gebhart/patrepeval huggingface dataset:
Organic anions and potassium salts in nutrition and metabolism (2004)

The present review examines the importance of dietary organic anions in preventive nutrition. Organic anions are chiefly supplied by plant foods, as partially neutralised K salts such as potassium citrate, potassium malate and, to a lesser extent, oxalate or tartrate salts. Animal products may also supply K anions, essentially as phosphate, but also as lactate as a result of fermentative or maturation processes, but these K salts have little alkalinising significance. Citrate and malate anions are absorbed in the upper digestive tract, while a substantial proportion is probably metabolised in the splanchnic area. Whatever their site of metabolism, these anions finally yield KHCO3 which is used by the kidneys to neutralise fixed acidity. This acidity essentially reflects the oxidation of excess S amino acids to sulfate ions, which is mainly related to the dietary protein level. Failure to neutralise acidity leads to low-grade metabolic acidosis, with possible long-term deleterious effects on bone Ca status and on protein status. Furthermore, low-grade acidosis is liable to affect other metabolic processes, such as peroxidation of biological structures. These metabolic disturbances could be connected with the relatively high incidence of osteoporosis and muscle-protein wasting problems observed in ageing individuals in Europe and Northern America. Providing a sufficient supply of K organic anions through fruit and vegetable intake should be recommended, fostering the actual motivational campaigns ('five (or ten) per d') already launched to promote the intake of plant foods rich in complex carbohydrates and various micronutrients.
Operating Limits of Spark-Assisted Compression Ignition Combustion Under Boosted Ultra-EGR Dilute Conditions in a Negative Valve Overlap Engine (2019)

Abstract Spark-assisted compression ignition (SACI) is a low temperature combustion mode that can offer thermal efficiency improvements and lower nitrogen oxide emissions compared to conventional spark-ignited combustion. However, the SACI operating range is often limited due to excessive pressure rise rates driven by rapid heat release rates. Well-controlled experiments were performed to investigate the SACI operating limits under previously unexplored boosted, stoichiometric, EGR dilute conditions, where low temperature combustion engines promise high thermodynamic efficiencies. At higher intake boost, the SACI high load limit shifted towards lower fuel-to-charge equivalence ratio mixtures, creating a larger gap between the conventional spark-ignition EGR dilution limit and the boosted SACI operating limits. Combustion phasing retard was very effective at reducing maximum pressure rise rate levels until the stability limit, primarily due to slower end-gas burn rates. Gross fuel conversion efficiency improvements up to 10% were observed by using intake boost for either load expansion or dilution extension. Changes in engine speed necessitated changes in unburned gas temperature to match autoignition timing, but were shown to have negligible impact on the heat release profile on a crank angle basis. Lower engine speeds were favorable for load expansion, as time-based peak pressure rise rates scaled with engine speed.
Raman scattering studies on nanocrystalline BaTiO3 Part I—isolated particles and aggregates (2007)

Abstract BaTiO 3 powders with various crystallite sizes, which were prepared through microemulsion‐mediated synthesis, were thoroughly studied by Raman spectroscopy. Clear evidence for the presence of the tetragonal phase was found for ultrafine powders with an average crystallite size above 30 nm. The lifetime of phonons that are specifically assigned to the tetragonal phase decreased with decreasing crystallite size below a critical size of 100 nm. In particles as fine as 100 nm, the short mean free path of phonons, mainly due to internal pressure, causes decoupling of the coupled A 1 (TO) phonons and a diffuse phase transition behaviour ( T C = 115 °C). Coupled A 1 (TO) phonons, which give a spectral dip at around 180 cm −1 and a lesser extent of diffuseness, were revealed for powders consisting of particles as large as 0.17 µm ( T C = 123 °C). Further coarsening upon annealing induced the formation of aggregates, resulting in the shift of phase transition points to higher temperatures for the rhombohedral to orthorhombic and the orthorhombic to tetragonal transitions and to lower temperatures for the tetragonal to cubic transition, respectively. Phase stability in powders is discussed by considering possible factors such as internal pressure in isolated particles and internal stress in aggregates. Copyright © 2007 John Wiley &amp; Sons, Ltd.
Metabolic analysis of knee synovial fluid as a potential diagnostic approach for osteoarthritis (2015)

