gebhart/patrepeval huggingface dataset:
Cytoplasmic domain truncation enhances fusion activity by the exterior glycoprotein complex of human immunodeficiency virus type 2 in selected cell types (1992)

To investigate the glycoprotein determinants of viral cytopathology, we constructed chimeric env genes between a noncytopathic strain of human immunodeficiency virus type 2 (HIV-2), designated HIV-2/ST, and a highly fusogenic and cytopathic variant derived from this virus. Expression of the resulting chimeric glycoproteins indicated that efficient syncytium formation in the human T-cell line Sup T1 mapped to the C-terminal region of the transmembrane (TM) glycoprotein subunit. In this region, the wild-type and cytopathic ST glycoproteins differed by only four amino acids and by the presence of a premature termination codon in the cytopathic variant. Subsequent site-directed mutagenesis indicated that the cytoplasmic domain truncation was responsible for the enhanced fusion activity. This modification, however, increased the fusion activity of the glycoprotein only in Sup T1 cells (in which the ST variant arose) but not in Molt 4 clone 8 or peripheral blood mononuclear cells. These observations indicate that the length of the cytoplasmic domain of the HIV-2 glycoprotein modulates the fusion activity of the exterior glycoprotein complex in a cell-specific manner. Such adaptability appears to permit the emergence of fusogenic variants during HIV-2 passage in vitro and may also regulate viral growth or cytopathic effects in selected cell types during natural infection in vivo.
Band structure evolution during the ultrafast ferromagnetic-paramagnetic phase transition in cobalt (2017)

The evolution of the electronic band structure of the simple ferromagnets Fe, Co, and Ni during their well-known ferromagnetic-paramagnetic phase transition has been under debate for decades, with no clear and even contradicting experimental observations so far. Using time- and spin-resolved photoelectron spectroscopy, we can make a movie on how the electronic properties change in real time after excitation with an ultrashort laser pulse. This allows us to monitor large transient changes in the spin-resolved electronic band structure of cobalt for the first time. We show that the loss of magnetization is not only found around the Fermi level, where the states are affected by the laser excitation, but also reaches much deeper into the electronic bands. We find that the ferromagnetic-paramagnetic phase transition cannot be explained by a loss of the exchange splitting of the spin-polarized bands but instead shows rapid band mirroring after the excitation, which is a clear signature of extremely efficient ultrafast magnon generation. Our result helps to understand band structure formation in these seemingly simple ferromagnetic systems and gives first clear evidence of the transient processes relevant to femtosecond demagnetization.
Nonparametric bayesian models for neural data (2007)

Many neural data analyses can be cast as latent variable modeling problems. Specific examples include spike sorting and neurological data analysis. Challenges in spike sorting include figuring out how many neurons generated a set of recorded action potentials and, further, which neuron generated each action potential. A challenge in analyzing neurological data is to infer both the number and the characteristics of lesions that may be causal with respect to clinical signs presented by stroke patients. A shared characteristic of both of these problems is that the true underlying generative process is unobservable and potentially quite complex, so care must be taken in not only choosing a family of models but also in selecting a model of appropriate complexity. In such cases it may be preferable to employ a model that allows model complexity to be inferred from the data. 
Non-parametric Bayesian (NPB) modeling is a type of latent variable modeling in which model complexity can be estimated from data without making restrictive a priori assumptions. Our thesis is that using NPB modeling results in theoretical and practical improvements to neural data analysis. 
In defense of this thesis we develop a NPB spike sorting approach and show how it allows experimentalists to utilize more data, to make assumptions explicit, and to express spike sorting uncertainty at the level of inference from a novel spike train model. We discuss the theoretical advantages of this approach and demonstrate novel and improved neural data analyses including neural decoding. We also develop a new NPB binary matrix factorization model and accompanying posterior estimation algorithms. We illustrate this NPB binary matrix factorization model by inferring a causal model for signs exhibited by stroke patients. Finally, a sequential posterior estimation algorithm for this model is developed and demonstrated.
An intelligent hybrid communication system for a distributed renewable energy management (2013)

The ever increasing demand for energy has led towards distributed renewable energy generation systems. Such systems depend on a well integrated information and communication infrastructure for interconnection and integration of various energy sources, loads, and environmental sensors to achieve intelligent distributed control and management. This paper describes the design and implementation of an intelligent hybrid communication system for a micro distributed energy generation application. The industrial standard controller area network (CAN) bus was selected to connect various energy sources and loads, due to its resistance to noisy conditions. An application specific communication protocol was designed, based on the CAN protocol, to allow data exchange and control. The proposed communication system was verified using a prototype micro wind generation system with multiple power converters and a central energy management unit. Combined with intelligent control algorithms, which could in future be incorporated in the energy management unit, the system has the ability to perform optimised load balancing and energy usage planning.
Effect of ricinoleic acid in acute and subchronic experimental models of inflammation (2000)

