gebhart/patrepeval huggingface dataset:
A new painkiller nanomedicine to bypass the blood-brain barrier and the use of morphine (2019)

The clinical use of endogenous neuropeptides has historically been limited due to pharmacokinetic issues, including plasma stability and blood-brain barrier permeability. In this study, we show that the rapidly metabolized Leu-enkephalin (LENK) neuropeptide may become pharmacologically efficient owing to a simple conjugation with the lipid squalene (SQ). The corresponding LENK-SQ bioconjugates were synthesized using different chemical linkers in order to modulate the LENK release after their formulation into nanoparticles. This new SQ-based nanoformulation prevented rapid plasma degradation of LENK and conferred on the released neuropeptide a notable antihyperalgesic effect that lasted longer than after treatment with morphine in a rat model of inflammation (Hargreaves test). The biodistribution study as well as the use of brain-permeant and -impermeant opioid receptor antagonists indicated that LENK-SQ NPs act through peripherally located opioid receptors. This study represents a novel nanomedicine approach, allowing the specific delivery of LENK neuropeptide into inflamed tissues for pain control.
Activity of small molecule inhibitors of the epidermal growth factor receptor (EGFR) kinase, on EGFR kinase domain mutants (2005)

5288 It was recently suggested that epidermal growth factor receptor (EGFR) mutations may predict sensitivity to small molecule tyrosine kinase inhibitors (TKIs), as several somatic mutations in the EGFR gene have been identified in certain patients with non-small-cell lung cancer (NSCLC). We characterized the activation state of four different EGFR receptors bearing mutations in the kinase domain (G719C, L858R, L861Q, del747-753) and studied their sensitivity to small molecule TKIs. We found two mutants (L858R, L861Q) to be ligand-independent, constitutively activate kinases. Activation of the G719 mutant was found to be ligand-dependent, and the deletion mutant (del747-753) exhibited reduced kinase activity (20-fold less as compare to wild type EGFR). In the present study we determined the inhibitory activity of gefitinib and IM092214 against three EGFR mutants (G719C, L858R, L861Q) and wild type EGFR using enzymatic and cell-based phosphorylation assays. IM092214 is a structurally novel benzoxazepine that potently inhibits the EGFR kinase activity (cell-based IC50 = 60 nM). We found that gefitinib and IM092214 inhibited wild-type and mutant EGFR activity to similar extent in both the enzymatic assay (gefitinib IC50 = 15 nM, IM092214 IC50 = 60 nM) and the cell-based phosphorylation assay (gefitinib IC50 = 20 nM, IM092214 IC50 = 50 nM). Importantly, we did not observe hypersensitivity of any of the tested mutants to gefitinib or IM092214. Our data suggest that there may be other mechanisms responsible for the observed favorable response of certain lung cancer patients with EGFR mutations to TKIs.
A distributed service, adaptive to trust assessment, based on peer-to-peer e-records replication and storage (2002)

The increasing pervasiveness of the Internet is changing the way enterprises are doing businesses. More and more B2B transactions and business interactions are happening on-line by exchanging digital information. Enterprises will continue to be accountable for their actions. Today paper-based evidence is retained for a long time and used to support claims. In the future digital documents will be used for this purpose. We believe there will be a proliferation of trust services to underpin e-businesses and specifically to address the management of long-term digital documents. These services are trusted, distributed, survivable and self-healing. We focus on the problem of long-term storage, integrity and survivability of digital documents (e-records) within an enterprise. We describe a service based on a distributed peer-to-peer architecture that uses cheap and abundant enterprise resources. We stress on the importance of the adaptiveness of this service to the trustworthiness of the distributed components.
Analyzing Uber's Ride-sharing Economy (2017)

