gebhart/patrepeval huggingface dataset:
The Chemokine Receptor CXCR7 Is Highly Expressed in Human Glioma Cells and Mediates Antiapoptotic Effects (2010)

The chemokine CXCL12/stromal cell-derived factor-1 and its receptor CXCR4 play a major role in tumor invasion, proliferation, and metastasis. Recently, CXCR7 was identified as a novel, alternate receptor for CXCL12 and CXCL11/I-TAC. Because both chemokines are expressed abundantly in human astrocytomas and glioblastomas, we investigated the occurrence and function of both receptors in astroglial tumors. In situ, CXCR7 is highly expressed on tumor endothelial, microglial, and glioma cells whereas CXCR4 has a much more restricted localization; CXCL12 is often colocalized with CXCR7. CXCR7 transcription in tumor homogenates increased with malignancy. In vitro, CXCR7 was highly expressed in all glioma cell lines investigated whereas CXCR4 was only scarcely transcribed on one of eight lines. In contrast, a tumor stem-like cell line preferentially expressed CXCR4 which diminished upon differentiation, whereas CXCR7 increased drastically. Stimulation of CXCR7-positive glioma cells (CXCR4- and CXCR3-negative) by CXCL12 induced transient phosphorylation of extracellular signal-regulated kinases Erk1/2, indicating that the receptor is functionally active. The phosphoinositide-specific phospholipase C inhibitor U73122 effectively inhibited Erk activation and suggests that the mitogen-activated protein kinase pathway is activated indirectly. Whereas proliferation and migration were little influenced, chemokine stimulation prevented camptothecin- and temozolomide-induced apoptosis. The selective CXCR7 antagonist CCX733 reduced the antiapoptotic effects of CXCL12 as shown by nuclear (Nicoletti) staining, caspase-3/7 activity assays, and cleavage of poly(ADP-ribose) polymerase-1. Thus, CXCR7 is a functional receptor for CXCL12 in astrocytomas/glioblastomas and mediates resistance to drug-induced apoptosis. Whereas CXCR7 is found on "differentiated" glioma cells, the alternate receptor CXCR4 is also localized on glioma stem-like cells.
Hybrid Sensor Module and Data Processing Using Low-Power Wakeup in WSN (2010)

Due to the development and proliferation of ubiquitous technologies and services, various sensor network applications are being appeared on the stage. The needs for algorithms requiring complex signal processing with a high-performance processor such as digital signal processor are also increased. However, it is difficult to use such processor for the low-power sensor network operating with a battery because of power consumption. This paper proposes and implements hardware and software architecture of the hybrid-type sensor module composed of a low-power sensor module and a high-performance sensor module for the complicated signal processing in the wireless sensor node. Although this approach needs some additional hardware, it results in some improvements in operation time supporting complex algorithms for target detection in the sensor networks.
Machine learning for classification of uterine activity outside pregnancy (2019)

The objective of this study was to investigate the use of classification methods by a machine-learning approach for discriminating the uterine activity during the four phases of the menstrual cycle. Four different classifiers, including support vector machine (SVM), K-nearest neighbors (KNN), Gaussian mixture model (GMM) and naïve Bayes are here proposed. A set of amplitude- and frequency-features were extracted from signals measured by two different quantitative and noninvasive methods, such as electrohysterography and ultrasound speckle tracking. The proposed classifiers were trained using all possible feature combinations. The method was applied on a database (24 measurements) collected in different phases of the menstrual cycle, comprising uterine active and quiescent phases. The SVM classifier showed the best performance for discrimination between the different menstrual phases. The classification accuracy, sensitivity, and specificity were 90%, 79%, 93%, respectively. Similar methods can in the future contribute to the diagnosis of infertility or other common uterine diseases such as endometriosis.
Data Transmission Capabilities of Silicon Avalanche Mode Light-Emitting Diodes (2018)

