gebhart/patrepeval huggingface dataset:
Imaging neural crest cell dynamics during formation of dorsal root ganglia and sympathetic ganglia (2004)

The neural crest is a migratory population of cells that produces many diverse structures within the embryo. Trunk neural crest cells give rise to such structures as the dorsal root ganglia (DRG) and sympathetic ganglia (SG), which form in a metameric pattern along the anterior-posterior axis of the embryo. While static analyses have provided invaluable information concerning the development of these structures, time-lapse imaging of neural crest cells navigating through their normal environment could potentially reveal previously unidentified cellular and molecular interactions integral to DRG and SG development. In this study, we follow fluorescently labeled trunk neural crest cells using a novel sagittal explant and time-lapse confocal microscopy. We show that along their dorsoventral migratory route, trunk neural crest cells are highly motile and interact extensively with neighboring cells and the environment, with many cells migrating in chain-like formations. Surprisingly, the segregated pattern of crest cell streams through the rostral somite is not maintained once these cells arrive alongside the dorsal aorta. Instead, neural crest cells disperse along the ventral outer border of the somite, interacting extensively with each other and their environment via dynamic extension and retraction of filopodia. Discrete sympathetic ganglia arise as a consequence of intermixing and selective reorganization of neural crest cells at the target site. The diverse cell migratory behaviors and active reorganization at the target suggest that cell-cell and cell-environment interactions are coordinated with dynamic molecular processes.
Molecular imaging of matrix metalloproteinases in atherosclerotic plaques (2012)

Ischaemic stroke and myocardial infarction often result from the sudden rupture of an atherosclerotic plaque. The subsequent arterial thrombosis occluding the vessel lumen has been widely indicated as the crucial acute event causing peripheral tissue ischaemia. A complex cross-talk between systemic and intraplaque inflammatory mediators has been shown to regulate maturation, remodeling and final rupture of an atherosclerotic plaque. Matrix metalloproteinases (MMPs) are proteolytic enzymes (released by several cell subsets within atherosclerotic plaques), which favour atherogenesis and increase plaque vulnerability. Thus, the assessment of intraplaque levels and activity of MMP might be of pivotal relevance in the evaluation of the risk of rupture. New imaging approaches, focused on the visualisation of inflammation in the vessel wall and plaque, may emerge as tools for individualised risk assessment and prevention of events. In this review, we summarize experimental findings of the currently available invasive and noninvasive imaging techniques, used to detect the presence and activity of MMPs in atherosclerotic plaques.
Resistance of Cu(Aβ4–16) to Copper Capture by Metallothionein‐3 Supports a Function for the Aβ4–42 Peptide as a Synaptic CuII Scavenger (2016)

Abstract Aβ4‐42 is a major species of Aβ peptide in the brains of both healthy individuals and those affected by Alzheimer's disease. It has recently been demonstrated to bind Cu II with an affinity approximately 3000 times higher than the commonly studied Aβ1‐42 and Aβ1‐40 peptides, which are implicated in the pathogenesis of Alzheimer's disease. Metallothionein‐3, a protein considered to orchestrate copper and zinc metabolism in the brain and provide antioxidant protection, was shown to extract Cu II from Aβ1‐40 when acting in its native Zn 7 MT‐3 form. This reaction is assumed to underlie the neuroprotective effect of Zn 7 MT‐3 against Aβ toxicity. In this work, we used the truncated model peptides Aβ1‐16 and Aβ4‐16 to demonstrate that the high‐affinity Cu II complex of Aβ4‐16 is resistant to Zn 7 MT‐3 reactivity. This indicates that the analogous complex of the full‐length peptide Cu(Aβ4‐42) will not yield copper to MT‐3 in the brain, thus supporting the concept of a physiological role for Aβ4‐42 as a Cu II scavenger in the synaptic cleft.
BACOM 2.0 facilitates absolute normalization and quantification of somatic copy number alterations in heterogeneous tumor (2013)