Uber is a popular ride-sharing application that matches people who need a ride (or riders) with drivers who are willing to provide it using their personal vehicles. Despite its growing popularity, there exist few studies that examine large-scale Uber data, or in general the factors affecting user participation in the sharing economy. We address this gap through a study of the Uber market that analyzes large-scale data covering 59 million rides which spans a period of 7 months. The data were extracted from email receipts sent by Uber collected on Yahoo servers, allowing us to examine the role of demographics (e.g., age and gender) on participation in the ride-sharing economy. In addition, we evaluate the impact of dynamic pricing (i.e., surge pricing) and income on both rider and driver behavior. We find that the surge pricing does not bias Uber use towards higher income riders. Moreover, we show that more homophilous matches (e.g., riders to drivers of a similar age) can result in higher driver ratings. Finally, we focus on factors that affect retention and use information from earlier rides to accurately predict which riders or drivers will become active Uber users.
Mobility performance of LTE co-channel deployment of macro and pico cells (2012)

This paper aims at analyzing the mobility performance in heterogeneous 3GPP (3rd Generation Partnership Project) Long Term Evolution (LTE) networks. The main objective is to analyze the behavior of LTE macro/pico co-channel networks with different mobility parameters, such as the “Time-To-Trigger” (TTT). For this purpose, a system simulator has been utilized to assess the performance. The system must have different settings depending on the user velocity and on which cell-layer user is being serviced. Additionally, we have considered scenarios with a mixture of users moving freely or constrained to a hotspot, and different pico cell deployments.
Structural and Electrochemical Characteristics of Ca-Doped “Flower-like” Li4Ti5O12Motifs as High-Rate Anode Materials for Lithium-Ion Batteries (2018)

Doped motifs offer an intriguing structural pathway toward improving conductivity for battery applications. Specifically, Ca-doped, three-dimensional “flower-like” Li<sub>4–x</sub>Ca<sub>x</sub>Ti<sub>5</sub>O<sub>12</sub> (“x” = 0, 0.1, 0.15, and 0.2) micrometer-scale spheres have been successfully prepared for the first time using a simple and reproducible hydrothermal reaction followed by a short calcination process. The products were experimentally characterized by means of X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) mapping, inductively coupled plasma optical emission spectrometry (ICP-OES), X-ray photoelectron spectroscopy (XPS), cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and galvanostatic charge–discharge testing. Calcium dopant ions were shown to be uniformly distributed within the LTO structure without altering the underlying “flower-like” morphology. The largest lattice expansion and the highest Ti<sup>3+</sup> ratios were noted with XRD and XPS, respectively, whereas increased charge transfer conductivity and decreased Li<sup>+</sup>-ion diffusion coefficients were displayed in EIS for the Li<sub>4–x</sub>Ca<sub>x</sub>Ti<sub>5</sub>O<sub>12</sub> (“x” = 0.2) sample. The “x” = 0.2 sample yielded a higher rate capability, an excellent reversibility, and a superior cycling stability, delivering 151 and 143 mAh/g under discharge rates of 20C and 40C at cycles 60 and 70, respectively. In addition, a high cycling stability was demonstrated with a capacity retention of 92% after 300 cycles at a very high discharge rate of 20C. In addition, first-principles calculations based on density functional theory (DFT) were conducted with the goal of further elucidating and understanding the nature of the doping mechanism in this study. The DFT calculations not only determined the structure of the Ca-doped Li<sub>4</sub>Ti<sub>5</sub>O<sub>12</sub>, which was found to be in accordance with the experimentally measured XPD pattern, but also yielded valuable insights into the doping-induced effect on both the atomic and electronic structures of Li<sub>4</sub>Ti<sub>5</sub>O<sub>12</sub>.
Factor inhibiting HIF can catalyze two asparaginyl hydroxylations in VNVN motifs of ankyrin fold proteins (2022)

