gebhart/patrepeval huggingface dataset:
Chinese Medicine, Jiang-Tang-Ke-Li, Improves Insulin Resistance by Modulating Muscle Fiber Composition and Muscle Tumor Necrosis Factor-.ALPHA. in Fructose-Fed Rats (2003)

Insulin resistance and hyperinsulinemia are common findings in patients with essential hypertension. These impairments in glucose metabolism are commonly associated with diabetes mellitus, hypertension, and dyslipidemia, which are high risk factors of cardiovascular diseases, and recent evidence indicates that they may play a role in the development of coronary artery disease. The aim of this study was to determine the effect of Jiang-Tang-Ke-Li (JTKL), a traditional Chinese medicine used to treat diabetes mellitus in China, on insulin resistance and hypertension in fructose-fed rats (FFR). Systolic blood pressures in the FFR groups were significantly higher than that in the control group, although JTKL had no effect on systolic blood pressure for the last 2 weeks of treatment with the medicine. The average rate of glucose infusion during a glucose clamp, as an index of insulin sensitivity (M value), was significantly lower in the FFR than in the control rats, and treatment with JTKL for 2 weeks significantly increased the M value to that of the control. Treatment with Panax ginseng (PG), a component of JTKL, for 2 weeks also significantly increased the M value of FFR to the control level. The composite ratio of type I fibers in soleus muscle decreased significantly in the FFR compared to that in the control, and treatment with JTKL led to recovery of the composite ratio of type I fibers to the same level as that of the control group. The M value showed a significant positive correlation with the composite ratio of type I fibers and a significant negative correlation with the composite ratio of type II fibers. Tumor necrosis factor (TNF)-alpha levels were significantly higher in the soleus and extensor digitorum longus (EDL) muscles of the FFR than in those of the control rats. Treatment with JTKL for 2 weeks significantly lowered TNF-alpha levels to the control levels. M values showed a significant negative correlation with TNF-alpha in both the soleus and EDL muscles. The results suggest that the Chinese medicine JTKL, which contains PG as one of its valid components, improves insulin resistance by modulating muscle fiber composition and TNF-alpha in skeletal muscles in hypertensive and insulin-resistant FFR.
Van der Waals density functional theory with applications (2004)

Abstract The details of a density functional that includes van der Waals (vdW) interactions are presented. In particular we give some key steps of the transition from a form for fully planar systems to a procedure for realistic layered compounds that have planar symmetry only on large‐distance scales, and which have strong covalent bonds within the layers. It is shown that the random‐phase approximation of that original functional can be replaced by an approximation that is exact at large separation between vdW interacting fragments and seamless as the fragments merge. An approximation to the latter which renders the functional easily applicable and which preserves useful accuracy in both limits and in between is given. We report additional data from applications to forms of graphite, boron nitride, and molybdenum sulfide not reported in our previous communication. © 2005 Wiley Periodicals, Inc. Int J Quantum Chem, 2005
Molecular cloning and nucleotide sequence of cDNA for human liver arginase. (1987)

Arginase (EC 3.5.3.1) catalyzes the last step of the urea cycle in the liver of ureotelic animals. Inherited deficiency of the enzyme results in argininemia, an autosomal recessive disorder characterized by hyperammonemia. To facilitate investigation of the enzyme and gene structures and to elucidate the nature of the mutation in argininemia, we isolated cDNA clones for human liver arginase. Oligo(dT)-primed and random primer human liver cDNA libraries in lambda gt11 were screened using isolated rat arginase cDNA as a probe. Two of the positive clones, designated lambda hARG6 and lambda hARG109, contained an overlapping cDNA sequence with an open reading frame encoding a polypeptide of 322 amino acid residues (predicted Mr, 34,732), a 5'-untranslated sequence of 56 base pairs, a 3'-untranslated sequence of 423 base pairs, and a poly(A) segment. Arginase activity was detected in Escherichia coli cells transformed with the plasmid carrying lambda hARG6 cDNA insert. RNA gel blot analysis of human liver RNA showed a single mRNA of 1.6 kilobases. The predicted amino acid sequence of human liver arginase is 87% and 41% identical with those of the rat liver and yeast enzymes, respectively. There are several highly conserved segments among the human, rat, and yeast enzymes.
Self-tuning speculation for maintaining the consistency of client-cached data (2004)