Osteoarthritis (OA) is a leading cause of chronic joint pain in the older human population. Diagnosis of OA at an earlier stage may enable the development of new treatments to one day effectively modify the progression and prognosis of the disease. In this work, we explore whether an integrated metabolomics approach could be utilized for the diagnosis of OA. Synovial fluid (SF) samples were collected from symptomatic chronic knee OA patients and normal human cadaveric knee joints. The samples were analyzed using (1)H nuclear magnetic resonance (NMR) spectroscopy and gas chromatography-mass spectrometry (GC-MS) followed by multivariate statistical analysis. Based on the metabolic profiles, we were able to distinguish OA patients from the controls and validate the statistical models. Moreover, we have integrated the (1)H NMR and GC-MS results and we found that 11 metabolites were statistically important for the separation between OA and normal SF. Additionally, statistical analysis showed an excellent predictive ability of the constructed metabolomics model (area under the receiver operating characteristic curve = 1.0). Our findings indicate that metabolomics might serve as a promising approach for the diagnosis and prognosis of degenerative changes in the knee joint and should be further validated in clinical settings.
Consequences of hyperphosphatemia and elevated levels of the calcium-phosphorus product in dialysis patients (2001)

Control of serum phosphorus levels is a central goal in the management of patients with chronic renal failure. Inadequate control of serum phosphorus leads to elevated levels of the calcium-phosphorus product. This plays a pivotal role in vascular calcification, cardiovascular disease, calciphylaxis, and death. Elevated phosphorus and elevated levels of the calcium-phosphorus product are both significant predictors of cardiovascular mortality, at phosphorus and calcium-phosphorus product levels that were considered safe until recently. A lowering of levels such that phosphorus is maintained between 2.2 and 5.5 mg/dl, calcium-phosphorus product is below 55 mg(2)/dl(2), and serum calcium is at 9.2-9.6 mg/dl, respectively, might well be the goal of therapeutic management strategies.
A Base Camp for Scaling AI (2016)

Modern statistical machine learning (SML) methods share a major limitation with the early approaches to AI: there is no scalable way to adapt them to new domains. Human learning solves this in part by leveraging a rich, shared, updateable world model. Such scalability requires modularity: updating part of the world model should not impact unrelated parts. We have argued that such modularity will require both "correctability" (so that errors can be corrected without introducing new errors) and "interpretability" (so that we can understand what components need correcting). To achieve this, one could attempt to adapt state of the art SML systems to be interpretable and correctable; or one could see how far the simplest possible interpretable, correctable learning methods can take us, and try to control the limitations of SML methods by applying them only where needed. Here we focus on the latter approach and we investigate two main ideas: "Teacher Assisted Learning", which leverages crowd sourcing to learn language; and "Factored Dialog Learning", which factors the process of application development into roles where the language competencies needed are isolated, enabling non-experts to quickly create new applications. We test these ideas in an "Automated Personal Assistant" (APA) setting, with two scenarios: that of detecting user intent from a user-APA dialog; and that of creating a class of event reminder applications, where a non-expert "teacher" can then create specific apps. For the intent detection task, we use a dataset of a thousand labeled utterances from user dialogs with Cortana, and we show that our approach matches state of the art SML methods, but in addition provides full transparency: the whole (editable) model can be summarized on one human-readable page. For the reminder app task, we ran small user studies to verify the efficacy of the approach.
Data from Selective Inhibition of HDAC3 Targets Synthetic Vulnerabilities and Activates Immune Surveillance in Lymphoma (2023)

