Miracle-dz/UniFAR-FTUs huggingface dataset:
Expression of organic anion-transporting polypeptides 1B3, 1B1, and 1A2 in human pancreatic cancer reveals a new class of potential therapeutic targets

Background: Organic anion-transporting polypeptides (OATPs) are influx transporters that mediate intracellular uptake of selective endogenous and xenobiotic compounds. Identification of new molecular targets and discovery of novel targeted therapies is top priority for pancreatic cancer, which lacks any effective therapy. Materials and methods: We studied expression of OATP 1A2, 1B1, and 1B3 in pancreatic cancer tissue and in cell lines. Formalin-fixed paraffin-embedded biopsy material of 12 human pancreatic cancers was immunohistochemically assessed for protein expression of the three studied influx transporters. Immunohistochemistry was evaluated by experienced pathologists and quantified by use of an automated image analysis system. BxPC-3 and MIA PaCa-2 pancreatic cancer cell lines were used to quantify transcripts of OATP 1B1 and 1B3. Results: OATP 1A2, 1B1, and 1B3 proteins were found ubiquitously expressed in all studied cases. Quantification performed by HistoQuest system revealed that mean intensity was 53 for 1A2, 45 for 1B1, and 167 for OATP 1B1/1B3 on a range scale 0–250 units. At mRNA level, 1B1 and 1B3 were overexpressed in both studied cancer cell lines but not in normal pancreatic tissue. Conclusion: OATPs 1A2, 1B1, and 1B3 are highly expressed in pancreatic adenocarcinoma. We suggest that expression of these transporters in pancreatic cancer justify research efforts towards discovery of novel therapeutics targeting OATPs.
Development and validation of a Luminex assay for detection of a predictive biomarker for PROSTVAC-VF therapy

Cancer therapies can provide substantially improved survival in some patients while other seemingly similar patients receive little or no benefit. Strategies to identify patients likely to respond well to a given therapy could significantly improve health care outcomes by maximizing clinical benefits while reducing toxicities and adverse effects. Using a glycan microarray assay, we recently reported that pretreatment serum levels of IgM specific to blood group A trisaccharide (BG-Atri) correlate positively with overall survival of cancer patients on PROSTVAC-VF therapy. The results suggested anti-BG-Atri IgM measured prior to treatment could serve as a biomarker for identifying patients likely to benefit from PROSTVAC-VF. For continued development and clinical application of serum IgM specific to BG-Atri as a predictive biomarker, a clinical assay was needed. In this study, we developed and validated a Luminex-based clinical assay for measuring serum IgM specific to BG-Atri. IgM levels were measured with the Luminex assay and compared to levels measured using the microarray for 126 healthy individuals and 77 prostate cancer patients. This assay provided reproducible and consistent results with low %CVs, and tolerance ranges were established for the assay. IgM levels measured using the Luminex assay were found to be highly correlated to the microarray results with R values of 0.93–0.95. This assay is a Laboratory Developed Test (LDT) and is suitable for evaluating thousands of serum samples in CLIA certified laboratories that have validated the assay. In addition, the study demonstrates that discoveries made using neoglycoprotein-based microarrays can be readily migrated to a clinical assay.
A mutation in sigma‐1 receptor causes juvenile amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterized by loss of motor neurons in the brain and spinal cord, leading to muscle weakness and eventually death from respiratory failure. ALS is familial in about 10% of cases, with SOD1 mutations accounting for 20% of familial cases. Here we describe a consanguineous family segregating juvenile ALS in an autosomal recessive pattern and describe the genetic variant responsible for the disorder.
Online Empirical Evaluation of Tracking Algorithms

