Deep ensemble learning of sparse regression models for brain disease diagnosis

PubMed Central

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2018-01-01

Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in computer-assisted intervention for brain disease diagnosis. Of various machine-learning techniques, sparse regression models have proved their effectiveness in handling high-dimensional data but with a small number of training samples, especially in medical problems. In the meantime, deep learning methods have been making great successes by outperforming the state-of-the-art performances in various applications. In this paper, we propose a novel framework that combines the two conceptually different methods of sparse regression and deep learning for Alzheimer’s disease/mild cognitive impairment diagnosis and prognosis. Specifically, we first train multiple sparse regression models, each of which is trained with different values of a regularization control parameter. Thus, our multiple sparse regression models potentially select different feature subsets from the original feature set; thereby they have different powers to predict the response values, i.e., clinical label and clinical scores in our work. By regarding the response values from our sparse regression models as target-level representations, we then build a deep convolutional neural network for clinical decision making, which thus we call ‘ Deep Ensemble Sparse Regression Network.’ To our best knowledge, this is the first work that combines sparse regression models with deep neural network. In our experiments with the ADNI cohort, we validated the effectiveness of the proposed method by achieving the highest diagnostic accuracies in three classification tasks. We also rigorously analyzed our results and compared with the previous studies on the ADNI cohort in the literature. PMID:28167394

Robust multi-atlas label propagation by deep sparse representation

PubMed Central

Zu, Chen; Wang, Zhengxia; Zhang, Daoqiang; Liang, Peipeng; Shi, Yonghong; Shen, Dinggang; Wu, Guorong

2016-01-01

Recently, multi-atlas patch-based label fusion has achieved many successes in medical imaging area. The basic assumption in the current state-of-the-art approaches is that the image patch at the target image point can be represented by a patch dictionary consisting of atlas patches from registered atlas images. Therefore, the label at the target image point can be determined by fusing labels of atlas image patches with similar anatomical structures. However, such assumption on image patch representation does not always hold in label fusion since (1) the image content within the patch may be corrupted due to noise and artifact; and (2) the distribution of morphometric patterns among atlas patches might be unbalanced such that the majority patterns can dominate label fusion result over other minority patterns. The violation of the above basic assumptions could significantly undermine the label fusion accuracy. To overcome these issues, we first consider forming label-specific group for the atlas patches with the same label. Then, we alter the conventional flat and shallow dictionary to a deep multi-layer structure, where the top layer (label-specific dictionaries) consists of groups of representative atlas patches and the subsequent layers (residual dictionaries) hierarchically encode the patchwise residual information in different scales. Thus, the label fusion follows the representation consensus across representative dictionaries. However, the representation of target patch in each group is iteratively optimized by using the representative atlas patches in each label-specific dictionary exclusively to match the principal patterns and also using all residual patterns across groups collaboratively to overcome the issue that some groups might be absent of certain variation patterns presented in the target image patch. Promising segmentation results have been achieved in labeling hippocampus on ADNI dataset, as well as basal ganglia and brainstem structures, compared to other counterpart label fusion methods. PMID:27942077

Robust multi-atlas label propagation by deep sparse representation.

PubMed

Zu, Chen; Wang, Zhengxia; Zhang, Daoqiang; Liang, Peipeng; Shi, Yonghong; Shen, Dinggang; Wu, Guorong

2017-03-01

Recently, multi-atlas patch-based label fusion has achieved many successes in medical imaging area. The basic assumption in the current state-of-the-art approaches is that the image patch at the target image point can be represented by a patch dictionary consisting of atlas patches from registered atlas images. Therefore, the label at the target image point can be determined by fusing labels of atlas image patches with similar anatomical structures. However, such assumption on image patch representation does not always hold in label fusion since (1) the image content within the patch may be corrupted due to noise and artifact; and (2) the distribution of morphometric patterns among atlas patches might be unbalanced such that the majority patterns can dominate label fusion result over other minority patterns. The violation of the above basic assumptions could significantly undermine the label fusion accuracy. To overcome these issues, we first consider forming label-specific group for the atlas patches with the same label. Then, we alter the conventional flat and shallow dictionary to a deep multi-layer structure, where the top layer ( label-specific dictionaries ) consists of groups of representative atlas patches and the subsequent layers ( residual dictionaries ) hierarchically encode the patchwise residual information in different scales. Thus, the label fusion follows the representation consensus across representative dictionaries. However, the representation of target patch in each group is iteratively optimized by using the representative atlas patches in each label-specific dictionary exclusively to match the principal patterns and also using all residual patterns across groups collaboratively to overcome the issue that some groups might be absent of certain variation patterns presented in the target image patch. Promising segmentation results have been achieved in labeling hippocampus on ADNI dataset, as well as basal ganglia and brainstem structures, compared to other counterpart label fusion methods.

Cell-specific Labeling Enzymes for Analysis of Cell–Cell Communication in Continuous Co-culture*

PubMed Central

Tape, Christopher J.; Norrie, Ida C.; Worboys, Jonathan D.; Lim, Lindsay; Lauffenburger, Douglas A.; Jørgensen, Claus

2014-01-01

We report the orthologous screening, engineering, and optimization of amino acid conversion enzymes for cell-specific proteomic labeling. Intracellular endoplasmic-reticulum-anchored Mycobacterium tuberculosis diaminopimelate decarboxylase (DDCM.tub-KDEL) confers cell-specific meso-2,6-diaminopimelate-dependent proliferation to multiple eukaryotic cell types. Optimized lysine racemase (LyrM37-KDEL) supports D-lysine specific proliferation and efficient cell-specific isotopic labeling. When ectopically expressed in discrete cell types, these enzymes confer 90% cell-specific isotopic labeling efficiency after 10 days of co-culture. Moreover, DDCM.tub-KDEL and LyrM37-KDEL facilitate equally high cell-specific labeling fidelity without daily media exchange. Consequently, the reported novel enzyme pairing can be used to study cell-specific signaling in uninterrupted, continuous co-cultures. Demonstrating the importance of increased labeling stability for addressing novel biological questions, we compare the cell-specific phosphoproteome of fibroblasts in direct co-culture with epithelial tumor cells in both interrupted (daily media exchange) and continuous (no media exchange) co-cultures. This analysis identified multiple cell-specific phosphorylation sites specifically regulated in the continuous co-culture. Given their applicability to multiple cell types, continuous co-culture labeling fidelity, and suitability for long-term cell–cell phospho-signaling experiments, we propose DDCM.tub-KDEL and LyrM37-KDEL as excellent enzymes for cell-specific labeling with amino acid precursors. PMID:24820872

Automated bone segmentation from dental CBCT images using patch-based sparse representation and convex optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Li; Gao, Yaozong; Shi, Feng

Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate three-dimensional (3D) models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the poor image quality, including very low signal-to-noise ratio and the widespread image artifacts such as noise, beam hardening, and inhomogeneity, it is challenging to segment the CBCT images. In this paper, the authors present a new automatic segmentation method to address these problems. Methods: To segmentmore » CBCT images, the authors propose a new method for fully automated CBCT segmentation by using patch-based sparse representation to (1) segment bony structures from the soft tissues and (2) further separate the mandible from the maxilla. Specifically, a region-specific registration strategy is first proposed to warp all the atlases to the current testing subject and then a sparse-based label propagation strategy is employed to estimate a patient-specific atlas from all aligned atlases. Finally, the patient-specific atlas is integrated into amaximum a posteriori probability-based convex segmentation framework for accurate segmentation. Results: The proposed method has been evaluated on a dataset with 15 CBCT images. The effectiveness of the proposed region-specific registration strategy and patient-specific atlas has been validated by comparing with the traditional registration strategy and population-based atlas. The experimental results show that the proposed method achieves the best segmentation accuracy by comparison with other state-of-the-art segmentation methods. Conclusions: The authors have proposed a new CBCT segmentation method by using patch-based sparse representation and convex optimization, which can achieve considerably accurate segmentation results in CBCT segmentation based on 15 patients.« less

Incremental Transductive Learning Approaches to Schistosomiasis Vector Classification

NASA Astrophysics Data System (ADS)

Fusco, Terence; Bi, Yaxin; Wang, Haiying; Browne, Fiona

2016-08-01

The key issues pertaining to collection of epidemic disease data for our analysis purposes are that it is a labour intensive, time consuming and expensive process resulting in availability of sparse sample data which we use to develop prediction models. To address this sparse data issue, we present the novel Incremental Transductive methods to circumvent the data collection process by applying previously acquired data to provide consistent, confidence-based labelling alternatives to field survey research. We investigated various reasoning approaches for semi-supervised machine learning including Bayesian models for labelling data. The results show that using the proposed methods, we can label instances of data with a class of vector density at a high level of confidence. By applying the Liberal and Strict Training Approaches, we provide a labelling and classification alternative to standalone algorithms. The methods in this paper are components in the process of reducing the proliferation of the Schistosomiasis disease and its effects.

MRM-Lasso: A Sparse Multiview Feature Selection Method via Low-Rank Analysis.