The aspariginyl hydroxylase human factor inhibiting hypoxia-inducible factor (FIH) is an important regulator of the transcriptional activity of hypoxia-inducible factor. FIH also catalyzes the hydroxylation of asparaginyl and other residues in ankyrin repeat domain-containing proteins, including apoptosis stimulating of p53 protein (ASPP) family members. ASPP2 is reported to undergo a single FIH-catalyzed hydroxylation at Asn-986. We report biochemical and crystallographic evidence showing that FIH catalyzes the unprecedented post-translational hydroxylation of both asparaginyl residues in "VNVN" and related motifs of ankyrin repeat domains in ASPPs (i.e., ASPP1, ASPP2, and iASPP) and the related ASB11 and p18-INK4C proteins. Our biochemical results extend the substrate scope of FIH catalysis and may have implications for its biological roles, including in the hypoxic response and ASPP family function.
Expression Profiles of a Human Pancreatic Cancer Cell Line upon Induction of Apoptosis Search for Modulators in Cancer Therapy (2004)

We analyzed the differential gene expression in the pancreatic cancer cell line NP-18 upon induction of apoptosis caused by cyclin-dependent kinase inhibition triggered by either overexpression of the tumor suppressor gene p16(INK4A)using an adenoviral construction or incubation with the chemical inhibitors, roscovitine or olomoucine. Screening was performed using cDNA arrays from Clontech that allowed the determination of the expression of 1,176 genes specifically related with cancer. The analysis was carried out using the Atlas Image 2.01 (Clontech) and GeneSpring 4.2 (Silicon Genetics) softwares. Among the differentially expressed genes, we chose for further validation histone deacetylase 1 (HDAC1), von Hippel Lindau and decorin as upregulated genes, and Sp1, hypoxia-inducible factor-1 alpha and DNA primase as downregulated genes. The changes in the expression of these genes to mRNA were validated by quantitative RT-PCR and the final translation into protein by Western blot analysis. Inhibition of HDAC activity, Sp1 binding and DNA primase expression led to an increase in the level of apoptosis, both in parental cells and in doxorubicin-resistant cells. Therefore, these proteins could constitute possible targets to develop modulators in cancer chemotherapy that would increase or restore apoptosis.
eSampling: Energy Harvesting ADCs (2020)

Analog-to-digital converters (ADCs) allow physical signals to be processed using digital hardware. The power consumed in conversion grows with the sampling rate and quantization resolution, imposing a major challenge in power-limited systems. A common ADC architecture is based on sample-and-hold (S/H) circuits, where the analog signal is being tracked only for a fraction of the sampling period. In this paper, we propose the concept of eSampling ADCs, which harvest energy from the analog signal during the time periods where the signal is not being tracked. This harvested energy can be used to supplement the ADC itself, paving the way to the possibility of zero-power consumption and power-saving ADCs. We analyze the tradeoff between the ability to recover the sampled signal and the energy harvested, and provide guidelines for setting the sampling rate in the light of accuracy and energy constraints. Our analysis indicates that eSampling ADCs operating with up to 12 bits per sample can acquire bandlimited analog signals such that they can be perfectly recovered without requiring power from the external source. Furthermore, our theoretical results reveal that eSampling ADCs can in fact save power by harvesting more energy than they consume. To verify the feasibility of eSampling ADCs, we present a circuit-level design using standard complementary metal oxide semiconductor (CMOS) 65 nm technology. An eSampling 8-bit ADC which samples at 40 MHZ is designed on a Cadence Virtuoso platform. Our experimental study involving Nyquist rate sampling of bandlimited signals demonstrates that such ADCs are indeed capable of harvesting more energy than that spent during analog-to-digital conversion, without affecting the accuracy.
AVO and Anisotropy from Logs and Walkaways (1993)

AVO (Amplitude Versus Offset) is the seismic technique used for mapping lithology, and modelling is an important step for successful AVO interpretations. Shear velocity measurements are essential, since AVO attempts to exploit the elastic (as opposed to acoustic) nature of seismic wave propagation. A property of seismic wave propagation not often considered is anisotropy. This is probable because the magnitude of the anisotropy has been difficult to measure, and its effect on AVO is not widely known.New technology is helping to improve AVO modelling. Dipole source shear logging tools can now measure very slow shear velocities, increasing the range of applicability of AVO, and new borehole seismic techniques can measure anisotropy. When integrated, these new measurements provide more detailed information about the elastic moduli that govern wave propagation, and bring the possiblity for greater reliability in AVO interpretation.The effect of anisotropy on AVO is found to be significant and may lead to misinterpretations of AVO anomalies.
Location and tracking applications for high data rate UWB systems (2011)