Evaluation of tracking algorithms in the absence of ground truth is a challenging problem. There exist a variety of approaches for this problem, ranging from formal model validation techniques to heuristics that look for mismatches between track properties and the observed data. However, few of these methods scale up to the task of visual tracking, where the models are usually nonlinear and complex and typically lie in a high-dimensional space. Further, scenarios that cause track failures and/or poor tracking performance are also quite diverse for the visual tracking problem. In this paper, we propose an online performance evaluation strategy for tracking systems based on particle filters using a time-reversed Markov chain. The key intuition of our proposed methodology relies on the time-reversible nature of physical motion exhibited by most objects, which in turn should be possessed by a good tracker. In the presence of tracking failures due to occlusion, low SNR, or modeling errors, this reversible nature of the tracker is violated. We use this property for detection of track failures. To evaluate the performance of the tracker at time instant t, we use the posterior of the tracking algorithm to initialize a time-reversed Markov chain. We compute the posterior density of track parameters at the starting time t = 0 by filtering back in time to the initial time instant. The distance between the posterior density of the time-reversed chain (at t = 0) and the prior density used to initialize the tracking algorithm forms the decision statistic for evaluation. It is observed that when the data are generated by the underlying models, the decision statistic takes a low value. We provide a thorough experimental analysis of the evaluation methodology. Specifically, we demonstrate the effectiveness of our approach for tackling common challenges such as occlusion, pose, and illumination changes and provide the Receiver Operating Characteristic (ROC) curves. Finally, we also show the applicability of the core ideas of the paper to other tracking algorithms such as the Kanade-Lucas-Tomasi (KLT) feature tracker and the mean-shift tracker.
Experimental Introduction to Surface Roughness Parameters Measurement

Surface roughness influences the performance of a finished part. In machining operations, the surface roughness generated is influenced by an enormous set of factors. In ball end milling operations, the geometric characteristics of the cut clearly affect the surface crests generated. This paper presents an experimental methodology that permits engineering students to identify and analyze the surface roughness. The methodology is applicable to training courses and surface texture generation as well.
Passive Q-switching and Q-switched mode-locking operations of 2 μm Tm:CLNGG laser with MoS 2 saturable absorber mirror

With MoS2 as saturable absorber, passive Q-switching and Q-switched mode-locking operations of a Tm-doped calcium lithium niobium gallium garnet (Tm:CLNGG) laser were experimentally demonstrated. The Q-switched laser emitted a maximum average output power of 62 mW and highest pulse energy of 0.72 μJ. Q-switched mode locking was also obtained in the experiment. The research results will open up applications of MoS2 at the mid-infrared wavelength.
Neutron Strain Scanning of Archaeological Bronzes

We report neutron strain scanning experiments on archaeological bronzes, with the aim of identifying the original manufacturing techniques used. The specimens studied were a Picenan necklace from VI BC, and an Etruscan bucket handle from IV BC, exhibited at the Marches Museum of Archaeology, Ancona, Italy. Time-of-flight neutron diffraction and transmission experiments were performed at the ENGIN-X instrument, ISIS, UK. For the necklace, characteristic bending strain profiles and a small degree of preferred orientation indicate that the specimen had been cold worked. For the handle, broad diffraction peaks and highly distorted Bragg edges -typical of a columnar grain microstructure- suggested that this specimen was cast and did not undergo significant thermal or mechanical treatment. The relation between the experimental diffracted and transmitted time-of-flight spectra, and the microstructure of specimens are discussed.
Adenosine‐induced presynaptic inhibition of IPSCs and EPSCs in rat hypothalamic supraoptic nucleus neurones