PubMed

Yang, Wanqi; Gao, Yang; Shi, Yinghuan; Cao, Longbing

2015-11-01

Learning about multiview data involves many applications, such as video understanding, image classification, and social media. However, when the data dimension increases dramatically, it is important but very challenging to remove redundant features in multiview feature selection. In this paper, we propose a novel feature selection algorithm, multiview rank minimization-based Lasso (MRM-Lasso), which jointly utilizes Lasso for sparse feature selection and rank minimization for learning relevant patterns across views. Instead of simply integrating multiple Lasso from view level, we focus on the performance of sample-level (sample significance) and introduce pattern-specific weights into MRM-Lasso. The weights are utilized to measure the contribution of each sample to the labels in the current view. In addition, the latent correlation across different views is successfully captured by learning a low-rank matrix consisting of pattern-specific weights. The alternating direction method of multipliers is applied to optimize the proposed MRM-Lasso. Experiments on four real-life data sets show that features selected by MRM-Lasso have better multiview classification performance than the baselines. Moreover, pattern-specific weights are demonstrated to be significant for learning about multiview data, compared with view-specific weights.

Discriminative Bayesian Dictionary Learning for Classification.

PubMed

Akhtar, Naveed; Shafait, Faisal; Mian, Ajmal

2016-12-01

We propose a Bayesian approach to learn discriminative dictionaries for sparse representation of data. The proposed approach infers probability distributions over the atoms of a discriminative dictionary using a finite approximation of Beta Process. It also computes sets of Bernoulli distributions that associate class labels to the learned dictionary atoms. This association signifies the selection probabilities of the dictionary atoms in the expansion of class-specific data. Furthermore, the non-parametric character of the proposed approach allows it to infer the correct size of the dictionary. We exploit the aforementioned Bernoulli distributions in separately learning a linear classifier. The classifier uses the same hierarchical Bayesian model as the dictionary, which we present along the analytical inference solution for Gibbs sampling. For classification, a test instance is first sparsely encoded over the learned dictionary and the codes are fed to the classifier. We performed experiments for face and action recognition; and object and scene-category classification using five public datasets and compared the results with state-of-the-art discriminative sparse representation approaches. Experiments show that the proposed Bayesian approach consistently outperforms the existing approaches.

Multi-instance multi-label distance metric learning for genome-wide protein function prediction.

PubMed

Xu, Yonghui; Min, Huaqing; Song, Hengjie; Wu, Qingyao

2016-08-01

Multi-instance multi-label (MIML) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with not only multiple instances but also multiple class labels. To find an appropriate MIML learning method for genome-wide protein function prediction, many studies in the literature attempted to optimize objective functions in which dissimilarity between instances is measured using the Euclidean distance. But in many real applications, Euclidean distance may be unable to capture the intrinsic similarity/dissimilarity in feature space and label space. Unlike other previous approaches, in this paper, we propose to learn a multi-instance multi-label distance metric learning framework (MIMLDML) for genome-wide protein function prediction. Specifically, we learn a Mahalanobis distance to preserve and utilize the intrinsic geometric information of both feature space and label space for MIML learning. In addition, we try to deal with the sparsely labeled data by giving weight to the labeled data. Extensive experiments on seven real-world organisms covering the biological three-domain system (i.e., archaea, bacteria, and eukaryote; Woese et al., 1990) show that the MIMLDML algorithm is superior to most state-of-the-art MIML learning algorithms. Copyright © 2016 Elsevier Ltd. All rights reserved.

The directed self-assembly for the surface patterning by electron beam II

NASA Astrophysics Data System (ADS)

Nakagawa, Sachiko T.

2015-03-01

When a low-energy electron beam (EB) or a low-energy ion beam (IB) irradiates a crystal of zincblende (ZnS)-type as crystalline Si (c-Si), a very similar {311} planar defect is often observed. Here, we used a molecular dynamics simulation for a c-Si that included uniformly distributed Frenkel-pairs, assuming a wide beam and sparse distribution of defects caused by each EB. We observed the formation of ? linear defects, which agglomerate to form planar defects labeled with the Miller index {311} as well as the case of IB irradiation. These were identified by a crystallographic analysis called pixel mapping (PM) method. The PM had suggested that self-interstitial atoms may be stabilized on a specific frame of a lattice made of invisible metastable sites in the ZnS-type crystal. This agglomeration appears as {311} planar defects. It was possible at a much higher temperature than room temperature,for example, at 1000 K. This implies that whatever disturbance may bring many SIAs in a ZnS-type crystal, elevated lattice vibration promotes self-organization of the SIAs to form {311} planar defects according to the frame of metastable lattice as is guided by a chart presented by crystallography.

46 CFR 162.039-4 - Marine type label.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 6 2011-10-01 2011-10-01 false Marine type label. 162.039-4 Section 162.039-4 Shipping...: SPECIFICATIONS AND APPROVAL ENGINEERING EQUIPMENT Extinguishers, Fire, Semiportable, Marine Type § 162.039-4 Marine type label. (a) In addition to all other marking, every semiportable extinguisher shall bear a...

46 CFR 162.039-4 - Marine type label.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 6 2013-10-01 2013-10-01 false Marine type label. 162.039-4 Section 162.039-4 Shipping...: SPECIFICATIONS AND APPROVAL ENGINEERING EQUIPMENT Extinguishers, Fire, Semiportable, Marine Type § 162.039-4 Marine type label. (a) In addition to all other marking, every semiportable extinguisher shall bear a...

46 CFR 162.039-4 - Marine type label.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 6 2010-10-01 2010-10-01 false Marine type label. 162.039-4 Section 162.039-4 Shipping...: SPECIFICATIONS AND APPROVAL ENGINEERING EQUIPMENT Extinguishers, Fire, Semiportable, Marine Type § 162.039-4 Marine type label. (a) In addition to all other marking, every semiportable extinguisher shall bear a...

46 CFR 162.039-4 - Marine type label.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 6 2014-10-01 2014-10-01 false Marine type label. 162.039-4 Section 162.039-4 Shipping...: SPECIFICATIONS AND APPROVAL ENGINEERING EQUIPMENT Extinguishers, Fire, Semiportable, Marine Type § 162.039-4 Marine type label. (a) In addition to all other marking, every semiportable extinguisher shall bear a...

46 CFR 162.039-4 - Marine type label.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 6 2012-10-01 2012-10-01 false Marine type label. 162.039-4 Section 162.039-4 Shipping...: SPECIFICATIONS AND APPROVAL ENGINEERING EQUIPMENT Extinguishers, Fire, Semiportable, Marine Type § 162.039-4 Marine type label. (a) In addition to all other marking, every semiportable extinguisher shall bear a...

Ultrastructure of the central subnucleus of the nucleus tractus solitarii and the esophageal afferent terminals in the rat.

PubMed

Hayakawa, Tetsu; Takanaga, Akinori; Tanaka, Koichi; Maeda, Seishi; Seki, Makoto

2003-03-01

The central subnucleus of the nucleus tractus solitarii (ceNTS) receives afferent projections from the esophageal wall and projects to the nucleus ambiguus, thus serving as a relay nucleus for peristalsis of the esophagus. Here we examine the synaptic organization of the ceNTS, and its esophageal afferents by using transganglionic anterograde transport of cholera toxin-conjugated horseradish peroxidase (CT-HRP). When CT-HRP was injected into the subdiaphragmatic esophagus, many anterogradely labeled terminals were found only in the ceNTS. The ceNTS was composed of round or oval-shaped, small neurons (14.7x8.7 micro m) containing sparse organelles and an irregularly shaped nucleus. The average number of axosomatic terminals was only 1.3 per section cut through the nucleolus. Most of them (92%) contained round vesicles and formed asymmetric synaptic contacts (Gray's type I), and a few (8%) contained pleomorphic vesicles and formed symmetric synaptic contacts (Gray's type II). All anterogradely labeled terminals contacted dendrites but not the neuronal somata. The labeled terminals were large (2.55+/-0.07 micro m) and exclusively Gray's type I. More than half of them (60%) contacted small dendrites (less than 1 micro m in diameter), and contained dense-cored vesicles. More than 40% of the labeled terminals contacted two to four dendrites, thus forming a synaptic glomerulus. Sometimes a labeled terminal that contacted an unlabeled terminal by an adherent junction was found within the glomerulus. The large terminals and these complex synaptic relations appeared to characterize the esophageal afferent projections in the ceNTS.

An approach for automatic classification of grouper vocalizations with passive acoustic monitoring.

PubMed

Ibrahim, Ali K; Chérubin, Laurent M; Zhuang, Hanqi; Schärer Umpierre, Michelle T; Dalgleish, Fraser; Erdol, Nurgun; Ouyang, B; Dalgleish, A

2018-02-01

Grouper, a family of marine fishes, produce distinct vocalizations associated with their reproductive behavior during spawning aggregation. These low frequencies sounds (50-350 Hz) consist of a series of pulses repeated at a variable rate. In this paper, an approach is presented for automatic classification of grouper vocalizations from ambient sounds recorded in situ with fixed hydrophones based on weighted features and sparse classifier. Group sounds were labeled initially by humans for training and testing various feature extraction and classification methods. In the feature extraction phase, four types of features were used to extract features of sounds produced by groupers. Once the sound features were extracted, three types of representative classifiers were applied to categorize the species that produced these sounds. Experimental results showed that the overall percentage of identification using the best combination of the selected feature extractor weighted mel frequency cepstral coefficients and sparse classifier achieved 82.7% accuracy. The proposed algorithm has been implemented in an autonomous platform (wave glider) for real-time detection and classification of group vocalizations.

46 CFR 162.028-7 - Procedure for listing and labeling.

Code of Federal Regulations, 2010 CFR

2010-10-01

... and motorboats may make application for listing and labeling as a marine-type portable fire..., AND MATERIALS: SPECIFICATIONS AND APPROVAL ENGINEERING EQUIPMENT Extinguishers, Fire, Portable, Marine Type § 162.028-7 Procedure for listing and labeling. (a) Manufacturers having a marine-type portable...