This paper presents a new protocol, self-tuning active data-aware cache consistency (SADCC), which employs parallel communication and self-tuning speculation to improve the performance of data-shipping database systems. Using parallel communication with simultaneous client-server and client-client communication, SADCC reduces the network latency for detecting data conflicts by 50%, while increasing message volume overhead by only about 4.8%. By being aware of the global states of cached data, clients self-tune between optimistic and pessimistic consistency control. The abort rate is reduced by statistically quantifying the speculation cost. We compare SADCC with the leading cache consistency algorithms, active data-aware cache consistency (ADCC) and asynchronous avoidance-based cache consistency (AACC), in a page server DBMS architecture with page-level consistency. The experiments show that, in a non-contention environment, both SADCC and ADCC display a slight reduction (an average of 2.3%) in performance compared to AACC with a high-speed network environment. With high contention, however, SADCC has an average of 14% higher throughput than AACC and 6% higher throughput than ADCC.
Safety and Abuse Testing of Energizer LiFeS2 AA Cells (2003)

The LiFeS2 test program was part of the study on state-of-the-art batteries/cells available in the commercial market. It was carried out in an effort to replace alkaline AA cells for Shuttle and Station applications. A large number of alkaline cells are used for numerous Shuttle and Station applications as loose cells. Other government agencies reported good performance and abuse tolerance of the AA LiFeS2 cells. In this study, only abuse testing was performed on the cells to determine their tolerance. The tests carried out were over-discharge, external short circuit, heat-to-vent, vibration and drop.
Microgravity Reduces Sleep-disordered Breathing in Humans (2001)

To understand the factors that alter sleep quality in space, we studied the effect of spaceflight on sleep-disordered breathing. We analyzed 77 8-h, full polysomnographic recordings (PSGs) from five healthy subjects before spaceflight, on four occasions per subject during either a 16- or 9-d space shuttle mission and shortly after return to earth. Microgravity was associated with a 55% reduction in the apnea-hypopnea index (AHI), which decreased from a preflight value of 8.3 +/- 1.6 to 3.4 +/- 0.8 events/h inflight. This reduction in AHI was accompanied by a virtual elimination of snoring, which fell from 16.5 +/- 3.0% of total sleep time preflight to 0.7 +/- 0.5% inflight. Electroencephalogram (EEG) arousals also decreased in microgravity (by 19%), and this decrease was almost entirely a consequence of the reduction in respiratory-related arousals, which fell from 5.5 +/- 1.2 arousals/h preflight to 1.8 +/- 0.6 inflight. Postflight there was a return to near or slightly above preflight levels in these variables. We conclude that sleep quality during spaceflight is not degraded by sleep-disordered breathing. This is the first direct demonstration that gravity plays a dominant role in the generation of apneas, hypopneas, and snoring in healthy subjects.
Speaker identification using multimodal neural networks and wavelet analysis (2015)

The rapid momentum of the technology progress in the recent years has led to a tremendous rise in the use of biometric authentication systems. The objective of this research is to investigate the problem of identifying a speaker from its voice regardless of the content. In this study, the authors designed and implemented a novel text‐independent multimodal speaker identification system based on wavelet analysis and neural networks. Wavelet analysis comprises discrete wavelet transform, wavelet packet transform, wavelet sub‐band coding and Mel‐frequency cepstral coefficients (MFCCs). The learning module comprises general regressive, probabilistic and radial basis function neural networks, forming decisions through a majority voting scheme. The system was found to be competitive and it improved the identification rate by 15% as compared with the classical MFCC. In addition, it reduced the identification time by 40% as compared with the back‐propagation neural network, Gaussian mixture model and principal component analysis. Performance tests conducted using the GRID database corpora have shown that this approach has faster identification time and greater accuracy compared with traditional approaches, and it is applicable to real‐time, text‐independent speaker identification systems.
A novel defense against hemolytic-oxidative stress (2006)