&lt;div&gt;Abstract&lt;p&gt;&lt;i&gt;CREBBP&lt;/i&gt; mutations are highly recurrent in B-cell lymphomas and either inactivate its histone acetyltransferase (HAT) domain or truncate the protein. Herein, we show that these two classes of mutations yield different degrees of disruption of the epigenome, with HAT mutations being more severe and associated with inferior clinical outcome. Genes perturbed by &lt;i&gt;CREBBP&lt;/i&gt; mutation are direct targets of the BCL6–HDAC3 onco-repressor complex. Accordingly, we show that HDAC3-selective inhibitors reverse &lt;i&gt;CREBBP&lt;/i&gt;-mutant aberrant epigenetic programming, resulting in: (i) growth inhibition of lymphoma cells through induction of BCL6 target genes such as &lt;i&gt;CDKN1A&lt;/i&gt; and (ii) restoration of immune surveillance due to induction of BCL6-repressed IFN pathway and antigen-presenting genes. By reactivating these genes, exposure to HDAC3 inhibitors restored the ability of tumor-infiltrating lymphocytes to kill DLBCL cells in an MHC class I and II–dependent manner, and synergized with PD-L1 blockade in a syngeneic model &lt;i&gt;in vivo&lt;/i&gt;. Hence, HDAC3 inhibition represents a novel mechanism-based immune epigenetic therapy for &lt;i&gt;CREBBP&lt;/i&gt;-mutant lymphomas.&lt;/p&gt;Significance:&lt;p&gt;We have leveraged the molecular characterization of different types of &lt;i&gt;CREBBP&lt;/i&gt; mutations to define a rational approach for targeting these mutations through selective inhibition of HDAC3. This represents an attractive therapeutic avenue for targeting synthetic vulnerabilities in &lt;i&gt;CREBBP&lt;/i&gt;-mutant cells in tandem with promoting antitumor immunity.&lt;/p&gt;&lt;p&gt;&lt;i&gt;This article is highlighted in the In This Issue feature, p. 327&lt;/i&gt;&lt;/p&gt;&lt;/div&gt;
Ultrafast Diffraction Switching Using GaAs Metasurfaces (2020)

We design a resonant metasurface that uses Mie quadrupole modes to suppress the -1 diffraction order. We show that this suppression can be spectrally tuned using optical pumping on a picosecond timescale.
Amide-Amide and Amide-Water Hydrogen Bonds: Implications for Protein Folding and Stability (1994)

Amide-amide hydrogen bonds have been implicated in directing protein folding and enhancing protein stability. Inversion transfer (13)C NMR spectroscopy and IR spectroscopy were used to compare the ability of various amide solvents and of water to alter the rate of the cis-trans isomerization of the prolyl peptide bond of Ac-Gly-[β,δ-(13)C]Pro-OMe and the amide I vibrational mode of [(13)C=O]Ac-Pro-OMe. The results indicate that secondary amides are significantly weaker hydrogen bond donors than is formamide or water. These results are most consistent with models for protein folding in which the formation of secondary structure is a cooperative process that follows hydrophobic collapse. These results also suggest that a hydrogen bond between a main-chain oxygen and an asparagine or glutamine sidechain may contribute more to protein stability than does a main-chain-main-chain hydrogen bond.
Gene expression profiling of glioblastoma cell lines using cDNA microarrays: Association with response to chemotherapeutic drugs (2004)

599 Glioblastoma multiforme is the most common brain tumor in adult life. Only 25% of patients with glioblastoma respond to chemotherapy, and the reasons why some patients benefit from chemotherapy and some do not remain unclear. The molecular basis of glioma cell resistance are mutations or amplifications affecting the expression or functional activity of tumor suppressor genes and oncogenes. Genome-wide expression analysis is a promising tool for identifying the precise genetic causes and molecular mechanisms of chemoresistance. The aim of this study was to identify genes, gene clusters, and signalling pathways that determine the sensitivity of glioblastoma cells to chemotherapeutic drugs. Thus, we used a cDNA microarray representing 5,800 human genes to analyze expression profiles in a panel of 12 human malignant glioma cell lines (A172, D247MG, LN-18, LN-229, LN-308, LN-319, LN-428, T98G, U87MG, U138MG, U251MG, U373MG). Using a bioinformatics approach, the gene expression data of the glioma cell lines were then compared with their responsiveness to 25 anticancer drugs. Cluster and gene expression correlation analysis identified subsets of genes whose expression levels exhibited significant associations with the drug sensitivity profiles. This integrated database of expression profiles and pharmacological profiles might be helpful to predict glioma cell resistance by determining the expression levels of a limited number of genes. Moreover, this approach could potentially contribute to the identification of novel drug targets for combating brain tumors.
Table S2 from Aurora A Kinase Inhibition Is Synthetic Lethal with Loss of the <i>RB1</i> Tumor Suppressor Gene (2023)

&lt;p&gt;Abs IC50 values (µM) for LY3295668 across a panel of 580 cell lines.&lt;/p&gt;
Inorganic nanoparticle empowered biomaterial hybrids: Engineered payload release (2022)