BACOM is a statistically principled and unsupervised method that detects copy number deletion types (homozygous versus heterozygous), estimates normal cell fraction, and recovers cancer specific copy number profiles, using allele specific copy number signals. In a subsequent analysis of TCGA ovarian cancer dataset, the average normal cell fraction estimated by BACOM was found higher than expected. In this letter, we first discuss the advantages of the BACOM in relation to alternative approaches. Then, we show that this elevated estimate of normal cell fraction is the combined result of inaccurate signal modeling and normalization. Lastly, we describe an allele specific signal modeling and normalization scheme that can enhance BACOM applications in many biological contexts. An open source MATLAB program was developed to implement our extended method and it is publically available.
The structure of 3,5-dinitroisoxazole (1987)

C 3 HN 3 O 5 cristallise avec le groupe d'espace P1. Affinement de la structure jusqu'a 0,044
2012-2013 North Anatolian Fault Microearthquake Catalog (2022)

Catalog of microseismicity along the North Anatolian Fault near the city of Izmit, Turkey, between May 2012 and September 2013. This catalog accompanies the article "Microseismic Constraints on the State of the North Anatolian Fault Thirteen Years after the 1999 M7.4 Izmit Earthquake" authored by Eric Beaucé, Robert D. van der Hilst, and Michel Campillo. The data are written in a csv file, and a README.txt contains information on the structure of the csv file.
Differential Radiosensitization in DNA Mismatch Repair-Proficient and -Deficient Human Colon Cancer Xenografts with 5-Iodo-2-pyrimidinone-2′-deoxyribose (2004)

These results suggest that IPdR-mediated radiosensitization can be an effective in vivo approach to treat "drug-resistant" MMR-deficient tumors as well as MMR-proficient tumors.
A novel method to estimate model uncertainty using machine learning techniques (2009)

A novel method is presented for model uncertainty estimation using machine learning techniques and its application in rainfall runoff modeling. In this method, first, the probability distribution of the model error is estimated separately for different hydrological situations and second, the parameters characterizing this distribution are aggregated and used as output target values for building the training sets for the machine learning model. This latter model, being trained, encapsulates the information about the model error localized for different hydrological conditions in the past and is used to estimate the probability distribution of the model error for the new hydrological model runs. The M5 model tree is used as a machine learning model. The method is tested to estimate uncertainty of a conceptual rainfall runoff model of the Bagmati catchment in Nepal. In this paper the method is extended further to enable it to predict an approximation of the whole error distribution, and also the new results of comparing this method to other uncertainty estimation approaches are reported. It can be concluded that the method generates consistent, interpretable and improved model uncertainty estimates.
Efficient Searchable Symmetric Encryption for Storing Multiple Source Data on Cloud (2015)

Cloud computing has greatly facilitated large-scale data outsourcing due to its cost efficiency, scalability and many other advantages. Subsequent privacy risks force data owners to encrypt sensitive data, hence making the outsourced data no longer searchable. Searchable Symmetric Encryption (SSE) is an advanced cryptographic primitive addressing the above issue, which maintains efficient keyword search over encrypted data without disclosing much information to the storage provider. Existing SSE schemes implicitly assume that original user data is centralized, so that a searchable index can be built at once. Nevertheless, especially in cloud computing applications, user-side data centralization is not reasonable, e.g. an enterprise distributes its data in several data centers. In this paper, we propose the notion of Multi-Data-Source SSE (MDS-SSE), which allows each data source to build a local index individually and enables the storage provider to merge all local indexes into a global index afterwards. We propose a novel MDS-SSE scheme, in which an adversary only learns the number of data sources, the number of entire data files, the access pattern and the search pattern, but not any other distribution information such as how data files or search results are distributed over data sources. We offer rigorous security proof of our scheme, and report experimental results to demonstrate the efficiency of our scheme.
DANGEROUS DRIVERS: RECOGNITION, SELECTION AND EFFECT (1976)