1 The effects of adenosine on synaptic transmission in magnocellular neurosecretory cells were investigated using whole‐cell patch‐clamp recordings in acute rat hypothalamic slices that included the supraoptic nucleus. 2 Adenosine reversibly reduced the amplitude of evoked inhibitory (IPSCs) and excitatory (EPSCs) postsynaptic currents in a dose‐dependent manner (IC50≈ 10 μm for both types of current). 3 Depression of IPSCs and EPSCs by adenosine was reversed by the application of the A1 adenosine receptor antagonist 8‐cyclopentyl‐1,3‐dimethylxanthine (CPT; 10 μm). 4 When pairs of stimuli were given at short intervals, adenosine inhibitory action was always less effective on the second of the two responses than on the first, resulting in an increased paired‐pulse facilitation and suggesting a presynaptic site of action. This observation was confirmed by analysis of spontaneous miniature synaptic currents whose frequency, but not amplitude or kinetics, was reversibly reduced by 100 μM adenosine. 5 CPT had no effect on synaptic responses evoked at a low frequency of stimulation (0.05–0.5 Hz), indicating the absence of tonic activation of A1 receptors under these recording conditions. However, CPT inhibited a time‐dependent depression of both IPSCs and EPSCs induced during a 1 Hz train of stimuli. 6 Taken together, these results suggest that adenosine can be released within the supraoptic nucleus at a concentration sufficient to inhibit the release of GABA and glutamate via the activation of presynaptic A1 receptors. By its inhibitory feedback action on the major afferent inputs to oxytocin and vasopressin neurones, adenosine could optimally adjust electrical and secretory activities of hypothalamic magnocellular neurones.
An Extended Model for TCP Loss Recovery Latency with Random Packet Losses

It has been a very important issue to evaluate the performance of transmission control protocol (TCP), and the importance is still growing up because TCP will be deployed more widely in future wireless as well as wireline networks. It is also the reason why there have been a lot of efforts to analyze TCP performance more accurately. Most of these works are focusing on overall TCP end-to-end throughput that is defined as the number of bytes transmitted for a given time period. Even though each TCP's fast recovery strategy should be considered in computation of the exact time period, it has not been considered sufficiently in the existing models. That is, for more detailed performance analysis of a TCP implementation, the fast recovery latency during which lost packets are retransmitted should be considered with its relevant strategy. In this paper, we extend the existing models in order to capture TCP's loss recovery behaviors in detail. On the basis of the model, the loss recovery latency of three TCP implementations can be derived with considering the number of retransmitted packets. In particular, the proposed model differentiates the loss recovery performance of TCP using selective acknowledgement (SACK) option from TCP NewReno. We also verify that the proposed model reflects the precise latency of each TCP's loss recovery by simulations.
Hyperspectral Confocal Fluorescence Microscope: A New Look into the Cell

Confocal microscopy is widely used in cell biology. Like other filter-based systems, traditional confocal microscopes are limited by the spectral bands established by each optical filter. As a result, emission spectra from labels and/or autofluorescence can be overlapped leading to spectral crosstalk and inability to quantify the amount of signal originating from each individual fluorescent species. The need for accurate quantification of in vivo cellular processes and in-depth knowledge of organelle development and microstructure led Monsanto to search for non-commercial microscopes that could achieve those goals. Through a cooperative research and development agreement (CRADA) established between Monsanto and Sandia Corporation in August 2006, we built a new 3D-hyperspectral confocal fluorescence imaging system, specifically designed to meet the analytical requirements of plant specimens.
Ontology Analysis Based on Ontology Design Patterns

The so-called Ontology Design Patterns (ODPs), which have been defined as solutions to ontological design problems, are of great help to developers when modelling ontologies since these patterns provide a development guide and improve the quality of the resulting ontologies. However, it has been demonstrated that, in many cases, developers encounter difficulties when they have to reuse ontology design patterns and include errors in the modelling. Thus, to avoid errors in ontology modelling, this paper proposes classifying errors into two types: (1) errors related to existing ODPs, called anti-patterns, and (2) errors not related to existing ODPs, called worst practices. This classification is the result of analysing a set of ontologies which come from an academic experiment. In addition, the paper presents a general classification of the worst practices found and a set of worst practice examples. Finally, the paper shows an example of how the aforementioned worst practices could be related among them.
Transient thermal stresses of orthotropic functionally graded thick strip due to nonuniform heat supply