There are many challenges in delivering active pharmaceutical ingredients from biomaterials, including retention of payload activity, accurate temporal release, and precise spatial administration, to name only a few. With our constantly increasing knowledge of biology and physiology, pathologies that require therapeutic interventions are becoming more understood. While the desired temporal and spatial administration of a therapy might be theorized, the ability to deliver an active therapeutic in a precise location during a specific time frame is often challenging. This has led researchers to develop hybrid biomaterials containing inorganic nanoparticles in order to combine the advantages of both inorganics and organics in payload delivery applications. Organic materials have many beneficial properties, including the ability to form networks and matrices to create three-dimensional structures from the nanometer to centimeter scale, biodegradability, the versatility to use both synthetic and natural precursors, and ease of chemical modifications, while inorganic materials offer highly controllable nanoscale features, can entrap and protect therapeutics, and have degradation properties that can be tightly regulated. Here in, we discuss the current state-of-the-art in active pharmaceutical ingredient delivery from biomaterial hybrids, demonstrate the added levels of control that these hybrid biomaterials offer, and give our perspective on future innovations in the field.
Inactivation of urokinase-type plasminogen activator receptor induces dermal and pulmonary fibrosis and peripheral microvasculopathy in mice closely mimicking human systemic sclerosis (2014)

Urokinase-type plasminogen activator receptor (uPAR, or CD87) is a key component of the fibrinolytic system involved in extracellular matrix remodeling and angiogenesis. The cleavage/inactivation of uPAR is a crucial step in fibroblast-to-myofibroblast transition and has been implicated in systemic sclerosis (SSc, scleroderma) peripheral microvasculopathy and impaired angiogenesis. In the present study, we investigated whether uPAR gene inactivation in mice could result in tissue fibrosis and peripheral microvasculopathy resembling human SSc. Skin and lung sections from uPAR-deficient mice and wild-type littermates at 12 and 24 weeks of age were stained with hematoxylin-eosin, Masson’s trichrome and Picrosirius red. Dermal thickness and hydroxyproline content were quantified. The number of myofibroblasts and microvessels were determined in skin sections immunostained for alpha-smooth muscle actin and the pan-endothelial cell marker CD31, respectively. Endothelial cell apoptosis was assessed by TUNEL/CD31 immunofluorescence assay. Dermal thickness, collagen content and myofibroblast counts were significantly greater in uPAR-deficient mice than in wild-type littermates. In uPAR-deficient mice, dermal fibrosis was paralleled by endothelial cell apoptosis and severe loss of microvessels. Lung specimens from uPAR-deficient mice exhibited non-specific interstitial pneumonia-like pathological features with large patchy areas of lung parenchyma displaying a uniform interstitial involvement characterized by both diffuse cellular inflammation and collagen deposition. In uPAR-deficient mice pulmonary pathology worsened significantly from 12 to 24 weeks of age, as shown by a significant increase in alveolar septal width and collagen content.The absence of uPAR induces dermal and pulmonary fibrosis and peripheral microvasculopathy in mice closely mimicking human SSc. uPAR-deficient mice might be a promising preclinical model to study the pathogenetic mechanisms of human SSc and enable testing of antifibrotic agents and drugs targeting small vessel vasculopathy simultaneously.
Semi-Supervised Learning of Multi-Object 3D Scene Representations (2021)

Representing scenes at the granularity of objects is a prerequisite for scene understanding and decision making. We propose a novel approach for learning multi-object 3D scene representations from images. A recurrent encoder regresses a latent representation of 3D shapes, poses and texture of each object from an input RGB image. The 3D shapes are represented continuously in function-space as signed distance functions (SDF) which we efficiently pre-train from example shapes. By differentiable rendering, we train our model to decompose scenes self-supervised from RGB-D images. Our approach learns to decompose images into the constituent objects of the scene and to infer their shape, pose and texture properties from a single view. In experiments, we evaluate the accuracy of our model in inferring the 3D scene layout and demonstrate the capabilities of the generative 3D scene model.
Influence of Barrier Design on Current Collapse in High Voltage AlGaN/GaN HEMTs. (2016)

Abstract not provided.
Nano-membrane based Plasmonic Devices for Surface-Enhanced Infrared Absorption Gas Sensing (2018)