HITHERTO, NO DEMONSTRATION HAS BEEN AVAILABLE REGARDING THE RELATIONSHIP BETWEEN GENERAL CRIMINALITY AND ACCIDENT PRONENESS. NEITHER HAS THERE BEEN CONFIRMATION OF THE CONCEPT OF THE SO-CALLED ACCIDENT-PRONE PERSON. DRIVING INABILITY CAN BE EXCLUDED BY MEANS OF DRIVING TESTS. DEFECTIVE PERSONALITY TRAITS ARE, HOWEVER, MORE DIFFICULT TO ELIMINATE, AS EACH PERSON WHO HAS NEGATIVE PERSONABILITY TRAITS WITH REGARD TO TRAFFIC, ALSO POSSESSES GOOD FEATURES WHICH COMPENSATE. WITH THE AID OF ACCIDENT ANALYSES, AN ATTEMPT IS THEREFORE MADE TO ISOLATE ACCIDENT RELATED PATTERNS OF BEHAVIOUR, IN ORDER TO WITHDRAW EACH DRIVER WHO DISPLAYS SUCH CHARACTERISTICS FROM TRAFFIC BEFORE HE MEETS WITH AN ACCIDENT. HOWEVER, SUFFICIENT ACCIDENT STATISTICS ARE NOT YET AVAILABLE, NOR IS THE CENTRAL STORAGE OF DATA ON TRAFFIC OFFENCES.
Plasmon-Mediated Surface Chemistry for Solar Photocatalysis (2015)

Using sunlight to facilitate and promote valuable chemical reactions is an ideal solution to the challenge of meeting future energy demands. Our group aims to address fundamental questions concerning surface plasmon resonance (SPR)-mediated interfacial electron transfer (ET) and photothermal heating in order to develop new materials and strategies for efficiently converting solar energy to chemical energy. In this talk, I will show how we unambiguously reveal the mechanics of plasmon-mediated electron transfer (PMET) in Au/TiO 2 heterostructures under visible light (λ &gt; 515 nm) during in situ operation. I will further discuss how we directly probe the relaxation dynamics and energetics of the transferred “effective hot electrons” that participate in photocatalytic reactions. I will explore some strategies for manipulating “hot electrons” for the rational design and construction of a new class of multi-component solar photocatalysts for efficiently producing H 2 from water.
ChemInform Abstract: Cycloaddition of Arynes and Cyclic Enol Ethers as a Platform for Access to Stereochemically Defined 1,2‐Disubstituted Benzocyclobutenes. (2015)

Abstract The reaction is investigated for various substrate types to produce the desired fused ring system.
Phase Change of Gallium Enables Highly Reversible and Switchable Adhesion (2016)

Gallium exhibits highly reversible and switchable adhesion when it undergoes a solid–liquid phase transition. The robustness of gallium is notable as it exhibits strong performance on a wide range of smooth and rough surfaces, under both dry and wet conditions. Gallium may therefore find numerous applications in transfer printing, robotics, electronic packaging, and biomedicine. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re-organized for online delivery, but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to 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.
A Road Network Traffic State Identification Method Based on Macroscopic Fundamental Diagram and Spectral Clustering and Support Vector Machine (2019)

Accurate identification of road network traffic status is the key to improve the efficiency of urban traffic control and management. Both data mining method and MFD‐based methods can divide the traffic state of road network, but each has its own advantages and disadvantages. The data mining method is oriented to traffic data with high efficiency, but it can only discriminate traffic status from microlevel, while the MFD of road network can discriminate traffic status from macrolevel, but there are still some problems, such as the fact that the discriminant method of equivalence points based on MFD lacks theoretical support or that traffic status could not be subdivided. If data mining methods and road network’s MFD are combined, the accuracy of road network traffic state identification will be greatly improved. In addition, the research shows that the combination of unsupervised learning clustering analysis method (such as spectral clustering algorithm) and supervised learning machine algorithm (such as support vector machine algorithm (SVM)) is more accurate in traffic state identification. Therefore, a traffic state identification method based on MFD and spectral clustering and SVM is proposed, combining the advantages of spectral clustering algorithm and SVM algorithm. Firstly, spectral clustering algorithm is used to classify the traffic state of road network’s MFD. Secondly, SVM multiclassifier is trained with the partitioned road network’s MFD parameters, and the accuracy evaluation method of classification results based on obfuscation matrix is given. Finally, the connected‐vehicle network simulation platform is built for empirical analysis. The results show that the classification results of spectral clustering algorithm are closer to the theoretical values, compared with K‐means algorithm, and the accuracy of SVM multiclassifier is 96.3%. It can be seen that our algorithm can identify the road network traffic state more effectively from the macrolevel.
Failing to make contact: young men’s health (2002)