Comment on Nielsen et al, page [2846][1]

The findings of Nielsen and colleagues that haptoglobin-related protein (Hpr) binds to free hemoglobin as avidly as haptoglobin emphasize the critical redundancy in hemoglobin clearance mechanisms and suggest the existence of intravascular cross talk between
Mechanical Transduction in Outer Hair Cells (2002)

The outer hair cells are responsible for the exquisite sensitivity, frequency selectivity and dynamic range of the cochlea. These cells are part of a mechanical feedback system involving the basilar membrane and tectorial membrane. Transverse displacement of the basilar membrane results in relative motion between the tectorial membrane and the reticular lamina, causing deflection of the stereocilia and modulation of the open probability of their transduction channels. The resulting current causes a change of membrane potential, which in turn produces mechanical force, that is fed back into the motion of the basilar membrane. Experiments were conducted to address mechanical transduction mechanisms in both the stereocilia and the basolateral cell membrane, as well as modes of coupling of the outer hair cell force to the organ of Corti.
Partition Systems of Bacterial Plasmids (2014)

Plasmids, as extrachromosomal elements, bear the burden of ensuring their own faithful segregation at cell division. This chapter reviews partition systems, which are, in general, systems that actively dictate the specific localization of plasmids inside the bacterial cell and coordinate this localization with the bacterial cell cycle. Partition systems also exert incompatibility, which is distinct from the replication-mediated incompatibility that has been used to classify plasmids. Growth of the membrane between attachment sites was proposed to push plasmids apart. It was subsequently shown that membrane growth is dispersive and thus cannot solely account for plasmid movement. An appealing candidate for the plasmid road sign is the bacterial replication apparatus. Experiments in Escherichia coli and Bacillus subtilis indicate that the replication machinery exists as localized factories in the cell. The intracellular localization patterns of the ParA from the E. coli virulence plasmid pB171 provide an intriguing clue as to the mechanism of ParA function. RepA and RepB are not essential for replication but are essential for plasmid stability. They have been shown to influence copy number, but this may be due to effects on the expression of repC. Recent cell biology, biochemical, and structural data show that R1 ParM looks and behaves like actin and suggest a partition model in which ParM acts as a cytoskeletal element to drive the movement of plasmids during the cell cycle.
OC07.04: Slow growth, versus small for gestational age, at the last scan as predictors of stillbirth risk (2021)

Fetal growth assessment is central to good antenatal care, yet there is a lack of definition of normal and abnormal growth rate which accounts for measurement interval and is predictive of pregnancy outcome. We studied a cohort of 102,081 singleton pregnancies which had at least two third trimester measurements of ultrasound scan estimated fetal weight (EFW). We projected the customised EFW centile from the first of each measurement pair to the gestational age of the second scan, and calculated the deviation of the second EFW from this projected weight. We grouped the interval between scans into eight categories (1-8 weeks), and undertook for each category a partial receiver operator curve analysis (pROC) by fixing the false positive rate (FP) at 10%. Slow growth based on the last two scans and compared with small for gestational age (SGA, < 10th centile) EFW at last scan, using stillbirth risk as outcome, calculated as relative risk (RR) and 95% confidence interval (CI). The average gestational age of the last two scans was 32 + 6 and 36 + 4 weeks. There were in total 12,196 (11.9%) of pregnancies with slow growth and 9,617 (9.4%) with small for gestational age (SGA) at the last scan. The table shows increased stillbirth risk in pregnancies with slow growth and SGA as well as with slow growth only and SGA at last scan only. 8081 of the 12,196 fetuses with slow growth (66.4%) were not SGA at last scan. Defining slow growth by customised projection and measurement interval specific limits helps to identify pregnancies at risk of stillbirth which are not SGA in late pregnancy.
Development of Models to Simulate Tracer Tests for Characterization of Enhanced Geothermal Systems (2013)