[Analysis of vegetation spatial and temporal variations in Qinghai Province based on remote sensing].

PubMed

Wang, Li-wen; Wei, Ya-xing; Niu, Zheng

2008-06-01

1 km MODIS NDVI time series data combining with decision tree classification, supervised classification and unsupervised classification was used to classify land cover type of Qinghai Province into 14 classes. In our classification system, sparse grassland and sparse shrub were emphasized, and their spatial distribution locations were labeled. From digital elevation model (DEM) of Qinghai Province, five elevation belts were achieved, and we utilized geographic information system (GIS) software to analyze vegetation cover variation on different elevation belts. Our research result shows that vegetation cover in Qinghai Province has been improved in recent five years. Vegetation cover area increases from 370047 km2 in 2001 to 374576 km2 in 2006, and vegetation cover rate increases by 0.63%. Among five grade elevation belts, vegetation cover ratio of high mountain belt is the highest (67.92%). The area of middle density grassland in high mountain belt is the largest, of which area is 94 003 km2. Increased area of dense grassland in high mountain belt is the greatest (1280 km2). During five years, the biggest variation is the conversion from sparse grassland to middle density grassland in high mountain belt, of which area is 15931 km2.

Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less

Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

DOE PAGES

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; ...

2014-10-01

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less

Sparsely Ionizing Diagnostic and Natural Background Radiations are Likely Preventing Cancer and Other Genomic-Instability-Associated Diseases

PubMed Central

Scott, Bobby R.; Di Palma, Jennifer

2007-01-01

Routine diagnostic X-rays (e.g., chest X-rays, mammograms, computed tomography scans) and routine diagnostic nuclear medicine procedures using sparsely ionizing radiation forms (e.g., beta and gamma radiations) stimulate the removal of precancerous neo-plastically transformed and other genomically unstable cells from the body (medical radiation hormesis). The indicated radiation hormesis arises because radiation doses above an individual-specific stochastic threshold activate a system of cooperative protective processes that include high-fidelity DNA repair/apoptosis (presumed p53 related), an auxiliary apoptosis process (PAM process) that is presumed p53-independent, and stimulated immunity. These forms of induced protection are called adapted protection because they are associated with the radiation adaptive response. Diagnostic X-ray sources, other sources of sparsely ionizing radiation used in nuclear medicine diagnostic procedures, as well as radioisotope-labeled immunoglobulins could be used in conjunction with apopto-sis-sensitizing agents (e.g., the natural phenolic compound resveratrol) in curing existing cancer via low-dose fractionated or low-dose, low-dose-rate therapy (therapeutic radiation hormesis). Evidence is provided to support the existence of both therapeutic (curing existing cancer) and medical (cancer prevention) radiation hormesis. Evidence is also provided demonstrating that exposure to environmental sparsely ionizing radiations, such as gamma rays, protect from cancer occurrence and the occurrence of other diseases via inducing adapted protection (environmental radiation hormesis). PMID:18648608

46 CFR 162.028-4 - Marine type label.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 6 2013-10-01 2013-10-01 false Marine type label. 162.028-4 Section 162.028-4 Shipping...: SPECIFICATIONS AND APPROVAL ENGINEERING EQUIPMENT Extinguishers, Fire, Portable, Marine Type § 162.028-4 Marine... containing the “marine type” listing manifest issued by a recognized laboratory. This label will include the...

46 CFR 162.028-4 - Marine type label.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 6 2011-10-01 2011-10-01 false Marine type label. 162.028-4 Section 162.028-4 Shipping...: SPECIFICATIONS AND APPROVAL ENGINEERING EQUIPMENT Extinguishers, Fire, Portable, Marine Type § 162.028-4 Marine... containing the “marine type” listing manifest issued by a recognized laboratory. This label will include the...

46 CFR 162.028-4 - Marine type label.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 6 2012-10-01 2012-10-01 false Marine type label. 162.028-4 Section 162.028-4 Shipping...: SPECIFICATIONS AND APPROVAL ENGINEERING EQUIPMENT Extinguishers, Fire, Portable, Marine Type § 162.028-4 Marine... containing the “marine type” listing manifest issued by a recognized laboratory. This label will include the...

46 CFR 162.028-4 - Marine type label.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 6 2014-10-01 2014-10-01 false Marine type label. 162.028-4 Section 162.028-4 Shipping...: SPECIFICATIONS AND APPROVAL ENGINEERING EQUIPMENT Extinguishers, Fire, Portable, Marine Type § 162.028-4 Marine... containing the “marine type” listing manifest issued by a recognized laboratory. This label will include the...

46 CFR 162.028-4 - Marine type label.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 6 2010-10-01 2010-10-01 false Marine type label. 162.028-4 Section 162.028-4 Shipping...: SPECIFICATIONS AND APPROVAL ENGINEERING EQUIPMENT Extinguishers, Fire, Portable, Marine Type § 162.028-4 Marine... containing the “marine type” listing manifest issued by a recognized laboratory. This label will include the...

Estimating patient-specific and anatomically correct reference model for craniomaxillofacial deformity via sparse representation

PubMed Central

Wang, Li; Ren, Yi; Gao, Yaozong; Tang, Zhen; Chen, Ken-Chung; Li, Jianfu; Shen, Steve G. F.; Yan, Jin; Lee, Philip K. M.; Chow, Ben; Xia, James J.; Shen, Dinggang

2015-01-01

Purpose: A significant number of patients suffer from craniomaxillofacial (CMF) deformity and require CMF surgery in the United States. The success of CMF surgery depends on not only the surgical techniques but also an accurate surgical planning. However, surgical planning for CMF surgery is challenging due to the absence of a patient-specific reference model. Currently, the outcome of the surgery is often subjective and highly dependent on surgeon’s experience. In this paper, the authors present an automatic method to estimate an anatomically correct reference shape of jaws for orthognathic surgery, a common type of CMF surgery. Methods: To estimate a patient-specific jaw reference model, the authors use a data-driven method based on sparse shape composition. Given a dictionary of normal subjects, the authors first use the sparse representation to represent the midface of a patient by the midfaces of the normal subjects in the dictionary. Then, the derived sparse coefficients are used to reconstruct a patient-specific reference jaw shape. Results: The authors have validated the proposed method on both synthetic and real patient data. Experimental results show that the authors’ method can effectively reconstruct the normal shape of jaw for patients. Conclusions: The authors have presented a novel method to automatically estimate a patient-specific reference model for the patient suffering from CMF deformity. PMID:26429255

Incidental Detection of Type B2 Thymoma on 68Ga-Labeled Prostate-Specific Membrane Antigen PET/CT Imaging.

PubMed

Krishnaraju, Venkata Subramanian; Basher, Rajender Kumar; Singh, Harmandeep; Singh, Shrawan Kumar; Bal, Amanjit; Mittal, Bhagwant Rai

2018-05-01

Ga-labeled prostate-specific membrane antigen is a novel radiotracer for imaging of prostate cancer. We report a hormonally treated patient with prostate carcinoma, presenting with lower urinary tract symptoms and rising prostate-specific antigen levels, who underwent Ga-labeled prostate-specific membrane antigen PET/CT for suspected recurrence. No tracer avid lesion was noted in the prostate gland and locoregional area. However, intense tracer avid heterogeneously enhancing soft tissue lesion with cystic areas and coarse calcifications was seen in the anterior mediastinum. PET/CT-guided biopsy from the mediastenal lesion revealed type B2 thymoma.

Heterogeneous expression of Ca(2+) handling proteins in rabbit sinoatrial node.

PubMed

Musa, Hanny; Lei, Ming; Honjo, Hauro; Jones, Sandra A; Dobrzynski, Halina; Lancaster, Mathew K; Takagishi, Yoshiko; Henderson, Zaineb; Kodama, Itsuo; Boyett, Mark R

2002-03-01

We investigated the densities of the L-type Ca(2+) current, i(Ca,L), and various Ca(2+) handling proteins in rabbit sinoatrial (SA) node. The density of i(Ca,L), recorded with the whole-cell patch-clamp technique, varied widely in sinoatrial node cells. The density of i(Ca,L) was significantly (p<0.001) correlated with cell capacitance (measure of cell size) and the density was greater in larger cells (likely to be from the periphery of the SA node) than in smaller cells (likely to be from the center of the SA node). Immunocytochemical labeling of the L-type Ca(2+) channel, Na(+)-Ca(2+) exchanger, sarcoplasmic reticulum Ca(2+) release channel (RYR2), and sarcoplasmic reticulum Ca(2+) pump (SERCA2) also varied widely in SA node cells. In all cases there was significantly (p<0.05) denser labeling of cells from the periphery of the SA node than of cells from the center. In contrast, immunocytochemical labeling of the Na(+)-K(+) pump was similar in peripheral and central cells. We conclude that Ca(2+) handling proteins are sparse and poorly organized in the center of the SA node (normally the leading pacemaker site), whereas they are more abundant in the periphery (at the border of the SA node with the surrounding atrial muscle).