There is consistent evidence that men have a higher health risk than women, with heart disease, accidents, and alcohol and drug abuse being particularly significant (Lloyd and Forrest, 2001). Most of these differences are attributable to behaviour rather than genetics. Harrison and Dignan (1999) have suggested that men ignore their health because cultural emphasis on combat, competition and independence results in them taking ‘risks’ for ‘fun’. Further, Helman (1994) has suggested that maleness requires the drinking of alcohol and the smoking of cigarettes as part of the validation of the gender role. In this way male culture negatively impacts on health through its promotion of unhealthy life choices and occupations.
Investigation of novel quantum dots/proteins/cellulose bioconjugate using NSOM and photoluminescence (2004)

We investigated the engineered bioconjugate of cadmium selenide core/zinc sulfide shell, (CdSe)ZnS, quantum dots (QDs) with genetically modified proteins using near-field scanning optical microscopy (NSOM). A genetically engineered protein polymer was expressed and purified from E. coli. The protein polymer was allowed to self-assemble to the bacterial microcrystalline cellulose surface through the cellulosic binding domain. QDs were then conjugated to the protein/cellulose assembly through interaction with the 6x-histidine tag on the protein. The transmitted near-field optical signals are collected and detected by both a PMT (near-field scanning optical microscopy, NSOM) and a spectrometer (near-field scanning optical spectroscopy, NSOS). Results from the sample containing the QDs/protein/cellulose assemblies suggest that QDs were arrayed along the cellulose surface. The near-field spectroscopic study also showed that the slight change of spectroscopic properties of the QDs upon bioconjugation, indicating the strong interaction between the constructed protein and QDs.
Sequential verification of exogenous protein production in OVA gene-targeted chicken bioreactors (2022)

The chicken has potential as an efficient bioreactor system because of its outstanding protein production capacity and low cost. The CRISPR/Cas9-mediated gene-editing system enables production of highly marketable exogenous proteins in transgenic chicken bioreactors. However, because it takes approximately 18 mo to evaluate the recombinant protein productivity of the bioreactor due to the generation interval from G0 founders to G1 egg-laying hens, to verification of the exogenous protein at the early stage is difficult. Here we propose a system for sequential validation of exogenous protein production in chicken bioreactors as in hatching female chicks as well as in egg-laying hens. We generated chicken OVALBUMIN (OVA) EGFP knock-in (KI) chicken (OVA EGFP KI) by CRISPR/Cas9-mediated nonhomologous end joining at the chicken OVA gene locus. Subsequently, the estrogen analog, diethylstilbestrol (DES), was subcutaneously implanted in the abdominal region of 1-wk-old OVA EGFP KI female chicks to artificially increase OVALBUMIN expression. The oviducts of DES-treated OVA EGFP KI female chicks expressed OVA and EGFP at the 3-wk-old stage (10 d after DES treatment). We evaluated the expression of EGFP protein in the oviduct, along with the physical properties of eggs and egg white from OVA EGFP KI hens. The rapid identification and isolation of exogenous protein can be confirmed at a very early stage and high-yield production is possible by targeting the chicken oviduct.
Variable Explicit Regularization in Affine Projection Algorithm: Robustness Issues and Optimal Choice (2007)

