linked to activation of a ubiquitin ligase. This observation has implications for how the enzyme may exert its multifaceted roles in the cellular antiviral response. Support or Funding Information This work was supported in part by NIH grants GM 093088 to E.N.G.M. and DK 046960 to R.T.K. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
Stimulated rotational Raman scattering of arbitrarily polarized broadband light (2020)

Laser plasma instabilities are problematic for inertial confinement fusion because they can spoil illumination uniformity, reduce laser-target coupling, and create unwanted fast electrons. Recent experiments and simulations have shown that self-seeded stimulated rotational Raman scattering (SRRS) in air might achieve enough spectral broadening to mitigate these instabilities with only moderate unwanted broadening of the focal spot. The theoretical model for the simulations included chaotic broadband and spatially multimode light, but was a scalar formulation suitable for only linear polarization, where the SRRS gains and spectral broadening are limited by Stokes--anti-Stokes coupling. This paper derives a tensor formulation of SRRS theory suitable for modeling spectral broadening of arbitrarily polarized spatially and temporally incoherent light; it then describes the algorithms used to simulate the theory and provides some preliminary results that compare linear and elliptical polarizations. It begins with a paraxial wave equation for an arbitrarily polarized optical field envelope, which is phase modulated by a term proportional to a Raman driven molecular polarizability tensor. Treating the air molecules as rigid rotators, it uses a quantum treatment to derive a driven harmonic oscillator equation for that polarizability, then expresses these vector and tensor equations in terms of the field's right- and left-handed circular polarization components to derive the final coupled equations for arbitrary polarization. The formulation includes possible ac Stark shift contributions, but shows that they are negligible for intensities below $10\phantom{\rule{0.16em}{0ex}}\mathrm{GW}/{\mathrm{cm}}^{2}$. It then describes the algorithms used in the simulation code and the numerical model of the chaotic light, whose initial spectral bandwidth is broad enough to self-seed the SRRS. In this algorithm, the SRRS process accurately conserves the total energy at each axial plane along the propagation path. Finally, it compares simulations of power spectra and far-field profiles for elliptical vs linear polarization, which show that elliptically polarized light produces significantly more broadening of both profiles than linear polarization. For linear polarization, the SRRS process reduces the incident coherence time from 0.54 to 0.27 ps; for elliptical polarization, it reduces to 0.19 ps. The theory and simulation algorithms presented here provide a framework for evaluating techniques that combine beams of alternating circular polarizations with different spectra and angular divergences to improve SRRS spectral broadening without excessive focal spot broadening.