This paper discusses a maximum likelihood (ML) estimator for the localization of mobile nodes in communication networks. The derived estimator is optimized for ranging measurements exploiting the received signal strength (RSS). For this purpose, the bias and uncertainties of the RSS based ranging procedure are analyzed, considering a path loss model of an indoor ultra-wideband (UWB) network under line of sight (LOS) conditions. The nonlinearity of the path loss model is first taken into account before the statistics of the observed RSS are approximated by a Taylor sequence of first order. The so found metrics describe a weighted least squares (WLS) method. The metrics of the estimator are analytically derived in closed-form. The performance of the derived estimator is investigated in Monte-Carlo simulations and compared with a simple least squares (LS) method and another method exploiting RSS fingerprints.
ChemInform Abstract: New Class of Chiral Diphosphine Ligands for Highly Efficient Transition‐Metal‐Catalyzed Stereoselective Reactions: The Bis( diphenylphosphino) Five‐Membered Biheteroaryls. (1997)

Abstract ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
Examining the Use of Antidepressants for Adolescents with Depression/Anxiety Who Regularly Use Cannabis: A Narrative Review (2022)

Depression and anxiety disorders are two of the most common and growing mental health concerns in adolescents. Consequently, antidepressant medication (AD) use has increased widely during the last decades. Several classes of antidepressants are used mainly to treat depression, anxiety, and obsessive-compulsive disorders by targeting relevant brain neurochemical pathways. Almost all randomized clinical trials of antidepressants examined patients with no concomitant medications or drugs. This does not address the expected course of therapy and outcome in cannabis users. Cannabis is the most commonly used illicit substance globally. Substantial changes in its regulation are recently taking place. Many countries and US states are becoming more permissive towards its medical and recreational use. The psychological and physiological effects of cannabis (mainly of its major components, tetrahydrocannabinol (THC) and cannabidiol (CBD)) have been extensively characterized. Cannabis use can be a risk factor for depressive and anxiety symptoms, but some constituents or mixtures may have antidepressant and/or anxiolytic potential. The aim of this literature review is to explore whether simultaneous use of AD and cannabis in adolescence can affect AD treatment outcomes. Based on the current literature, it is reasonable to assume that antidepressants are less effective for adolescents with depression/anxiety who frequently use cannabis. The mechanisms of action of antidepressants and cannabis point to several similarities and conjunctions that merit future investigation regarding the potential effectiveness of antidepressants among adolescents who consume cannabis regularly.
DSOD: Learning Deeply Supervised Object Detectors from Scratch (2017)

We present Deeply Supervised Object Detector (DSOD), a framework that can learn object detectors from scratch. State-of-the-art object objectors rely heavily on the off the-shelf networks pre-trained on large-scale classification datasets like Image Net, which incurs learning bias due to the difference on both the loss functions and the category distributions between classification and detection tasks. Model fine-tuning for the detection task could alleviate this bias to some extent but not fundamentally. Besides, transferring pre-trained models from classification to detection between discrepant domains is even more difficult (e.g. RGB to depth images). A better solution to tackle these two critical problems is to train object detectors from scratch, which motivates our proposed DSOD. Previous efforts in this direction mostly failed due to much more complicated loss functions and limited training data in object detection. In DSOD, we contribute a set of design principles for training object detectors from scratch. One of the key findings is that deep supervision, enabled by dense layer-wise connections, plays a critical role in learning a good detector. Combining with several other principles, we develop DSOD following the single-shot detection (SSD) framework. Experiments on PASCAL VOC 2007, 2012 and MS COCO datasets demonstrate that DSOD can achieve better results than the state-of-the-art solutions with much more compact models. For instance, DSOD outperforms SSD on all three benchmarks with real-time detection speed, while requires only 1/2 parameters to SSD and 1/10 parameters to Faster RCNN.
Increased insulin action in rats with mild insulin deficiency induced by neonatal streptozotocin (1991)