This paper is concerned with the theoretical treatment of transient thermal stresses involving an orthotropic functionally graded thick strip due to nonuniform heat supply in the width direction. The thermal and thermoelastic constants of the strip are assumed to possess orthotropy and vary exponentially in the thickness direction. The transient two-dimensional temperature is analyzed by the methods of Laplace and finite sine transformations. We obtain the exact solution for the simply supported strip under the state of plane strain. Some numerical results for the temperature change, the displacement and the stress distributions are shown in figures. Furthermore, the influence of the orthotropy and nonhomogeneity of the material is investigated.
A single-inductor multiple-output boost converter with freewheel charge-pump control

This paper presents a freewheel-charge-pump-controlled design for a single-inductor multiple-output (SIMO) DC-DC Converter. By applying the freewheel-charge-pump-controlled (FCPC) technique, the freewheel switching time is reused, and two extra charge-pump outputs are provided by time recycling, with no cost in time sequences. The converter has two step-up outputs and two charge-pump outputs that can be higher or lower than the input supply. The proposed converter shows low cross-regulation and achieves a maximum loading current of 70 mA. Fabricated in a 0.18-μm CMOS process, the proposed circuit occupies only 1.3×1.3 mm2. Experimental results demonstrate that the converter successfully generates four wellregulated outputs with a single inductor. The supply voltage ranged from 1.6 V to 2.5 V and the load regulation performance was 0.08 mV/mA, 0.05mV/mA, 1.7 mV/mA, and 1.9 mV/mA for VO1, VO2, VO3 and VO4, respectively.
CAPTCHA Using Strangeness in Machine Translation

CAPTCHA is a technique that is used to prevent automatic programs from being able to acquire free e-mail or online service accounts. However, as many researchers have already reported, conventional CAPTCHA could be overcome by state-of-the-art malware since the capabilities of computers are approaching those of humans. Therefore, CAPTCHA should be based on even more advanced human-cognitive-processing abilities. We propose using the human ability of recognizing “strangeness” to achieve a new CAPTCHA. This paper focuses on strangeness in machine-translated sentences as an example, and proposes CAPTCHA using Strangeness in Sentences (SS-CAPTCHA), which detects malware by checking if users can distinguish natural sentences created by humans from machine-translated sentences. We discuss possible threats to SS-CAPTCHA and countermeasures against these threats. We also carried out basic experiments to confirm its usability by human users.
Using Lexical Chains for Text Summarization

We investigate one technique to produce a summary of an original text without requiring its full semantic interpretation, but instead relying on a model of the topic progression in the text derived from lexical chains. We present a new algorithm to compute lexical chains in a text, merging several robust knowledge sources: the WordNet thesaurus, a part-of-speech tagger, shallow parser for the identification of nominal groups, and a segmentation algorithm. Summarization proceeds in four steps: the original text is segmented, lexical chains are constructed, strong chains are identified and significant sentences are extracted. We present in this paper empirical results on the identification of strong chains and of significant sentences. Preliminary results indicate that quality indicative summaries are produced. Pending problems are identified. Plans to address these short-comings are briefly presented.
Virk: an active learning-based system for bootstrapping knowledge base development in the neurosciences

The frequency and volume of newly-published scientific literature is quickly making manual maintenance of publicly-available databases of primary data unrealistic and costly. Although machine learning (ML) can be useful for developing automated approaches to identifying scientific publications containing relevant information for a database, developing such tools necessitates manually annotating an unrealistic number of documents. One approach to this problem, active learning (AL), builds classification models by iteratively identifying documents that provide the most information to a classifier. Although this approach has been shown to be effective for related problems, in the context of scientific databases curation, it falls short. We present Virk, an AL system that, while being trained, simultaneously learns a classification model and identifies documents having information of interest for a knowledge base. Our approach uses a support vector machine (SVM) classifier with input features derived from neuroscience-related publications from the primary literature. Using our approach, we were able to increase the size of the Neuron Registry, a knowledge base of neuron-related information, by a factor of 90%, a knowledge base of neuron-related information, in 3 months. Using standard biocuration methods, it would have taken between 1 and 2 years to make the same number of contributions to the Neuron Registry. Here, we describe the system pipeline in detail, and evaluate its performance against other approaches to sampling in AL.
Zero-Shot Embedding for Unseen Entities in Knowledge Graph