Simultaneous neuron- and astrocyte-specific fluorescent marking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schulze, Wiebke; Hayata-Takano, Atsuko; Kamo, Toshihiko

2015-03-27

Systematic and simultaneous analysis of multiple cell types in the brain is becoming important, but such tools have not yet been adequately developed. Here, we aimed to generate a method for the specific fluorescent labeling of neurons and astrocytes, two major cell types in the brain, and we have developed lentiviral vectors to express the red fluorescent protein tdTomato in neurons and the enhanced green fluorescent protein (EGFP) in astrocytes. Importantly, both fluorescent proteins are fused to histone 2B protein (H2B) to confer nuclear localization to distinguish between single cells. We also constructed several expression constructs, including a tandem alignmentmore » of the neuron- and astrocyte-expression cassettes for simultaneous labeling. Introducing these vectors and constructs in vitro and in vivo resulted in cell type-specific and nuclear-localized fluorescence signals enabling easy detection and distinguishability of neurons and astrocytes. This tool is expected to be utilized for the simultaneous analysis of changes in neurons and astrocytes in healthy and diseased brains. - Highlights: • We develop a method for the specific fluorescent labeling of neurons and astrocytes. • Neuron-specific labeling is achieved using Scg10 and synapsin promoters. • Astrocyte-specific labeling is generated using the minimal GFAP promoter. • Nuclear localization of fluorescent proteins is achieved with histone 2B protein.« less

Porosity estimation by semi-supervised learning with sparsely available labeled samples

NASA Astrophysics Data System (ADS)

Lima, Luiz Alberto; Görnitz, Nico; Varella, Luiz Eduardo; Vellasco, Marley; Müller, Klaus-Robert; Nakajima, Shinichi

2017-09-01

This paper addresses the porosity estimation problem from seismic impedance volumes and porosity samples located in a small group of exploratory wells. Regression methods, trained on the impedance as inputs and the porosity as output labels, generally suffer from extremely expensive (and hence sparsely available) porosity samples. To optimally make use of the valuable porosity data, a semi-supervised machine learning method was proposed, Transductive Conditional Random Field Regression (TCRFR), showing good performance (Görnitz et al., 2017). TCRFR, however, still requires more labeled data than those usually available, which creates a gap when applying the method to the porosity estimation problem in realistic situations. In this paper, we aim to fill this gap by introducing two graph-based preprocessing techniques, which adapt the original TCRFR for extremely weakly supervised scenarios. Our new method outperforms the previous automatic estimation methods on synthetic data and provides a comparable result to the manual labored, time-consuming geostatistics approach on real data, proving its potential as a practical industrial tool.

Subject-based discriminative sparse representation model for detection of concealed information.

PubMed

Akhavan, Amir; Moradi, Mohammad Hassan; Vand, Safa Rafiei

2017-05-01

The use of machine learning approaches in concealed information test (CIT) plays a key role in the progress of this neurophysiological field. In this paper, we presented a new machine learning method for CIT in which each subject is considered independent of the others. The main goal of this study is to adapt the discriminative sparse models to be applicable for subject-based concealed information test. In order to provide sufficient discriminability between guilty and innocent subjects, we introduced a novel discriminative sparse representation model and its appropriate learning methods. For evaluation of the method forty-four subjects participated in a mock crime scenario and their EEG data were recorded. As the model input, in this study the recurrence plot features were extracted from single trial data of different stimuli. Then the extracted feature vectors were reduced using statistical dependency method. The reduced feature vector went through the proposed subject-based sparse model in which the discrimination power of sparse code and reconstruction error were applied simultaneously. Experimental results showed that the proposed approach achieved better performance than other competing discriminative sparse models. The classification accuracy, sensitivity and specificity of the presented sparsity-based method were about 93%, 91% and 95% respectively. Using the EEG data of a single subject in response to different stimuli types and with the aid of the proposed discriminative sparse representation model, one can distinguish guilty subjects from innocent ones. Indeed, this property eliminates the necessity of several subject EEG data in model learning and decision making for a specific subject. Copyright © 2017 Elsevier B.V. All rights reserved.

Multiple Click-Selective tRNA Synthetases Expand Mammalian Cell-Specific Proteomics.

PubMed

Yang, Andrew C; du Bois, Haley; Olsson, Niclas; Gate, David; Lehallier, Benoit; Berdnik, Daniela; Brewer, Kyle D; Bertozzi, Carolyn R; Elias, Joshua E; Wyss-Coray, Tony

2018-06-13

Bioorthogonal tools enable cell-type-specific proteomics, a prerequisite to understanding biological processes in multicellular organisms. Here we report two engineered aminoacyl-tRNA synthetases for mammalian bioorthogonal labeling: a tyrosyl ( ScTyr Y43G ) and a phenylalanyl ( MmPhe T413G ) tRNA synthetase that incorporate azide-bearing noncanonical amino acids specifically into the nascent proteomes of host cells. Azide-labeled proteins are chemoselectively tagged via azide-alkyne cycloadditions with fluorophores for imaging or affinity resins for mass spectrometric characterization. Both mutant synthetases label human, hamster, and mouse cell line proteins and selectively activate their azido-bearing amino acids over 10-fold above the canonical. ScTyr Y43G and MmPhe T413G label overlapping but distinct proteomes in human cell lines, with broader proteome coverage upon their coexpression. In mice, ScTyr Y43G and MmPhe T413G label the melanoma tumor proteome and plasma secretome. This work furnishes new tools for mammalian residue-specific bioorthogonal chemistry, and enables more robust and comprehensive cell-type-specific proteomics in live mammals.

Jacalin and peanut agglutinin (PNA) bindings in the taste bud cells of the rat: new reliable markers for type IV cells of the rat taste buds.

PubMed

Taniguchi, Ryo; Shi, Lei; Fujii, Masae; Ueda, Katsura; Honma, Shiho; Wakisaka, Satoshi

2005-12-01

Lectin histochemistry of Jacalin (Artocarpus integrifolia) and peanut agglutinin (PNA), specific lectins for galactosyl (beta-1, 3) N-acetylgalactosamine (galactosyl (beta-1, 3) GalNAc), was applied to the gustatory epithelium of the adult rat. In the ordinary lingual epithelium, Jacalin and PNA labeled the cell membrane from the basal to granular cell layer. They also bound membranes of rounded-cells at the basal portion of taste buds, but the number of PNA labeled cells was smaller than that of Jacalin labeled cells. There was no apparent difference in the binding patterns of Jacalin and PNA among the taste buds of the lingual papillae and those of the palatal epithelium. Occasionally, a few spindle-shaped cells were labeled with Jacalin, but not with PNA. Double labeling of Jacalin and alpha-gustducin, a specific marker for type II cells, revealed that Jacalin-labeled spindle-shaped taste cells were immunonegative for alpha-gustducin. Spindle-shaped cells expressing protein gene product 9.5 (PGP 9.5) immunoreactivity lacked Jacalin labeling. During the development of taste buds in circumvallate papillae, the binding pattern of Jacalin became almost identical from postnatal day 5. The present results indicate that rounded cells at the basal portion of the taste buds cells (type IV cells) bind to Jacalin and PNA, and these lectins are specific markers for type IV cells of the rat taste cells.

16 CFR 309.21 - Labeling requirements for used covered vehicles.

Code of Federal Regulations, 2010 CFR

2010-01-01

... visible surface of each such vehicle. (b) Layout. Figure 6 of appendix A is the prototype label that... consistent with the prototype label. The label required by this section is one-sided and rectangular in shape... label. Specific type sizes and faces to be used are indicated on the prototype label (Figure 6 of...

Semi-Supervised Sparse Representation Based Classification for Face Recognition With Insufficient Labeled Samples

NASA Astrophysics Data System (ADS)

Gao, Yuan; Ma, Jiayi; Yuille, Alan L.

2017-05-01

This paper addresses the problem of face recognition when there is only few, or even only a single, labeled examples of the face that we wish to recognize. Moreover, these examples are typically corrupted by nuisance variables, both linear (i.e., additive nuisance variables such as bad lighting, wearing of glasses) and non-linear (i.e., non-additive pixel-wise nuisance variables such as expression changes). The small number of labeled examples means that it is hard to remove these nuisance variables between the training and testing faces to obtain good recognition performance. To address the problem we propose a method called Semi-Supervised Sparse Representation based Classification (S$^3$RC). This is based on recent work on sparsity where faces are represented in terms of two dictionaries: a gallery dictionary consisting of one or more examples of each person, and a variation dictionary representing linear nuisance variables (e.g., different lighting conditions, different glasses). The main idea is that (i) we use the variation dictionary to characterize the linear nuisance variables via the sparsity framework, then (ii) prototype face images are estimated as a gallery dictionary via a Gaussian Mixture Model (GMM), with mixed labeled and unlabeled samples in a semi-supervised manner, to deal with the non-linear nuisance variations between labeled and unlabeled samples. We have done experiments with insufficient labeled samples, even when there is only a single labeled sample per person. Our results on the AR, Multi-PIE, CAS-PEAL, and LFW databases demonstrate that the proposed method is able to deliver significantly improved performance over existing methods.

Classification of mislabelled microarrays using robust sparse logistic regression.