Observational studies indicate that topical application of ricinoleic acid (RA), the main component of castor oil, exerts remarkable analgesic and anti-inflammatory effects. Pharmacological characterization has shown similarities between the effects of RA and those of capsaicin, suggesting a potential interaction of this drug on sensory neuropeptide-mediated neurogenic inflammation. The aim of this study was to assess RA anti-inflammatory activities in comparison with capsaicin in several models of acute and subchronic inflammation. The acute inflammation was induced by intradermal injection of carrageenan in the mouse or by histamine in the guinea-pig eyelid. In either experiment, the extent of the oedema thickness was measured. Subchronic oedema was induced by complete Freund's adjuvant injection in the ventral right paw of mice. Tissue substance P (SP) was measured in the carrageenan experiments by radioimmunoassay (RIA). It was found that the acute topical application of RA (0.9 mg/mouse) or capsaicin (0.09 mg/mouse) significantly increased the mouse paw oedema induced by carrageenan, while an 8-day repeated topical treatment with the same doses of both compounds resulted in a marked inhibition of carrageenan-induced paw oedema matched by a reduction in SP tissue levels. Similar effects were found against histamine-induced eyelid oedema in guinea-pigs after acute or repeated application of RA or capsaicin. RA and capsaicin given for 1-3 weeks reduced the established oedema induced by Freund's adjuvant, a subchronic model of inflammation, particularly if given by the intradermal route. Either in mouse paw or in guinea-pig eyelid, capsaicin but not RA by itself produced a slight hyperemia and activation of a behavioural response (e.g. scratching of the eyelids). On the basis of the present results, RA may be seen as a new capsaicin-like, non-pungent anti-inflammatory agent suitable for peripheral application.
Nonlinear derating method for high intensity focused ultrasound (HIFU) fields (2009)

In this work, a new derating method to extrapolate nonlinear ultrasound fields in water to biological tissue is proposed and tested for therapeutic medical systems. Focal values of acoustic field parameters in absorptive tissue are obtained from a numerical solution to a KZK-type equation and are compared to those derated, using the proposed method, from the results of simulations in water. It is validated in modeling that for high gain sources, which are typically used for therapeutic medical applications, the focal field parameters in tissue can be obtained from the results obtained in water. The feasibility of the derating method is also demonstrated experimentally in water and excised bovine liver tissue using a 2 MHz HIFU source of 44 mm aperture and focal length.
Analysis of expressed sequence tags generated from full-length enriched cDNA libraries of melon (2011)

The collection of melon ESTs generated from full-length enriched and standard cDNA libraries is expected to play significant roles in annotating the melon genome. The ESTs and associated analysis results will be useful resources for gene discovery, functional analysis, marker-assisted breeding of melon and closely related species, comparative genomic studies and for gaining insights into gene expression patterns.
Frequency of Major Hemorrhage in Patients Treated With Unfractionated Intravenous Heparin for Deep Venous Thrombosis or Pulmonary Embolism (2000)

Administration of continuous intravenous UFH in patients with DVT or PE in routine clinical practice leads to a major bleeding rate of 4.0%. This rate is comparable to the rate of major bleeding in patients who received UFH in clinical trials. Our findings are relevant to the discussion of major bleeding rates in patients with DVT and PE treated in daily clinical practice with subcutaneous low-molecular-weight heparin and newer antithrombotic drugs.
Metallophthalocyanine Based Carbon Paste Electrodes for the Determination of 2′,3′‐Dideoxyinosine (2009)

Abstract Novel electrochemical sensors based on carbon paste impregnated with metallopthalocyanine (MPc, M=Co, Fe) complexes, have been constructed for the assay of anti‐HIV drug 2′,3′‐dideoxyinosine (didanosine, DDI). Both modified electrodes showed electrocatalytic activity towards the oxidation of dideoxyinosine in phosphate buffer pH 7.4 with a working concentration range of 10 −6 –10 −4 mol/L and a detection limit of 10 −7 mol/L magnitude order. The sensor proved to be highly reliable for the assay of the purity of DDI ‐ raw material as well as for the uniformity content test of Videx tablets.
Abnormalities in cartilage and bone development in the Apert syndrome FGFR2+/S252W mouse (2005)