Knowledge graph (KG) embedding aims at learning the latent semantic representations for entities and relations. However, most existing approaches can only be applied to KG completion, so cannot identify relations including unseen entities (or Out-of-KG entities). In this paper, motivated by the zero-shot learning, we propose a novel model, namely JointE, jointly learning KG and entity descriptions embedding, to extend KG by adding new relations with Out-of-KG entities. The JointE model is evaluated on entity prediction for zero-shot embedding. Empirical comparisons on benchmark datasets show that the proposed JointE model outperforms state-of-the-art approaches. The source code of JointE is available at https://github.com/yzur/JointE. key words: zero-shot learning, knowledge graph, embedding learning, relation prediction
Synthesis and Evaluation of Fe Nanowire and Nanorod by Electro-Chemical Process

Nanoporous structured alumina templates for the synthesis of Fe nanowires were synthesized by the anodization of aluminium metal under various synthetic conditions in some acid solutions. Subsequently, using this nanoporous structured alumina as a template, Fe nanowires with some tens nanometer in diameter and some micron in length was successfully synthesized by both electrodeposition process into various types of porous alumina templates and chemical treatments in mixed-acid solutions to remove the templates. Effects of anodization treatments of aluminium for a porous template on the microstructure of Fe nanowires and nanorods were examined. As a result, the morphology of Fe products obtained by electrodeposition process could be designed with the template obtained under the synthetic conditions (anodization temperatures and electrodeposition conditions etc).
Study on Suitability of KOD DNA Polymerase for Enzymatic Production of Artificial Nucleic Acids Using Base/Sugar Modified Nucleoside Triphosphates

Recently, KOD and its related DNA polymerases have been used for preparing various modified nucleic acids, including not only base-modified nucleic acids, but also sugar-modified ones, such as bridged/locked nucleic acid (BNA/LNA) which would be promising candidates for nucleic acid drugs. However, thus far, reasons for the effectiveness of KOD DNA polymerase for such purposes have not been clearly elucidated. Therefore, using mutated KOD DNA polymerases, we studied here their catalytic properties upon enzymatic incorporation of nucleotide analogues with base/sugar modifications. Experimental data indicate that their characteristic kinetic properties enabled incorporation of various modified nucleotides. Among those KOD mutants, one achieved efficient successive incorporation of bridged nucleotides with a 2′-ONHCH2CH2-4′ linkage. In this study, the characteristic kinetic properties of KOD DNA polymerase for modified nucleoside triphosphates were shown, and the effectiveness of genetic engineering in improvement of the enzyme for modified nucleotide polymerization has been demonstrated.
Vertically dispersive holographic screens and autostereoscopic displays in 3D medical imaging

In this work we describe a setup employed for the recording of vertical dispersive holographic screens that can be used for medical applications. We show how to obtain holographic screens with areas up to 1200 cm2, focal length of 25±2 cm and diffraction efficiency of 7.2%. We analyze the technique employed and the holographic screens obtained. Using this screen we describe a setup for the projection of Magnetic Resonance or Tomographic Images. We also describe and present the first results of an autostereoscopic system for 3D medical imaging.
Optimisation of monolithic lining concepts of channel induction furnace

Abstract For the possible energy savings and extension of the volume capacity, the monolithic lining of a channel induction furnace was optimised in the following manner. Orthogonal array method is utilised to systematically design the lining concepts, and the finite element simulations including the temperature dependent properties of monoliths are carried out to determine the temperatures and stresses during the preheating and holding. In terms of the main effect analysis materials for the monolithic lining are recommended. Moreover, a thickness–thickness–temperature isothermal map is provided to show the acceptable thickness range of working and insulating linings. Nevertheless, for the final decision the deliberate consideration for the cost effectiveness of a certain lining concept is also necessary.