PubMed

Bootkrajang, Jakramate; Kabán, Ata

2013-04-01

Previous studies reported that labelling errors are not uncommon in microarray datasets. In such cases, the training set may become misleading, and the ability of classifiers to make reliable inferences from the data is compromised. Yet, few methods are currently available in the bioinformatics literature to deal with this problem. The few existing methods focus on data cleansing alone, without reference to classification, and their performance crucially depends on some tuning parameters. In this article, we develop a new method to detect mislabelled arrays simultaneously with learning a sparse logistic regression classifier. Our method may be seen as a label-noise robust extension of the well-known and successful Bayesian logistic regression classifier. To account for possible mislabelling, we formulate a label-flipping process as part of the classifier. The regularization parameter is automatically set using Bayesian regularization, which not only saves the computation time that cross-validation would take, but also eliminates any unwanted effects of label noise when setting the regularization parameter. Extensive experiments with both synthetic data and real microarray datasets demonstrate that our approach is able to counter the bad effects of labelling errors in terms of predictive performance, it is effective at identifying marker genes and simultaneously it detects mislabelled arrays to high accuracy. The code is available from http://cs.bham.ac.uk/∼jxb008. Supplementary data are available at Bioinformatics online.

Differential co-localization with choline acetyltransferase in nervus terminalis suggests functional differences for GnRH isoforms in bonnethead sharks (Sphyrna tiburo)

PubMed Central

Moeller, John F.; Meredith, Michael

2010-01-01

The nervus terminalis (NT) is a vertebrate cranial nerve whose function in adults is unknown. In bonnethead sharks the nerve is anatomically independent of the olfactory system, with two major cell populations within one or more ganglia along its exposed length. Most cells are immunoreactive for either gonadotropin-releasing hormone (GnRH) or RFamide-like peptides. To define further the cell populations and connectivity, we used double-label immuno-cytochemistry with antisera to different isoforms of GnRH and to choline acetyltransferase (ChAT). The labeling patterns of two GnRH antisera revealed different populations of GnRH immunoreactive (ir) cell-profiles in the NT ganglion. One antiserum labeled a large group of cells and fibers, which likely contain mammalian GnRH (GnRH-I) as described in previous studies, and which were ChAT immunoreactive. The other antiserum labeled large club-like structures, which were anuclear, and a sparse number of fibers, but with no clear labeling of cell bodies in the ganglion. These club structures were choline acetyltrasferase (ChAT) negative, and preabsorption control tests suggest they may contain chicken-GnRH-II (GnRH-II) or dogfish GnRH. The second major NT ganglion cell-type was immunoreactive for RF-amides, which regulate GnRH release in other vertebrates, and may provide an intraganglionic influence on GnRH release. The immunocytochemical and anatomical differences between the two GnRH immunoreactive profile types indicate possible functional differences for these isoforms in the NT. The club-like structures may be sites of GnRH release into the general circulation since these structures were observed near blood vessels and resembled structures seen in the median eminence of rats. PMID:20950589

Differential co-localization with choline acetyltransferase in nervus terminalis suggests functional differences for GnRH isoforms in bonnethead sharks (Sphyrna tiburo).

PubMed

Moeller, John F; Meredith, Michael

2010-12-17

The nervus terminalis (NT) is a vertebrate cranial nerve whose function in adults is unknown. In bonnethead sharks, the nerve is anatomically independent of the olfactory system, with two major cell populations within one or more ganglia along its exposed length. Most cells are immunoreactive for either gonadotropin-releasing hormone (GnRH) or RF-amide-like peptides. To define further the cell populations and connectivity, we used double-label immunocytochemistry with antisera to different isoforms of GnRH and to choline acetyltransferase (ChAT). The labeling patterns of two GnRH antisera revealed different populations of GnRH-immunoreactive (ir) cell profiles in the NT ganglion. One antiserum labeled a large group of cells and fibers, which likely contain mammalian GnRH (GnRH-I) as described in previous studies and which were ChAT immunoreactive. The other antiserum labeled large club-like structures, which were anuclear, and a sparse number of fibers, but with no clear labeling of cell bodies in the ganglion. These club structures were choline acetyltrasferase (ChAT)-negative, and preabsorption control tests suggest they may contain chicken-GnRH-II (GnRH-II) or dogfish GnRH. The second major NT ganglion cell-type was immunoreactive for RF-amides, which regulate GnRH release in other vertebrates, and may provide an intraganglionic influence on GnRH release. The immunocytochemical and anatomical differences between the two GnRH-immunoreactive profile types indicate possible functional differences for these isoforms in the NT. The club-like structures may be sites of GnRH release into the general circulation since these structures were observed near blood vessels and resembled structures seen in the median eminence of rats. Copyright © 2010 Elsevier B.V. All rights reserved.

Rapid and accurate peripheral nerve detection using multipoint Raman imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kumamoto, Yasuaki; Minamikawa, Takeo; Kawamura, Akinori; Matsumura, Junichi; Tsuda, Yuichiro; Ukon, Juichiro; Harada, Yoshinori; Tanaka, Hideo; Takamatsu, Tetsuro

2017-02-01

Nerve-sparing surgery is essential to avoid functional deficits of the limbs and organs. Raman scattering, a label-free, minimally invasive, and accurate modality, is one of the best candidate technologies to detect nerves for nerve-sparing surgery. However, Raman scattering imaging is too time-consuming to be employed in surgery. Here we present a rapid and accurate nerve visualization method using a multipoint Raman imaging technique that has enabled simultaneous spectra measurement from different locations (n=32) of a sample. Five sec is sufficient for measuring n=32 spectra with good S/N from a given tissue. Principal component regression discriminant analysis discriminated spectra obtained from peripheral nerves (n=863 from n=161 myelinated nerves) and connective tissue (n=828 from n=121 tendons) with sensitivity and specificity of 88.3% and 94.8%, respectively. To compensate the spatial information of a multipoint-Raman-derived tissue discrimination image that is too sparse to visualize nerve arrangement, we used morphological information obtained from a bright-field image. When merged with the sparse tissue discrimination image, a morphological image of a sample shows what portion of Raman measurement points in arbitrary structure is determined as nerve. Setting a nerve detection criterion on the portion of "nerve" points in the structure as 40% or more, myelinated nerves (n=161) and tendons (n=121) were discriminated with sensitivity and specificity of 97.5%. The presented technique utilizing a sparse multipoint Raman image and a bright-field image has enabled rapid, safe, and accurate detection of peripheral nerves.

A sparse differential clustering algorithm for tracing cell type changes via single-cell RNA-sequencing data

PubMed Central

Barron, Martin; Zhang, Siyuan

2018-01-01

Abstract Cell types in cell populations change as the condition changes: some cell types die out, new cell types may emerge and surviving cell types evolve to adapt to the new condition. Using single-cell RNA-sequencing data that measure the gene expression of cells before and after the condition change, we propose an algorithm, SparseDC, which identifies cell types, traces their changes across conditions and identifies genes which are marker genes for these changes. By solving a unified optimization problem, SparseDC completes all three tasks simultaneously. SparseDC is highly computationally efficient and demonstrates its accuracy on both simulated and real data. PMID:29140455

Characterizing human activity induced impulse and slip-pulse excitations through structural vibration

NASA Astrophysics Data System (ADS)

Pan, Shijia; Mirshekari, Mostafa; Fagert, Jonathon; Ramirez, Ceferino Gabriel; Chung, Albert Jin; Hu, Chih Chi; Shen, John Paul; Zhang, Pei; Noh, Hae Young

2018-02-01

Many human activities induce excitations on ambient structures with various objects, causing the structures to vibrate. Accurate vibration excitation source detection and characterization enable human activity information inference, hence allowing human activity monitoring for various smart building applications. By utilizing structural vibrations, we can achieve sparse and non-intrusive sensing, unlike pressure- and vision-based methods. Many approaches have been presented on vibration-based source characterization, and they often either focus on one excitation type or have limited performance due to the dispersion and attenuation effects of the structures. In this paper, we present our method to characterize two main types of excitations induced by human activities (impulse and slip-pulse) on multiple structures. By understanding the physical properties of waves and their propagation, the system can achieve accurate excitation tracking on different structures without large-scale labeled training data. Specifically, our algorithm takes properties of surface waves generated by impulse and of body waves generated by slip-pulse into account to handle the dispersion and attenuation effects when different types of excitations happen on various structures. We then evaluate the algorithm through multiple scenarios. Our method achieves up to a six times improvement in impulse localization accuracy and a three times improvement in slip-pulse trajectory length estimation compared to existing methods that do not take wave properties into account.

An immunohistochemical study of the inflammatory infiltrate associated with nasal carcinoma in dogs and cats.

PubMed

Vanherberghen, M; Day, M J; Delvaux, F; Gabriel, A; Clercx, C; Peeters, D

2009-07-01

The aims of this study were to characterize the inflammatory infiltrate associated with nasal carcinoma in dogs and cats and to determine whether this differed between the two species or with different types of carcinoma. Sections from fixed tissue biopsy samples of intranasal carcinoma from 31 dogs and six cats were labelled immunohistochemically to detect expression of the T-lymphocyte marker CD3, class II molecules of the major histocompatibility complex (MHC II), the myelomonocytic antigen MAC387 and immunoglobulin (Ig) G, IgA and IgM within the cytoplasm of plasma cells. All canine carcinomas were heavily infiltrated by MAC387(+) neutrophils, with smaller numbers of MAC387(+) macrophages. T cells were particularly prominent in the infiltrate associated with transitional carcinoma, and in such tumours were frequently mixed with MHC II(+) cells having macrophage or dendritic cell morphology. IgG(+) and IgA(+) plasma cells were detected at the peripheral margins of all types of canine carcinoma. In contrast, feline intranasal carcinoma was invariably associated with a marked infiltration of CD3(+) T cells. The feline tumour infiltrates contained sparse neutrophils and macrophages and few IgG(+) and IgA(+) plasma cells. These findings suggest that qualitatively different immune responses are induced in response to specific types of canine intranasal carcinoma, and that the canine and feline immune response to these neoplasms is also distinct.