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> A variable regularized affine projection algorithm (VR-APA) is introduced, without requiring the classical step size. Its use is supported from different points of view. First, it has the property of being <emphasis><formula formulatype="inline"> <tex>$H^{\infty}$</tex></formula></emphasis> optimal and it satisfies certain error energy bounds. Second, the time-varying regularization parameter is obtained by maximizing the speed of convergence of the algorithm. Although we first derive the VR-APA for a linear time invariant (LTI) system, we show that the same expression holds if we consider a time-varying system following a first-order Markov model. We also find expressions for the power of the steady-state error vector for the VR-APA and the standard APA with no regularization parameter. Particularly, we obtain quite different results with and without using the independence assumption between the <emphasis emphasistype="bold"><emphasis emphasistype="italic">a priori</emphasis></emphasis> error vector and the measurement noise vector. Simulation results are presented to test the performance of the proposed algorithm and to compare it with other schemes under different situations. An important conclusion is that the former independence assumption can lead to very inaccurate steady-state results, especially when high values of the projection order are used. </para>
Volatile organic sulfur compounds in anaerobic sludge and sediments: Biodegradation and toxicity (2006)

A variety of environmental samples was screened for anaerobic degradation of methanethiol, ethanethiol, propanethiol, dimethylsulfide, and dimethyldisulfide. All sludge and sediment samples degraded methanethiol, dimethylsulfide, and dimethyldisulfide anaerobically. In contrast, ethanethiol and propanethiol were not degraded by the samples investigated under any of the conditions tested. Methanethiol, dimethylsulfide, and dimethyldisulfide were mainly degraded by methanogenic archaea. In the presence of sulfate and the methanogenic inhibitor bromoethane sulfonate, degradation of these compounds coupled to sulfate reduction occurred as well, but at much lower rates. Besides their biodegradability, also the toxicity of methanethiol, ethanethiol, and propanethiol to methanogenesis with methanol, acetate, and H2/CO2 as the substrates was assessed. The 50% inhibition concentration of methanethiol on the methane production from these substrates ranged between 7 and 10 mM. The 50% inhibition concentration values of ethanethiol and propanethiol for the degradation of methanol and acetate were between 6 and 8 mM, whereas hydrogen consumers were less affected by ethanethiol and propanethiol, as indicated by their higher 50% inhibition concentration (14 mM). Sulfide inhibited methanethiol degradation already at relatively low concentrations: methanethiol degradation was almost completely inhibited at an initial sulfide concentration of 8 mM. These results define the operational limits of anaerobic technologies for the treatment of volatile organic sulfur compounds in sulfide-containing wastewater streams.
Nerva Flight Engine Control System Design (1972)

Modern control system theory has been applied to the design of the control system for the nerva nuclear rocket engine. Multiloop classical controls design approach has been used previously in the engine test program. The configuration and operation of the engine system with the resulting high degree of coupling and the multivariable nature of the system establishes a need for modern control techniques with considerable ad vantages over classical methods. The design procedure consists of system model linearization, system simplification, and the quadratic optimal control design. Transient performance results have been obtained from digital implimentation of the control system.
Illumination Compensation and Normalization for Automatic Recognition of Rapid Diagnostic Kits (2015)

In this paper, we present an illumination compensation technique and a region of interest (ROI) extraction method for the recognition of medical diagnostic kits. The Hough transform and a multi-stage image segmentation technique are used for the ROI extraction method. To improve the accuracy of quantitative recognition, an illumination normalization method which is adaptive to the variations of background image and lighting conditions is proposed. Varying illumination condition may cause a distortion of color and intensity information of the target image. Therefore, we propose a data conversion method called illumination compensation curve which can be adjusted by a set of reference image patterns. The curve is generated by calculating the compensation factor from the change of average RGB values in the ROI of the reference image patterns. We discuss the usability of the suggested methods through the experimental results which are applied to 20 types of kit image patterns.
Supplementary figures and tables FTS1 from Intraperitoneal Monocytes plus IFNs as a Novel Cellular Immunotherapy for Ovarian Cancer: Mechanistic Characterization and Results from a Phase I Clinical Trial (2023)

&lt;p&gt;Supplementary figures and tables&lt;/p&gt;