A recent report found that power and heat produced from enhanced (or engineered) geothermal systems (EGSs) could have a major impact on the U.S energy production capability while having a minimal impact on the environment. EGS resources differ from high-grade hydrothermal resources in that they lack sufficient temperature distribution, permeability/porosity, fluid saturation, or recharge of reservoir fluids. Therefore, quantitative characterization of temperature distributions and the surface area available for heat transfer in EGS is necessary for the design and commercial development of the geothermal energy of a potential EGS site. The goal of this project is to provide integrated tracer and tracer interpretation tools to facilitate this characterization. This project was initially focused on tracer development with the application of perfluorinated tracer (PFT) compounds, non-reactive tracers used in numerous applications from atmospheric transport to underground leak detection, to geothermal systems, and evaluation of encapsulated PFTs that would release tracers at targeted reservoir temperatures. After the 2011 midyear review and subsequent discussions with the U.S. Department of Energy Geothermal Technology Program (GTP), emphasis was shifted to interpretive tool development, testing, and validation. Subsurface modeling capabilities are an important component of this project for both the design of suitable tracers and the interpretation of data from in situ tracer tests, be they single- or multi-well tests. The purpose of this report is to describe the results of the tracer and model development for simulating and conducting tracer tests for characterizing EGS parameters.
Disentangling factors of variation in deep representations using\n adversarial training (2016)

We introduce a conditional generative model for learning to disentangle the\nhidden factors of variation within a set of labeled observations, and separate\nthem into complementary codes. One code summarizes the specified factors of\nvariation associated with the labels. The other summarizes the remaining\nunspecified variability. During training, the only available source of\nsupervision comes from our ability to distinguish among different observations\nbelonging to the same class. Examples of such observations include images of a\nset of labeled objects captured at different viewpoints, or recordings of set\nof speakers dictating multiple phrases. In both instances, the intra-class\ndiversity is the source of the unspecified factors of variation: each object is\nobserved at multiple viewpoints, and each speaker dictates multiple phrases.\nLearning to disentangle the specified factors from the unspecified ones becomes\neasier when strong supervision is possible. Suppose that during training, we\nhave access to pairs of images, where each pair shows two different objects\ncaptured from the same viewpoint. This source of alignment allows us to solve\nour task using existing methods. However, labels for the unspecified factors\nare usually unavailable in realistic scenarios where data acquisition is not\nstrictly controlled. We address the problem of disentanglement in this more\ngeneral setting by combining deep convolutional autoencoders with a form of\nadversarial training. Both factors of variation are implicitly captured in the\norganization of the learned embedding space, and can be used for solving\nsingle-image analogies. Experimental results on synthetic and real datasets\nshow that the proposed method is capable of generalizing to unseen classes and\nintra-class variabilities.\n
VEGF-B is dispensable for blood vessel growth but critical for their survival, and VEGF-B targeting inhibits pathological angiogenesis (2009)

VEGF-B, a homolog of VEGF discovered a long time ago, has not been considered an important target in antiangiogenic therapy. Instead, it has received little attention from the field. In this study, using different animal models and multiple types of vascular cells, we revealed that although VEGF-B is dispensable for blood vessel growth, it is critical for their survival. Importantly, the survival effect of VEGF-B is not only on vascular endothelial cells, but also on pericytes, smooth muscle cells, and vascular stem/progenitor cells. In vivo, VEGF-B targeting inhibited both choroidal and retinal neovascularization. Mechanistically, we found that the vascular survival effect of VEGF-B is achieved by regulating the expression of many vascular prosurvival genes via both NP-1 and VEGFR-1. Our work thus indicates that the function of VEGF-B in the vascular system is to act as a "survival," rather than an "angiogenic" factor and that VEGF-B inhibition may offer new therapeutic opportunities to treat neovascular diseases.
Dual Role of Deep Eutectic Solvent as a Solvent and Template for the Synthesis of Octahedral Cobalt Vanadate for an Oxygen Evolution Reaction (2018)