The data transmission capabilities of silicon avalanche mode light-emitting diodes (AMLEDs) were investigated, and the results are correlated with the multiplication noise and leakage current. The incoming data were modulated using pulse-position modulation, and the bit error rate (BER) and jitter in the transmitted data were measured. The results indicate an intrinsically low speed in terms of BER and jitter. From various size AMLEDs, temperature variations, and optical excitations, it is shown that the speed can be improved by using AMLEDs with a: 1) relatively high multiplication noise; 2) relatively high leakage current; and 3) higher charge-per-bit. Design recommendations for the high-speed AMLEDs are discussed.
Effect of Pressure and Ion Beam Irradiation on the Giant Magnetoresistance of Fe/Cr Magnetic Multilayers (2014)

The effect of high pressure and ion beam irradiation on the magnitude of giant magnetoresistance (GMR) of Fe/Cr magnetic multilayers (MML), [Fe(20 Å)/Cr(t Å)] <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">20</sub> (abbreviated as Fe/Cr(t)), has been measured at 77.4 K. It is found that the GMR of Fe/Cr(8) is decreased but that of Fe/Cr(30) is increased by applying pressure. By ion beam irradiation, the electrical resistance of these MMLs is increased significantly and the magnitude of GMR is decreased. Furthermore we have measured the GMR of irradiated Fe/Cr(8) and Fe/Cr(30) under high pressure and compared the results with the sample before irradiation. The GMR of Fe/Cr(8) after the irradiation is found to increase with pressure and the pressure-coefficient of the saturation resistivity is extremely large. These results are discussed on the basis of the spin dependent scattering by the roughness at the interfaces and also bulk scattering in MML in connection with an irradiation-induced instability of the electronic states in Fe/Cr(8).
Institutional Profile: The Carolina Center of Cancer Nanotechnology Excellence: Past Accomplishments and Future Perspectives (2010)

The Carolina Center of Cancer Nanotechnology Excellence (C-CCNE) is funded by the National Cancer Institute and is based at the University of North Carolina. The C-CCNE features interactions between physical and biological scientists in a series of projects and cores that work together to quickly harness innovations in nanotechnology for the early diagnosis and treatment of cancer. Two key focus areas of the C-CCNE are, first, the selective delivery of drugs and imaging agents utilizing advanced nanoparticle technology, and second, novel approaches to imaging and radiotherapy utilizing carbon nanotube-based x-ray sources.
Abstract 178: RASSF10 is frequently methylated in epithelial cancers (2010)

Abstract The classical Ras-association domain family (RASSF1-6) are a group of Ras effector molecules that contain a C-terminal Ras-association (RA) domain of the RalGDS/AF-6 variety and a protein interaction domain known as the Sav/RASSF/Hippo (SARAH) domain. Several members of the classical RASSF family are involved in tumorigenesis since epigenetic inactivation of many isoforms is a frequent event across many tumor types and their functions are consistent with roles as tumor suppressor proteins. Recently several additional RA-domain containing family members have been identified and designated N-terminal RASSF proteins (RASSF7-10). These comprise RASSF7 (also known as HRC1 located 11p15.5), RASSF8 (also known as HOJ-1 or C12ORF2 located 12p12.1), RASSF9 (also known as P-CIP1 or PAMCI located 12q21.31) and RASSF10 (located 11p15.2). These proteins are divergent and structurally distinct from RASSF1-6, containing an RA domain within their extreme N-termini and lacking the SARAH protein interaction domain. Little is known about the N-terminal RASSF7-10 proteins although they represent an evolutionarily conserved group of proteins with orthologues of all four in the lower vertebrate Xenopus laevis and a RASSF7/8 homologue in Drosophila melanogaster distinct from the RASSF1-6 Drosophila homologue. We have recently characterized the N-terminal RASSF10 gene and demonstrated frequent methylation of the associated 5’ CpG island in acute lymphoblastic leukemia. In this report we analysed the methylation status of the CpG island in a range of common epithelial cancers. RASSF10 was frequently methylated in grade II-IV gliomas (grade II, 50%; grade III, 80%, grade IV 57%) but was unmethylated in grade I astrocytomas and in DNA from age matched control brain samples. In other common epithelial cancers RASSF10 was also methylated but at a lesser frequency compared to grade II-IV gliomas. RASSF10 was methylated in 25% breast tumors, 31% of colorectal cancers, 20% lung tumors and 28% of renal cell carcinomas. RASSF10 was unmethylated in DNA from corresponding normal tissues or control tissue samples. This work demonstrates that RASSF10 is a frequent target of epigenetic inactivation in a range of epithelial cancers as well as haematological cancers. We are now undertaking biological characterization of this novel protein. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 178.
Introducing the Resource Prospector (RP) Mission (2014)