Surface-enhanced infrared absorption for gas sensing is still not successful due to the intrinsically weak light-matter interaction. Herein, we demonstrate a plasmonic device integrated with metal-organic framework on Si 3 N 4 membrane substrate for CO 2 sensing.
Chip Scale Optical Microresonator Sensors Integrated With Embedded Thin Film Photodetectors on Electrowetting Digital Microfluidics Platforms (2011)

Miniaturized, portable, sensitive, and low cost sensing systems are important for medical and environmental diagnostic and monitoring applications. Chip scale integrated photonic sensing systems that combine optical, electrical, and fluidic functions are especially attractive for sensing applications due to the high sensitivity of optical sensors, the small form-factor of chip scale systems, and the low-cost processing possible for systems fabricated with well-developed mass production techniques. In this paper, a chip scale sensing system, which is composed of a planar integrated optical microdisk resonator and a thin film InGaAs photodetector, is integrated with a digital microfluidic system. This system was designed, fabricated, and experimentally characterized by dispensing and moving droplets of glucose solution from the reservoir to the microresonator sensor. The optical output of the resonator was transduced by the integrated photodetector to an electrical current signal for readout.
Scalable and Performance-Efficient Client Honeypot on High Interaction System (2012)

We investigated client honeypots for detecting and circumstantially analyzing drive-by download attacks. A client honeypot requires both improved inspection performance and in-depth analysis for inspecting and discovering malicious websites. However, OS overhead in recent client honeypot operation cannot be ignored for improving honeypot multiplication performance. We propose a client honeypot client system that uses our proposed multi-OS and multi-process honeypot multiplication approaches and implemented this system to evaluate its performance. Our process sandbox mechanism, a security measure for our multi-process approach, creates a virtually isolated environment for each web browser. In a field trial, we confirmed that the use of our multi-process approach was three or more times faster than that of a single process and [our multi-OS approach lineally improved system performance according to the number of honeypot instances. Thus, our proposed multiplication approaches improve performance efficiency and enables in-depth analysis on high interaction systems.
Reflectin’s Finely Tunable, Impedance-Matched, Amplifying Biophotonic System (2021)

An integrated system of reflectin proteins and surrounding membranes enables finely tunable photonic camouflage and communication in squids. The mechanism of this system’s tunability in Bragg reflectors and Mie scatterers is presented.
A New Approach to Styrenic Thermoplastic Elastomers:  Synthesis and Characterization of Crystalline Styrene−Butadiene−Styrene Triblock Copolymers (2005)

Crystalline styrene−butadiene−styrene (SBS) triblock copolymers consisting of elastic cis-polybutadiene (cis-PB) chemically bonded with crystallizable syndiotactic polystyrene (syn-PS) were synthesized through a stereospecific sequential triblock copolymerization of S with B catalyzed by C5Me5TiMe3/B(C6F5)3/trioctylaluminum (Al(oct)3) under controllable polymerization conditions. The first polymerization step was conducted at −25 °C, yielding syn-PS with controllable molecular weight by changing the polymerization time. The second one was started with the addition of excess B to the progressing syn-PS polymerization at −40 °C, yielding syn-PS/cis-PB diblock copolymer with high block efficiencies. The third one was conducted at −25 °C just by removal of the unreacted B in order to enhance the reinsertion and propagation of the remained S, yielding crystalline SBS triblock copolymers with relatively high PS compositions. The livingness of the whole polymerization process was confirmed through a linear increase of the molecular weights of the polymer products obtained in each step against their polymer yields, while keeping the polydispersity values almost constant. The 13C NMR analysis of the copolymer product proves that the PS blocks were highly syndiotactic ([rrrr] > 95%), and the PB block was primarily cis-1,4 structure (>70%). Cross-fractionation chromatography (CFC) was used to evaluate the contamination of the dead polymers in the crystalline SBS. Transmission electronic microscopy (TEM) was used to observe the phased separation morphology of the PS and PB blocks in the crystalline SBS. The existence of the syn-PS blocks in the crystalline SBS was further confirmed with the observation of a strong endothermic peak at 272 °C in their differential scanning calorimetry (DSC) curves. Preliminary results on the heat deformation stability as well as the chemical resistance property of this new material have also been evaluated in comparison with those of the corresponding anionic SBS materials.