The effect of chronic moderate insulin deficiency on in vivo insulin action was studied in young rats after neonatal (day of birth) streptozotocin (n0-STZ model) at a time (4 wk) when basal hyperglycemia is not yet established. The insulin action was quantified in vivo during insulin-glucose clamps performed on anesthetized rats while in the postabsorptive state; under basal or hyperinsulinemic conditions, total glucose production and utilization were assessed with a [3- 3H]-glucose perfusion, and local glucose utilization was estimated by measuring 2-deoxy-D-[1-3H]glucose 6-phosphate accumulation in various tissues. Compared with controls, the 4-wk-old n0-STZ rats were normoglycemic and hypoinsulinemic (P less than 0.05). The basal glucose production rate in the diabetics was significantly greater (P less than 0.05). During the clamp studies, suppression of endogenous glucose production by submaximal (1 nmol/l) or maximal (30 nmol/l) hyperinsulinemia was similar in both groups. Overall glucose utilization in the diabetics was significantly higher in the basal state and, after submaximal or maximal hyperinsulinemia, it remained significantly greater (P less than 0.001) than the corresponding utilization in the controls. This was correlated with an increased stimulation of glucose utilization in soleus muscle, diaphragm, white adipose tissue, and brown adipose tissue. In vitro studies using inguinal adipocytes showed that the glucose oxidative pathway retained normal sensitivity to insulin in the n0-STZ rats while the glucose conversion into lipids was significantly higher at sub-maximal insulin concentration compared with the control group.(ABSTRACT TRUNCATED AT 250 WORDS)
Synthesis of 1,4-Dihydropyridines by Regioselective Additions of Benzylic Zinc Bromides to Pyridinium Salts and Their Aromatizations to 4-Benzylpyridines (1997)

Abstract Benzylic zinc reagents add with high regioselectivity to 1-(phenoxycarbonyl) salts of methyl nicotinate to yield methyl-1-(phenoxylcarbonyl)-4-benzyl-1,4-dihydronicotinates. The dihydronicotinates on heating with sulfur in decalin afford methyl 4-benzylnicotinates.
Distributed architecture of Oracle database in-memory (2015)

Over the last few years, the information technology industry has witnessed revolutions in multiple dimensions. Increasing ubiquitous sources of data have posed two connected challenges to data management solutions -- processing unprecedented volumes of data, and providing ad-hoc real-time analysis in mainstream production data stores without compromising regular transactional workload performance. In parallel, computer hardware systems are scaling out elastically, scaling up in the number of processors and cores, and increasing main memory capacity extensively. The data processing challenges combined with the rapid advancement of hardware systems has necessitated the evolution of a new breed of main-memory databases optimized for mixed OLTAP environments and designed to scale. The Oracle RDBMS In-memory Option (DBIM) is an industry-first distributed dual format architecture that allows a database object to be stored in columnar format in main memory highly optimized to break performance barriers in analytic query workloads, simultaneously maintaining transactional consistency with the corresponding OLTP optimized row-major format persisted in storage and accessed through database buffer cache. In this paper, we present the distributed, highly-available, and fault-tolerant architecture of the Oracle DBIM that enables the RDBMS to transparently scale out in a database cluster, both in terms of memory capacity and query processing throughput. We believe that the architecture is unique among all mainstream in-memory databases. It allows complete application-transparent, extremely scalable and automated distribution of Oracle RDBMS objects in-memory across a cluster, as well as across multiple NUMA nodes within a single server. It seamlessly provides distribution awareness to the Oracle SQL execution framework through affinitized fault-tolerant parallel execution within and across servers without explicit optimizer plan changes or query rewrites.