he Resource Prospector (RP) Mission is an in-situ resource utilization (ISRU) technology demonstration mission under study by NASA’s Human Exploration and Operations Mission Directorate’s (HEOMD’s) Advanced Exploration Systems (AES) Division. The mission, currently planned to launch in 2019, will demonstrate prospecting for volatiles and extraction of oxygen from lunar regolith as an ISRU demonstration. The mission will utilize the RESOLVE (Regolith & Environment Science and Oxygen & Lunar Volatile Extraction) payload, developed by NASA. RP will address key Strategic Knowledge Gaps (SKGs) for robotic and human exploration to the moon, Near Earth Asteroids (NEAs), and ultimately Mars. The concept of ‘strategic knowledge gaps’ for all potential human destinations was developed by HEOMD as a guide for Agency investments including robotic precursor missions and the SKGs were externally vetted and contributed to by all three analysis groups for the three key future human destinations: asteroids (Small Bodies Analysis Group or SBAG), the moon (Lunar Exploration Analysis Group or LEAG), and Mars (the Mars Exploration Program Analysis Group or MEPAG), and then vetted by the international space community via the International Space Exploration Coordination Group (ISECG).
Evolutionary computation and evolutionary deep learning for image analysis, signal processing and pattern recognition (2021)

tutorial Evolutionary computation and evolutionary deep learning for image analysis, signal processing and pattern recognition Authors: Mengjie Zhang Victoria University of Wellington, Wellington, New Zealand Victoria University of Wellington, Wellington, New ZealandView Profile , Stefano Cagnoni University of Parma, Parma, Italy University of Parma, Parma, ItalyView Profile Authors Info & Claims GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference CompanionJuly 2021 Pages 1169–1198https://doi.org/10.1145/3449726.3461412Published:08 July 2021Publication History 0citation84DownloadsMetricsTotal Citations0Total Downloads84Last 12 Months11Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Re-Examination of Performance and Reliability Degradation in Metal–Oxide–Nitride–Oxide–Semiconductor Memory with Ultrathin SiN Charge Trap Layers (2012)

We demonstrated that the degradation of program characteristics in metal–oxide–nitride–oxide–semiconductor (MONOS) devices consisting of an ultrathin (∼2 nm) SiN charge trap layer is due to a decrease in the electron capture efficiency, instead of a reduction in the number of available trap sites. From the data retention properties with applied gate bias voltage, we clarified that charge loss through the tunnel layer during data retention becomes more significant with decreasing SiN thickness. These results indicate that to improve the performance and reliability of MONOS devices with an ultrathin SiN charge trap layer, measures must be taken to enhance the capture cross section of the traps and to inhibit carrier motion in the SiN layer simultaneously.
Immune‐instructive scaffolds modulating inflammation to promote bone regeneration (2020)