Change detection in Arctic satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

NASA Astrophysics Data System (ADS)

Moody, Daniela I.; Wilson, Cathy J.; Rowland, Joel C.; Altmann, Garrett L.

2015-06-01

Advanced pattern recognition and computer vision algorithms are of great interest for landscape characterization, change detection, and change monitoring in satellite imagery, in support of global climate change science and modeling. We present results from an ongoing effort to extend neuroscience-inspired models for feature extraction to the environmental sciences, and we demonstrate our work using Worldview-2 multispectral satellite imagery. We use a Hebbian learning rule to derive multispectral, multiresolution dictionaries directly from regional satellite normalized band difference index data. These feature dictionaries are used to build sparse scene representations, from which we automatically generate land cover labels via our CoSA algorithm: Clustering of Sparse Approximations. These data adaptive feature dictionaries use joint spectral and spatial textural characteristics to help separate geologic, vegetative, and hydrologic features. Land cover labels are estimated in example Worldview-2 satellite images of Barrow, Alaska, taken at two different times, and are used to detect and discuss seasonal surface changes. Our results suggest that an approach that learns from both spectral and spatial features is promising for practical pattern recognition problems in high resolution satellite imagery.

Labelling and targeted ablation of specific bipolar cell types in the zebrafish retina

PubMed Central

2009-01-01

Background Development of a functional retina depends on regulated differentiation of several types of neurons and generation of a highly complex network between the different types of neurons. In addition, each type of retinal neuron includes several distinct morphological types. Very little is known about the mechanisms responsible for generating this diversity of retinal neurons, which may also display specific patterns of regional distribution. Results In a screen in zebrafish, using a trapping vector carrying an engineered yeast Gal4 transcription activator and a UAS:eGFP reporter cassette, we have identified two transgenic lines of zebrafish co-expressing eGFP and Gal4 in specific subsets of retinal bipolar cells. The eGFP-labelling facilitated analysis of axon terminals within the inner plexiform layer of the adult retina and showed that the fluorescent bipolar cells correspond to previously defined morphological types. Strong regional restriction of eGFP-positive bipolar cells to the central part of the retina surrounding the optic nerve was observed in adult zebrafish. Furthermore, we achieved specific ablation of the labelled bipolar cells in 5 days old larvae, using a bacterial nitroreductase gene under Gal4-UAS control in combination with the prodrug metronidazole. Following prodrug treatment, nitroreductase expressing bipolar cells were efficiently ablated without affecting surrounding retina architecture, and recovery occurred within a few days due to increased generation of new bipolar cells. Conclusion This report shows that enhancer trapping can be applied to label distinct morphological types of bipolar cells in the zebrafish retina. The genetic labelling of these cells yielded co-expression of a modified Gal4 transcription activator and the fluorescent marker eGFP. Our work also demonstrates the potential utility of the Gal4-UAS system for induction of other transgenes, including a bacterial nitroreductase fusion gene, which can facilitate analysis of bipolar cell differentiation and how the retina recovers from specific ablation of these cells. PMID:19712466

Self-Taught Learning Based on Sparse Autoencoder for E-Nose in Wound Infection Detection

PubMed Central

He, Peilin; Jia, Pengfei; Qiao, Siqi; Duan, Shukai

2017-01-01

For an electronic nose (E-nose) in wound infection distinguishing, traditional learning methods have always needed large quantities of labeled wound infection samples, which are both limited and expensive; thus, we introduce self-taught learning combined with sparse autoencoder and radial basis function (RBF) into the field. Self-taught learning is a kind of transfer learning that can transfer knowledge from other fields to target fields, can solve such problems that labeled data (target fields) and unlabeled data (other fields) do not share the same class labels, even if they are from entirely different distribution. In our paper, we obtain numerous cheap unlabeled pollutant gas samples (benzene, formaldehyde, acetone and ethylalcohol); however, labeled wound infection samples are hard to gain. Thus, we pose self-taught learning to utilize these gas samples, obtaining a basis vector θ. Then, using the basis vector θ, we reconstruct the new representation of wound infection samples under sparsity constraint, which is the input of classifiers. We compare RBF with partial least squares discriminant analysis (PLSDA), and reach a conclusion that the performance of RBF is superior to others. We also change the dimension of our data set and the quantity of unlabeled data to search the input matrix that produces the highest accuracy. PMID:28991154

Weakly Supervised Dictionary Learning

NASA Astrophysics Data System (ADS)

You, Zeyu; Raich, Raviv; Fern, Xiaoli Z.; Kim, Jinsub

2018-05-01

We present a probabilistic modeling and inference framework for discriminative analysis dictionary learning under a weak supervision setting. Dictionary learning approaches have been widely used for tasks such as low-level signal denoising and restoration as well as high-level classification tasks, which can be applied to audio and image analysis. Synthesis dictionary learning aims at jointly learning a dictionary and corresponding sparse coefficients to provide accurate data representation. This approach is useful for denoising and signal restoration, but may lead to sub-optimal classification performance. By contrast, analysis dictionary learning provides a transform that maps data to a sparse discriminative representation suitable for classification. We consider the problem of analysis dictionary learning for time-series data under a weak supervision setting in which signals are assigned with a global label instead of an instantaneous label signal. We propose a discriminative probabilistic model that incorporates both label information and sparsity constraints on the underlying latent instantaneous label signal using cardinality control. We present the expectation maximization (EM) procedure for maximum likelihood estimation (MLE) of the proposed model. To facilitate a computationally efficient E-step, we propose both a chain and a novel tree graph reformulation of the graphical model. The performance of the proposed model is demonstrated on both synthetic and real-world data.

Artifact detection in electrodermal activity using sparse recovery

NASA Astrophysics Data System (ADS)

Kelsey, Malia; Palumbo, Richard Vincent; Urbaneja, Alberto; Akcakaya, Murat; Huang, Jeannie; Kleckner, Ian R.; Barrett, Lisa Feldman; Quigley, Karen S.; Sejdic, Ervin; Goodwin, Matthew S.

2017-05-01

Electrodermal Activity (EDA) - a peripheral index of sympathetic nervous system activity - is a primary measure used in psychophysiology. EDA is widely accepted as an indicator of physiological arousal, and it has been shown to reveal when psychologically novel events occur. Traditionally, EDA data is collected in controlled laboratory experiments. However, recent developments in wireless biosensing have led to an increase in out-of-lab studies. This transition to ambulatory data collection has introduced challenges. In particular, artifacts such as wearer motion, changes in temperature, and electrical interference can be misidentified as true EDA responses. The inability to distinguish artifact from signal hinders analyses of ambulatory EDA data. Though manual procedures for identifying and removing EDA artifacts exist, they are time consuming - which is problematic for the types of longitudinal data sets represented in modern ambulatory studies. This manuscript presents a novel technique to automatically identify and remove artifacts in EDA data using curve fitting and sparse recovery methods. Our method was evaluated using labeled data to determine the accuracy of artifact identification. Procedures, results, conclusions, and future directions are presented.

Does the visual system of the flying fox resemble that of primates? The distribution of calcium-binding proteins in the primary visual pathway of Pteropus poliocephalus.

PubMed

Ichida, J M; Rosa, M G; Casagrande, V A

2000-01-31

It has been proposed that flying foxes and echolocating bats evolved independently from early mammalian ancestors in such a way that flying foxes form one of the suborders most closely related to primates. A major piece of evidence offered in support of a flying fox-primate link is the highly developed visual system of flying foxes, which is theorized to be primate-like in several different ways. Because the calcium-binding proteins parvalbumin (PV) and calbindin (CB) show distinct and consistent distributions in the primate visual system, the distribution of these same proteins was examined in the flying fox (Pteropus poliocephalus) visual system. Standard immunocytochemical techniques reveal that PV labeling within the lateral geniculate nucleus (LGN) of the flying fox is sparse, with clearly labeled cells located only within layer 1, adjacent to the optic tract. CB labeling in the LGN is profuse, with cells labeled in all layers throughout the nucleus. Double labeling reveals that all PV+ cells also contain CB, and that these cells are among the largest in the LGN. In primary visual cortex (V1) PV and CB label different classes of non-pyramidal neurons. PV+ cells are found in all cortical layers, although labeled cells are found only rarely in layer I. CB+ cells are found primarily in layers II and III. The density of PV+ neuropil correlates with the density of cytochrome oxidase staining; however, no CO+ or PV+ or CB+ patches or blobs are found in V1. These results show that the distribution of calcium-binding proteins in the flying fox LGN is unlike that found in primates, in which antibodies for PV and CB label specific separate populations of relay cells that exist in different layers. Indeed, the pattern of calcium-binding protein distribution in the flying fox LGN is different from that reported in any other terrestrial mammal. Within V1 no PV+ patches, CO blobs, or patchy distribution of CB+ neuropil that might reveal interblobs characteristic of primate V1 are found; however, PV and CB are found in separate populations of non-pyramidal neurons. The types of V1 cells labeled with antibodies to PV and CB in all mammals examined including the flying fox suggest that the similarities in the cellular distribution of these proteins in cortex reflect the fact that this feature is common to all mammals.

Cross-View Action Recognition via Transferable Dictionary Learning.