In this study, the deep eutectic solvent (DES)-aided synthesis of γ-CoV2O6 under modest reaction conditions using 1:1 choline chloride–malonic acid was reported. In the presence of DES, the reaction occurred at a lower temperature (500 °C) compared with that of the respective conventional solid-state synthesis of metal oxides and also with the calcination process involving the metal salts, thereby decreasing the overall formation energy. Differential scanning calorimetry revealed a 2-fold decrease in the endo effect of the thermodestruction of DES, which was observed at a low temperature. The structural pathway taken during the phase and morphology formation was investigated by in situ and ex situ X-ray diffraction (XRD) analysis, Raman spectroscopy, and scanning electron microscopy. The in situ XRD results confirmed the presence of high-temperature α-CoV2O6, which was finally converted to γ-CoV2O6. On account of the metal speciation in DES similar to the biotemplate, well-defined octahedral CoV2O6 nanocrystals were obtained, which exhibited a remarkable OER catalytic activity at current density of 10 mA/cm2 with an overpotential of a mere 324 mV, with excellent durability for greater than 24 h. Thus, a designer DES solvent with characteristics of biodegradability, cost-effectiveness, and renewability demonstrates potential for the synthesis of noble-metal-free oxygen evolution reaction (OER) catalysts, which allows the present synthesis route to fit well within the merits of green chemistry.
Supervised Tractogram Filtering using Geometric Deep Learning (2022)

A tractogram is a virtual representation of the brain white matter. It is composed of millions of virtual fibers, encoded as 3D polylines, which approximate the white matter axonal pathways. To date, tractograms are the most accurate white matter representation and thus are used for tasks like presurgical planning and investigations of neuroplasticity, brain disorders, or brain networks. However, it is a well-known issue that a large portion of tractogram fibers is not anatomically plausible and can be considered artifacts of the tracking procedure. With Verifyber, we tackle the problem of filtering out such non-plausible fibers using a novel fully-supervised learning approach. Differently from other approaches based on signal reconstruction and/or brain topology regularization, we guide our method with the existing anatomical knowledge of the white matter. Using tractograms annotated according to anatomical principles, we train our model, Verifyber, to classify fibers as either anatomically plausible or non-plausible. The proposed Verifyber model is an original Geometric Deep Learning method that can deal with variable size fibers, while being invariant to fiber orientation. Our model considers each fiber as a graph of points, and by learning features of the edges between consecutive points via the proposed sequence Edge Convolution, it can capture the underlying anatomical properties. The output filtering results highly accurate and robust across an extensive set of experiments, and fast; with a 12GB GPU, filtering a tractogram of 1M fibers requires less than a minute. Verifyber implementation and trained models are available at https://github.com/FBK-NILab/verifyber.
Demographic profile of blood donors at three major Brazilian blood centers: results from the International REDS‐II study, 2007 to 2008 (2009)

Donors in the three Brazilian centers tended to be younger with a higher proportion of males than in the general population. Donation rates were lower than desirable. There were substantial differences in sex, age, and community/replacement status by center. Studies on the safety, donation frequencies, and motivations of donors are in progress to orient efforts to enhance the availability of blood.
Enhanced antibacterial and antiparasitic activity of multifunctional polymeric nanoparticles (2020)

Due to the resistance to drugs, studies involving the combination and controlled release of different agents are gradually increasing. In this study, two different active ingredients, known to have antibacterial and antiparasitic activities, were encapsulated into single polymeric nanoparticles. After co-encapsulation their antibacterial and antileishmanial activity was enhanced approximately 5 and 250 times, respectively. Antibacterial and antileishmanial activities of caffeic acid phenethyl ester and juglone loaded, multifunctional nanoformulations (CJ4-CJ6-CJ8) were also evaluated for the first time in the literature comparatively with their combined free formulations. The antibacterial activity of the multifunctional nanoformulation (CJ8) were found to have a much higher activity (MIC values 6.25 and 12.5 μg ml<sup>-1</sup> for S. aureus and E. coli, respectively) than all other formulations. Similar efficacy for CJ8 was obtained in the antiparasitic study against the Leishmania promastigotes and the IC<sub>50</sub> was reduced to 0.1263 μg ml<sup>-1</sup>. The high activity of multifunctional nanoparticles is not only due to the synergistic effect of the active molecules but also by the encapsulation into polymeric nanoparticles. Therefore, it has been shown in the literature for the first time that the biological activity of molecules whose activity is increased by the synergistic effect can be improved with nanosystems.