Background: The repair and treatment of large bone defects following trauma, ablative surgery or pathological bone changes presents often a clinical challenge, and adjunctive methods to enhance bone healing are needed. Bone tissue engineering have emerged as highly progressive alternative treatments, multidisciplinary fields of research, combining molecular and cell biology, material engineering, nanotechnology and other disciplines. Aim/Hypothesis: The aim of our study was to investigate the possibility of copolymer scaffold functionalised with plant-derived Rhamnogalacturonan-I pectins (RG-I) to modulate inflammation to promote bone regeneration. Materials and Methods: The 3D-printed bone graft used in this study were poly(L-lactide-co-e-caprolactone) scaffolds (PCLA). The chemical and physical properties of functionalised PCLA with RG-I nanoparticles (PCLA RG-I) were characterized using confocal and atomic force microscopy (AFM). PCLA RG-I and PCLA (control) were tested in vitro, using human immune cells and in vivo using subcutaneous rat model. Cell response was tested using real-time PCR. For in vivo study, PCLA RG-I and control, PLCA were implanted subcutaneously into female Wistar rats and scaffolds were distributed randomly. Animals were sacrificed at 4 days and 4 weeks after implantation to test acute and chronic inflammatory response. Harvested samples were analysed for inflammatory markers. Data were analysed using one-way ANOVA. Results: The chemical and physical properties results indicated success of the functionalization of PCLA with RG-I. The cell response on PCLA RG-I showed significant increase of anti-inflammatory gene, IL10 and decrease of pro-inflammatory (LGALS1, LGALS3, TNFA, IL1A, IL1B, TLR2, TLR4, IL6, IL8) genes expression. The subcutaneous model confirmed the in vitro results, showing a decrease of proinflammatory gene expression in early and late time points. In addition, results showed significant (3 folds) increase of anti-inflammatory gene expression, IL10. The histology showed spare inflammatory capsule around PCLA RG-I scaffolds after 4 days and 4 weeks. Conclusions and Clinical Implications: In conclusion, the RG-I nanoparticles significantly decreased pro-inflammatory response in vitro and in vivo, indicating their anti-inflammatory properties. These finding may have a crucial influence on bone regeneration especially in elderly and immunocompromised patients. Keywords: Bone regeneration, 3D scaffold, acute and chronic inflammation, Rhamnogalacturonan-I, Nanoparticles.
Role of distension on duodenal and colonic contractility in mice: a novel myograph for intestines (2012)

Our results suggest that distension is an important stimulus for intestinal contractility and nervous regulation is implicated in the intestinal contractility response to mechanical stimulus.
Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems (2023)

Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains. As opposed to purely data-driven methods, PIML models can be trained from additional information obtained by enforcing physical laws such as energy and mass conservation. More broadly, PIML models can include abstract properties and conditions such as stability, convexity, or invariance. The basic premise of PIML is that the integration of ML and physics can yield more effective, physically consistent, and data-efficient models. This paper aims to provide a tutorial-like overview of the recent advances in PIML for dynamical system modeling and control. Specifically, the paper covers an overview of the theory, fundamental concepts and methods, tools, and applications on topics of: 1) physics-informed learning for system identification; 2) physics-informed learning for control; 3) analysis and verification of PIML models; and 4) physics-informed digital twins. The paper is concluded with a perspective on open challenges and future research opportunities.
A 122-150 GHz LNA with 30 dB gain and 6.2 dB noise figure in SiGe BiCMOS technology (2015)

This paper presents a D-Band Low Noise Amplifier (LNA) for imaging applications designed in an advanced 90 nm SiGe BiCMOS process. The LNA consists of 3 cascode stages and one common-emitter stage and achieves peak gain of 30 dB and 3 dB bandwidth at 122-150 GHz. The measured noise figure is maintained below 7.5 dB over the measurement band with minimum of 6.2 dB at 140 GHz. The amplifier consumes DC power of only 45 mW, and occupies area of 0.11 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> (without pads), which make it suitable for integration in large scale imaging arrays. To our knowledge, this work demonstrates the highest gain, highest bandwidth and lowest noise figure achieved so far at D-Band in any silicon-based technology.
Clay Bragg Stack Optical Sensors (2008)

Functional 1D photonic crystals are fabricated based on the clay Laponite and mesoporous oxide layers. Color-tunable clay Bragg stacks are sensitive to a wide range of analytes and show potential as intelligent optical devices for chemo-optical sensing applications. Detailed facts of importance to specialist readers are published as ”Supporting Information”. Such documents are peer-reviewed, but not copy-edited or typeset. They are made available as submitted by the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
Improved microarray methods for profiling the yeast knockout strain collection (2005)