PubMed

Zheng, Jingjing; Jiang, Zhuolin; Chellappa, Rama

2016-05-01

Discriminative appearance features are effective for recognizing actions in a fixed view, but may not generalize well to a new view. In this paper, we present two effective approaches to learn dictionaries for robust action recognition across views. In the first approach, we learn a set of view-specific dictionaries where each dictionary corresponds to one camera view. These dictionaries are learned simultaneously from the sets of correspondence videos taken at different views with the aim of encouraging each video in the set to have the same sparse representation. In the second approach, we additionally learn a common dictionary shared by different views to model view-shared features. This approach represents the videos in each view using a view-specific dictionary and the common dictionary. More importantly, it encourages the set of videos taken from the different views of the same action to have the similar sparse representations. The learned common dictionary not only has the capability to represent actions from unseen views, but also makes our approach effective in a semi-supervised setting where no correspondence videos exist and only a few labeled videos exist in the target view. The extensive experiments using three public datasets demonstrate that the proposed approach outperforms recently developed approaches for cross-view action recognition.

Label-free optical imaging of membrane patches for atomic force microscopy

PubMed Central

Churnside, Allison B.; King, Gavin M.; Perkins, Thomas T.

2010-01-01

In atomic force microscopy (AFM), finding sparsely distributed regions of interest can be difficult and time-consuming. Typically, the tip is scanned until the desired object is located. This process can mechanically or chemically degrade the tip, as well as damage fragile biological samples. Protein assemblies can be detected using the back-scattered light from a focused laser beam. We previously used back-scattered light from a pair of laser foci to stabilize an AFM. In the present work, we integrate these techniques to optically image patches of purple membranes prior to AFM investigation. These rapidly acquired optical images were aligned to the subsequent AFM images to ~40 nm, since the tip position was aligned to the optical axis of the imaging laser. Thus, this label-free imaging efficiently locates sparsely distributed protein assemblies for subsequent AFM study while simultaneously minimizing degradation of the tip and the sample. PMID:21164738

Couple Graph Based Label Propagation Method for Hyperspectral Remote Sensing Data Classification

NASA Astrophysics Data System (ADS)

Wang, X. P.; Hu, Y.; Chen, J.

2018-04-01

Graph based semi-supervised classification method are widely used for hyperspectral image classification. We present a couple graph based label propagation method, which contains both the adjacency graph and the similar graph. We propose to construct the similar graph by using the similar probability, which utilize the label similarity among examples probably. The adjacency graph was utilized by a common manifold learning method, which has effective improve the classification accuracy of hyperspectral data. The experiments indicate that the couple graph Laplacian which unite both the adjacency graph and the similar graph, produce superior classification results than other manifold Learning based graph Laplacian and Sparse representation based graph Laplacian in label propagation framework.

Serotonin projection patterns to the cochlear nucleus.

PubMed

Thompson, A M; Thompson, G C

2001-07-13

The cochlear nucleus is well known as an obligatory relay center for primary auditory nerve fibers. Perhaps not so well known is the neural input to the cochlear nucleus from cells containing serotonin that reside near the midline in the midbrain raphe region. Although the specific locations of the main, if not sole, sources of serotonin within the dorsal cochlear nucleus subdivision are known to be the dorsal and median raphe nuclei, sources of serotonin located within other cochlear nucleus subdivisions are not currently known. Anterograde tract tracing was used to label fibers originating from the dorsal and median raphe nuclei while fluorescence immunohistochemistry was used to simultaneously label specific serotonin fibers in cat. Biotinylated dextran amine was injected into the dorsal and median raphe nuclei and was visualized with Texas Red, while serotonin was visualized with fluorescein. Thus, double-labeled fibers were unequivocally identified as serotoninergic and originating from one of the labeled neurons within the dorsal and median raphe nuclei. Double-labeled fiber segments, typically of fine caliber with oval varicosities, were observed in many areas of the cochlear nucleus. They were found in the molecular layer of the dorsal cochlear nucleus, in the small cell cap region, and in the granule cell and external regions of the cochlear nuclei, bilaterally, of all cats. However, the density of these double-labeled fiber segments varied considerably depending upon the exact region in which they were found. Fiber segments were most dense in the dorsal cochlear nucleus (especially in the molecular layer) and the large spherical cell area of the anteroventral cochlear nucleus; they were moderately dense in the small cell cap region; and fiber segments were least dense in the octopus and multipolar cell regions of the posteroventral cochlear nucleus. Because of the presence of labeled fiber segments in subdivisions of the cochlear nucleus other than the dorsal cochlear nucleus, we concluded that the serotoninergic projection pattern to the cochlear nucleus is divergent and non-specific. Double-labeled fiber segments were also present, but sparse, in the superior olive, localized mainly in periolivary regions; this indicated that the divergence of dorsal and median raphe neurons that extends throughout regions of the cochlear nucleus also extended well beyond the cochlear nucleus to include at least the superior olivary complex as well.

Structured sparse linear graph embedding.

PubMed

Wang, Haixian

2012-03-01

Subspace learning is a core issue in pattern recognition and machine learning. Linear graph embedding (LGE) is a general framework for subspace learning. In this paper, we propose a structured sparse extension to LGE (SSLGE) by introducing a structured sparsity-inducing norm into LGE. Specifically, SSLGE casts the projection bases learning into a regression-type optimization problem, and then the structured sparsity regularization is applied to the regression coefficients. The regularization selects a subset of features and meanwhile encodes high-order information reflecting a priori structure information of the data. The SSLGE technique provides a unified framework for discovering structured sparse subspace. Computationally, by using a variational equality and the Procrustes transformation, SSLGE is efficiently solved with closed-form updates. Experimental results on face image show the effectiveness of the proposed method. Copyright © 2011 Elsevier Ltd. All rights reserved.

40 CFR 600.311-12 - Determination of values for fuel economy labels.

Code of Federal Regulations, 2012 CFR

2012-07-01

... of available information from the certification database for all model types. Specifically, the mean... vehicle cannot be charged at the higher voltage. (l) California-specific values. If the Administrator... fuel economy or other label values from those intended for sale in other states, the Administrator will...

Scene Text Recognition using Similarity and a Lexicon with Sparse Belief Propagation

PubMed Central

Weinman, Jerod J.; Learned-Miller, Erik; Hanson, Allen R.

2010-01-01

Scene text recognition (STR) is the recognition of text anywhere in the environment, such as signs and store fronts. Relative to document recognition, it is challenging because of font variability, minimal language context, and uncontrolled conditions. Much information available to solve this problem is frequently ignored or used sequentially. Similarity between character images is often overlooked as useful information. Because of language priors, a recognizer may assign different labels to identical characters. Directly comparing characters to each other, rather than only a model, helps ensure that similar instances receive the same label. Lexicons improve recognition accuracy but are used post hoc. We introduce a probabilistic model for STR that integrates similarity, language properties, and lexical decision. Inference is accelerated with sparse belief propagation, a bottom-up method for shortening messages by reducing the dependency between weakly supported hypotheses. By fusing information sources in one model, we eliminate unrecoverable errors that result from sequential processing, improving accuracy. In experimental results recognizing text from images of signs in outdoor scenes, incorporating similarity reduces character recognition error by 19%, the lexicon reduces word recognition error by 35%, and sparse belief propagation reduces the lexicon words considered by 99.9% with a 12X speedup and no loss in accuracy. PMID:19696446

16 CFR 309.17 - Labels.

Code of Federal Regulations, 2013 CFR

2013-01-01

... contents of the label that you wish to use, and the reasons that you want to use it. (3) Electric vehicle... electric vehicle fuel dispensing systems. All type should be set in upper case (all caps) “Helvetica Black... ALTERNATIVE FUELS AND ALTERNATIVE FUELED VEHICLES Requirements for Alternative Fuels Label Specifications...

16 CFR 309.17 - Labels.

Code of Federal Regulations, 2014 CFR

2014-01-01

... contents of the label that you wish to use, and the reasons that you want to use it. (3) Electric vehicle... electric vehicle fuel dispensing systems. All type should be set in upper case (all caps) “Helvetica Black... ALTERNATIVE FUELS AND ALTERNATIVE FUELED VEHICLES Requirements for Alternative Fuels Label Specifications...

16 CFR 309.17 - Labels.

Code of Federal Regulations, 2012 CFR

2012-01-01

... contents of the label that you wish to use, and the reasons that you want to use it. (3) Electric vehicle... electric vehicle fuel dispensing systems. All type should be set in upper case (all caps) “Helvetica Black... ALTERNATIVE FUELS AND ALTERNATIVE FUELED VEHICLES Requirements for Alternative Fuels Label Specifications...

Adherence to Preexposure Prophylaxis: Current, Emerging, and Anticipated Bases of Evidence

PubMed Central

Amico, K. Rivet; Stirratt, Michael J.