Apert syndrome is an autosomal dominant disorder characterized by malformations of the skull, limbs and viscera. Two-thirds of affected individuals have a S252W mutation in fibroblast growth factor receptor 2 (FGFR2). To study the pathogenesis of this condition, we generated a knock-in mouse model with this mutation. The Fgfr2(+/S252W) mutant mice have abnormalities of the skeleton, as well as of other organs including the brain, thymus, lungs, heart and intestines. In the mutant neurocranium, we found a midline sutural defect and craniosynostosis with abnormal osteoblastic proliferation and differentiation. We noted ectopic cartilage at the midline sagittal suture, and cartilage abnormalities in the basicranium, nasal turbinates and trachea. In addition, from the mutant long bones, in vitro cell cultures grown in osteogenic medium revealed chondrocytes, which were absent in the controls. Our results suggest that altered cartilage and bone development play a significant role in the pathogenesis of the Apert syndrome phenotype.
A systematic comparison of error correction enzymes by next-generation sequencing (2017)

Gene synthesis, the process of assembling gene-length fragments from shorter groups of oligonucleotides (oligos), is becoming an increasingly important tool in molecular and synthetic biology. The length, quality and cost of gene synthesis are limited by errors produced during oligo synthesis and subsequent assembly. Enzymatic error correction methods are cost-effective means to ameliorate errors in gene synthesis. Previous analyses of these methods relied on cloning and Sanger sequencing to evaluate their efficiencies, limiting quantitative assessment. Here, we develop a method to quantify errors in synthetic DNA by next-generation sequencing. We analyzed errors in model gene assemblies and systematically compared six different error correction enzymes across 11 conditions. We find that ErrASE and T7 Endonuclease I are the most effective at decreasing average error rates (up to 5.8-fold relative to the input), whereas MutS is the best for increasing the number of perfect assemblies (up to 25.2-fold). We are able to quantify differential specificities such as ErrASE preferentially corrects C/G transversions whereas T7 Endonuclease I preferentially corrects A/T transversions. More generally, this experimental and computational pipeline is a fast, scalable and extensible way to analyze errors in gene assemblies, to profile error correction methods, and to benchmark DNA synthesis methods.
폐경전 및 갱년기 과체중 한국 성인 여성의 변증 지표 차이에 대한 연구 (2008)

Objectives
The aim of the study was to investigate the difference between pattern identification of premenopausal(n=39) and climacteric(n=40) korean...
Two New Amino Acid-Sesquiterpene Lactone Conjugates from Ixeris dentata (2012)

College of Pharmacy, Chungnam National University, Daejeon 305-764, KoreaReceived October 24, 2011, Accepted November 19, 2011Key Words : Amino acid-sesquiterpene lactone conjugates, Ixeris dentata, Asteraceae Ixeris dentata (Asteraceae) is a perennial herb which isused frequently as a Traditional Chinese Medicine for thetreatment of gastroenteric troubles, diabetes, pneumonia,hepatitis and tumor.
446 Accurate Localization of Back Pain by Radiomic Assessment of Sigma-1 Receptor Expression (2023)

INTRODUCTION: The current diagnostic tools that we have for back pain have low sensitivity and poor accuracy which leads to ineffective and unnecessary treatments, resulting in high health care costs and unwanted outcomes. Sigma-1 receptor (s1R) is broadly implicated in nociceptive signaling and peripheral pain sensation. METHODS: Specific patient selection for full body ([18F]FTC-146) PET/MRI scan was done after clinical and radiological review by a neurosurgeon specializing in spinal surgery. Six patients with various etiologies of back pain were included. For all the study participants, we recorded all relevant clinical details and reviewed prior diagnostic tests. All PET/MRI scans were completed at our institution’s facilities and images were reviewed and correlated by a musculoskeletal radiologist to identify lesions that may be causing patient’s symptoms. RESULTS: Our study results strongly support the likelihood of achieving enhanced diagnostic sensitivity to sources of back pain with the proposed s1r imaging approach. PET/MRI imaging matched the clinical diagnosis in all cases, including disc herniation, nerve compression, stenosis, and arthropathy. Additionally, it offered benefit over traditional MRI by identifying additional “functional” findings both within and outside the spine. This additional functional detail, was useful for patients with either no or multiple structural abnormalities on MRI to pinpoint the true cause of pain demonstrating the synergistic utility of this imaging modality. Such functional detail guided successful interventions including surgery, therapy, and injections in our patient cohort that successfully addressed the pain. CONCLUSIONS: Early results show promise for improved confidence and sensitivity in detecting sources of pain using full body ([18F]FTC-146) PET/MRI scan which can potentially improve patient management and outcomes.
Threshold level laser photoablation of oxidized aluminum(111): photoejected ion translational energy distributions (1991)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTThreshold level laser photoablation of oxidized aluminum(111): photoejected ion translational energy distributionsHyun Sook Kim and Henry HelvajianCite this: J. Phys. Chem. 1991, 95, 17, 6623–6627Publication Date (Print):August 1, 1991Publication History Published online1 May 2002Published inissue 1 August 1991https://pubs.acs.org/doi/10.1021/j100170a045https://doi.org/10.1021/j100170a045research-articleACS PublicationsRequest reuse permissionsArticle Views97Altmetric-Citations17LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access options Get e-Alerts
Selective thermal emission from patterned steel (2010)