A remarkable feature of the Yeast Knockout strain collection is the presence of two unique 20mer TAG sequences in almost every strain. In principle, the relative abundances of strains in a complex mixture can be profiled swiftly and quantitatively by amplifying these sequences and hybridizing them to microarrays, but TAG microarrays have not been widely used. Here, we introduce a TAG microarray design with sophisticated controls and describe a robust method for hybridizing high concentrations of dye-labeled TAGs in single-stranded form. We also highlight the importance of avoiding PCR contamination and provide procedures for detection and eradication. Validation experiments using these methods yielded false positive (FP) and false negative (FN) rates for individual TAG detection of 3-6% and 15-18%, respectively. Analysis demonstrated that cross-hybridization was the chief source of FPs, while TAG amplification defects were the main cause of FNs. The materials, protocols, data and associated software described here comprise a suite of experimental resources that should facilitate the use of TAG microarrays for a wide variety of genetic screens.
Identification of a five‐oxidoreductase‐gene cluster from Acetobacter pasteurianus conferring ethanol‐dependent acidification in Escherichia coli (2012)

Acetobacter pasteurianus, a Gram-negative bacterium belonging to the α-divison of Proteobacteria, produces acetic acid through ethanol oxidation. A genomic bank of A. pasteurianus 386B DNA was cloned in the low-copy cosmid pRG930Cm vector and the resulting clones were screened for the production of protease using the skimmed-milk agar assay whereby a clearing zone around the inoculated spots indicates casein degradation. Several positive clones were selected and restriction analysis revealed that many contained the same inserts. One clone was further analyzed and the cosmid DNA subjected to in vitro transposon insertion. After electroporation, several clones having lost the capacity to cause casein degradation were isolated and the sequence of the transposon-flanking regions analyzed. The majority of insertions mapped to one gene encoding an NAD(P)(+)-dependent aldehyde dehydrogenase (ALDH) of the PNTB superfamily, whereas one insert was found upstream in a gene encoding an ethanol dehydrogenase. Addition of phenol red to the medium confirmed the ethanol-dependent acidification around the inoculated spots of the clones without transposon insertion, suggesting that casein degradation is due to the production of acetic acid as a result of the combined activities of the alcohol dehydrogenase and ALDH. Quantitative data and pH measurements confirmed a significant acidification, and the presence of acetic acid.
Comparative analysis of image-based phenotypes of mammographic density and parenchymal patterns in distinguishing betweenBRCA1/2cases, unilateral cancer cases, and controls (2014)

We statistically compare the contributions of parenchymal phenotypes to mammographic density in distinguishing between high-risk cases and low-risk controls. The age-matched evaluation included computerized mammographic assessment of breast percent density (PD) and parenchymal patterns (phenotypes of coarseness and contrast) from radiographic texture analysis (RTA) of the full-field digital mammograms from 456 cases: 53 women with BRCA1/2 gene mutations, 75 with unilateral cancer, and 328 at low risk of developing breast cancer. Image-based phenotypes of parenchymal pattern coarseness and contrast were each found to significantly discriminate between the groups; however, PD did not. From ROC analysis, PD alone yielded area under the fitted ROC curve (AUC) values of 0.53 ([Formula: see text]) and 0.57 ([Formula: see text]) in the classification task between BRCA1/2 gene-mutation carriers and low-risk women, and between unilateral cancer and low-risk women, respectively. In a round-robin evaluation with Bayesian artificial neural network (BANN) analysis, RTA yielded AUC values of 0.81 (95% confidence interval [0.71, 0.89]) and 0.70 (95% confidence interval [0.63, 0.77]) between the BRCA1/2 gene-mutation carriers and low-risk women, and between unilateral cancer and low-risk women, respectively. These results show that high-risk and low-risk women have different mammographic parenchymal patterns with significantly higher discrimination resulting from characteristics of the parenchymal patterns than just the breast PD.
A Simple and Novel Way to Synthesize Aligned Nanotube Bundles at Low Temperature (1998)

Large scale quantities of quasi-aligned carbon nanotube bundles have been synthesized by catalytic decomposition of acetylene over well dispersed metal particles (cobalt and vanadium) embedded in commercially available zeolite at 700°C. Scanning electron microscopy analysis revealed the homogenous nature of the sample while transmission electron microscopy studies revealed the perfect graphitization as well as the inner and outer diameters of the tubes.