Patterned metal films have been shown to possess unique optical properties resulting from the excitation of surface plasmon polaritons at the patterned metal surface. Here we demonstrate spectrally selective thermal emission from patterned steel substrates. The materials and processes used in this work were chosen for their potential scalability to large-area and low cost production of metal films with distinct and designable thermal signatures. The samples studied were characterized by reflection and emission spectroscopy, and a factor of 2.6 emission enhancement is demonstrated for the design wavelength. These results are compared to numerical simulations.
Multi-Atom PGM Based Catalyst for Highly Efficient Oxygen Reduction Reaction(ORR) and Hydrogen Oxidation Reaction (HOR) in Alkaline Environment (2022)

Anion exchange membrane fuel cells (AEMFCs) have recently seen significant growth in interest as their achievable current density, peak power density, and longevity have been improved dramatically. Though these advances in performance have been important for demonstrating the feasibility of the technology, nearly all AEMFCs reported in the literature have required a relatively high loading of platinum group metal (PGM)-based catalysts at both the anode and cathode electrodes [1]. However, to take command of the low-temperature fuel cell market, AEMFCs cannot simply reach the same performance as incumbent proton exchange membrane fuel cells (PEMFCs), which have had decades of development and investment. AEMFCs must realize their most widely quoted advantage over PEMFCs and be produced at a much lower cost than PEMFCs. The most likely pathway to acceptably low cost will involve reducing the PGM loading in both electrodes. At the cathode, reasonable PGM-free catalysts exist, as will be shown in this work. At the anode; however, there are no practical contenders that exist to replace PGM-based catalysts. Hence, the most practical approach is to create transitional catalysts with ultra-low PGM content until future PGM-free catalysts can be realized. To reduce the platinum group metal (PGM) loading in anion exchange membrane fuel cell (AEMFC) electrodes, it is important to transition to catalysts with very low PGM content, and eventually to create catalysts that are completely PGM-free. One approach that can be used in both cases is to create atomically dispersed metals on a carbon support. In this work, four catalysts were prepared using a new, simple, scalable Controlled Surface Tension (CST) method: Pt/C, Pt/NC, PtRu/C, and PtRu/NC. CST is unique as it allows for a high density of very small multi-atom clusters, facilitated by altering the surface tension in the synthesis medium. The catalysts were physically characterized using a wide array of techniques, including high-resolution Cs aberration-corrected scanning transmission electron microscopy (STEM), extended X-ray absorption fine structure (EXAFS), and X-ray Absorption Near-Edge Structure (XANES). The catalysts were also tested for their oxygen reduction reaction and hydrogen oxidation reaction activity both ex-situ on a rotating ring-disk electrode and in-situ while integrated into the anode (PtRu) and cathode (Pt) of operating AEMFCs. With this new generation of low-PGM materials, it was possible to reduce the PGM loading by a factor of 14 while achieving comparable performance to commercial catalysts with a peak power density approaching 2 W/cm 2 . AEMFCs were also assembled with ultralow PGM loading (0.05 mgPGM/cm 2 ), where PtRu/NC anodes were paired with Fe–N–C cathodes [2], which allowed for the demonstration of cells with a specific power of 25 W/mg PGM (40 W/mg Pt ).
An Online Sequence-to-Sequence Model Using Partial Conditioning (2015)

Sequence-to-sequence models have achieved impressive results on various tasks. However, they are unsuitable for tasks that require incremental predictions to be made as more data arrives. This is because they generate an output sequence conditioned on an entire input sequence. In this paper, we present a new model that can make incremental predictions as more input arrives, without redoing the entire computation. Unlike sequence-to-sequence models, our method computes the next-step distribution conditioned on the partial input sequence observed and the partial sequence generated. It accomplishes this goal using an encoder recurrent neural network (RNN) that computes features at the same frame rate as the input, and a transducer RNN that operates over blocks of input steps. The transducer RNN extends the sequence produced so far using a local sequence-to-sequence model. During training, our method uses alignment information to generate supervised targets for each block. Approximate alignment is easily available for tasks such as speech recognition, action recognition in videos, etc. During inference (decoding), beam search is used to find the most likely output sequence for an input sequence. This decoding is performed online - at the end of each block, the best candidates from the previous block are extended through the local sequence-to-sequence model. On TIMIT, our online method achieves 19.8% phone error rate (PER). For comparison with published sequence-to-sequence methods, we used a bidirectional encoder and achieved 18.7% PER compared to 17.6% from the best reported sequence-to-sequence model. Importantly, unlike sequence-to-sequence our model is minimally impacted by the length of the input. On artificially created longer utterances, it achieves 20.9% with a unidirectional model, compared to 20% from the best bidirectional sequence-to-sequence models.