2014-01-01

Despite considerable discussion and debate about adherence to preexposure prophylaxis (PrEP) for human immunodeficiency virus (HIV), scant data are available that characterize patterns of adherence to open-label PrEP. The current evidence base is instead dominated by research on adherence to placebo-controlled investigational drug by way of drug detection in active-arm participants of large randomized controlled trials (RCTs). Important differences between the context of blinded RCTs and open-label use suggest caution when generalizing from study product adherence to real-world PrEP use. Evidence specific to open-label PrEP adherence is presently sparse but will expand rapidly over the next few years as roll-out, demonstration projects, and more rigorous research collect and present findings. The current evidence bases established cannot yet predict uptake, adherence, or persistence with open-label effective PrEP. Emerging evidence suggests that some cohorts could execute better adherence in open-label use vs placebo-controlled research. Uptake of PrEP is presently slow in the United States; whether this changes as grassroots and community efforts increase awareness of PrEP as an effective HIV prevention option remains to be determined. As recommended by multiple guidelines for PrEP use, all current demonstration projects offer PrEP education and/or counseling. PrEP support approaches generally fall into community-based, technology, monitoring, and integrated sexual health promotion approaches. Developing and implementing research that moves beyond simple correlates of either study product use or open-label PrEP adherence toward more comprehensive models of sociobehavioral and socioecological adherence determinants would greatly accelerate progress. Intervention research is needed to identify effective models of support for open-label PrEP adherence. PMID:24926036

Protein expression and isotopic enrichment based on induction of the Entner-Doudoroff pathway in Escherichia coli

DOE Office of Scientific and Technical Information (OSTI.GOV)

Refaeli, Bosmat; Goldbourt, Amir, E-mail: amirgo@post.tau.ac.il

2012-10-12

Highlights: Black-Right-Pointing-Pointer The Entner-Doudoroff pathway is induced during protein expression in E. coli. Black-Right-Pointing-Pointer 1-{sup 13}C-gluconate and {sup 15}NH{sub 4}Cl provide a carbonyl-amide protein backbone labeling scheme. Black-Right-Pointing-Pointer The enrichment pattern is determined by nuclear magnetic resonance. -- Abstract: The Entner-Doudoroff pathway is known to exist in many organisms including bacteria, archea and eukarya. Although the common route for carbon catabolism in Escherichia coli is the Embden-Meyerhof-Parnas pathway, it was shown that gluconate catabolism in E. coli occurs via the Entner-Doudoroff pathway. We demonstrate here that by supplying BL21(DE3) competent E.coli cells with gluconate in a minimal growth medium, proteinmore » expression can be induced. Nuclear magnetic resonance data of over-expressed ubiquitin show that by using [1-{sup 13}C]-gluconate as the only carbon source, and {sup 15}N-enriched ammonium chloride, sparse isotopic enrichment in the form of a spin-pair carbonyl-amide backbone enrichment is obtained. The specific amino acid labeling pattern is analyzed and is shown to be compatible with Entner-Doudoroff metabolism. Isotopic enrichment serves as a key factor in the biophysical characterization of proteins by various methods including nuclear magnetic resonance, mass spectrometry, infrared spectroscopy and more. Therefore, the method presented here can be applied to study proteins by obtaining sparse enrichment schemes that are not based on the regular glycolytic pathway, or to study the Entner-Doudoroff metabolism during protein expression.« less

Classification of melanoma lesions using sparse coded features and random forests

NASA Astrophysics Data System (ADS)

Rastgoo, Mojdeh; Lemaître, Guillaume; Morel, Olivier; Massich, Joan; Garcia, Rafael; Meriaudeau, Fabrice; Marzani, Franck; Sidibé, Désiré

2016-03-01

Malignant melanoma is the most dangerous type of skin cancer, yet it is the most treatable kind of cancer, conditioned by its early diagnosis which is a challenging task for clinicians and dermatologists. In this regard, CAD systems based on machine learning and image processing techniques are developed to differentiate melanoma lesions from benign and dysplastic nevi using dermoscopic images. Generally, these frameworks are composed of sequential processes: pre-processing, segmentation, and classification. This architecture faces mainly two challenges: (i) each process is complex with the need to tune a set of parameters, and is specific to a given dataset; (ii) the performance of each process depends on the previous one, and the errors are accumulated throughout the framework. In this paper, we propose a framework for melanoma classification based on sparse coding which does not rely on any pre-processing or lesion segmentation. Our framework uses Random Forests classifier and sparse representation of three features: SIFT, Hue and Opponent angle histograms, and RGB intensities. The experiments are carried out on the public PH2 dataset using a 10-fold cross-validation. The results show that SIFT sparse-coded feature achieves the highest performance with sensitivity and specificity of 100% and 90.3% respectively, with a dictionary size of 800 atoms and a sparsity level of 2. Furthermore, the descriptor based on RGB intensities achieves similar results with sensitivity and specificity of 100% and 71.3%, respectively for a smaller dictionary size of 100 atoms. In conclusion, dictionary learning techniques encode strong structures of dermoscopic images and provide discriminant descriptors.

Brain tumor classification and segmentation using sparse coding and dictionary learning.

PubMed

Salman Al-Shaikhli, Saif Dawood; Yang, Michael Ying; Rosenhahn, Bodo

2016-08-01

This paper presents a novel fully automatic framework for multi-class brain tumor classification and segmentation using a sparse coding and dictionary learning method. The proposed framework consists of two steps: classification and segmentation. The classification of the brain tumors is based on brain topology and texture. The segmentation is based on voxel values of the image data. Using K-SVD, two types of dictionaries are learned from the training data and their associated ground truth segmentation: feature dictionary and voxel-wise coupled dictionaries. The feature dictionary consists of global image features (topological and texture features). The coupled dictionaries consist of coupled information: gray scale voxel values of the training image data and their associated label voxel values of the ground truth segmentation of the training data. For quantitative evaluation, the proposed framework is evaluated using different metrics. The segmentation results of the brain tumor segmentation (MICCAI-BraTS-2013) database are evaluated using five different metric scores, which are computed using the online evaluation tool provided by the BraTS-2013 challenge organizers. Experimental results demonstrate that the proposed approach achieves an accurate brain tumor classification and segmentation and outperforms the state-of-the-art methods.

Distribution of α-Gustducin and Vimentin in premature and mature taste buds in chickens.

PubMed

Venkatesan, Nandakumar; Rajapaksha, Prasangi; Payne, Jason; Goodfellow, Forrest; Wang, Zhonghou; Kawabata, Fuminori; Tabata, Shoji; Stice, Steven; Beckstead, Robert; Liu, Hong-Xiang

2016-10-14

The sensory organs for taste in chickens (Gallus sp.) are taste buds in the oral epithelium of the palate, base of the oral cavity, and posterior tongue. Although there is not a pan-taste cell marker that labels all chicken taste bud cells, α-Gustducin and Vimentin each label a subpopulation of taste bud cells. In the present study, we used both α-Gustducin and Vimentin to further characterize chicken taste buds at the embryonic and post-hatching stages (E17-P5). We found that both α-Gustducin and Vimentin label distinct and overlapping populations of, but not all, taste bud cells. A-Gustducin immunosignals were observed as early as E18 and were consistently distributed in early and mature taste buds in embryos and hatchlings. Vimentin immunoreactivity was initially sparse at the embryonic stages then became apparent in taste buds after hatch. In hatchlings, α-Gustducin and Vimentin immunosignals largely co-localized in taste buds. A small subset of taste bud cells were labeled by either α-Gustducin or Vimentin or were not labeled. Importantly, each of the markers was observed in all of the examined taste buds. Our data suggest that the early onset of α-Gustducin in taste buds might be important for enabling chickens to respond to taste stimuli immediately after hatch and that distinctive population of taste bud cells that are labeled by different molecular markers might represent different cell types or different phases of taste bud cells. Additionally, α-Gustducin and Vimentin can potentially be used as molecular markers of all chicken taste buds in whole mount tissue. Copyright © 2016 Elsevier Inc. All rights reserved.

Progress of new label-free techniques for biosensors: a review.

PubMed

Sang, Shengbo; Wang, Yajun; Feng, Qiliang; Wei, Ye; Ji, Jianlong; Zhang, Wendong

2016-01-01

The detection techniques used in biosensors can be broadly classified into label-based and label-free. Label-based detection relies on the specific properties of labels for detecting a particular target. In contrast, label-free detection is suitable for the target molecules that are not labeled or the screening of analytes which are not easy to tag. Also, more types of label-free biosensors have emerged with developments in biotechnology. The latest developed techniques in label-free biosensors, such as field-effect transistors-based biosensors including carbon nanotube field-effect transistor biosensors, graphene field-effect transistor biosensors and silicon nanowire field-effect transistor biosensors, magnetoelastic biosensors, optical-based biosensors, surface stress-based biosensors and other type of biosensors based on the nanotechnology are discussed. The sensing principles, configurations, sensing performance, applications, advantages and restriction of different label-free based biosensors are considered and discussed in this review. Most concepts included in this survey could certainly be applied to the development of this kind of biosensor in the future.

Antigen processing of glycoconjugate vaccines; the polysaccharide portion of the pneumococcal CRM(197) conjugate vaccine co-localizes with MHC II on the antigen processing cell surface.

PubMed

Lai, Zengzu; Schreiber, John R

2009-05-21

Pneumococcal (Pn) polysaccharides (PS) are T-independent (TI) antigens and do not induce immunological memory or antibodies in infants. Conjugation of PnPS to the carrier protein CRM(197) induces PS-specific antibody in infants, and memory similar to T-dependent (Td) antigens. Conjugates have improved immunogenicity via antigen processing and presentation of carrier protein with MHC II and recruitment of T cell help, but the fate of the PS attached to the carrier is unknown. To determine the location of the PS component of PnPS-CRM(197) in the APC, we separately labeled PS and protein and tracked their location. The PS of types 14-CRM(197) and 19F-CRM(197) was specifically labeled by Alexa Fluor 594 hydrazide (red). The CRM(197) was separately labeled red in a reaction that did not label PS. Labeled antigens were incubated with APC which were fixed, permeabilized and incubated with anti-MHC II antibody labeled green by Alexa Fluor 488, followed by confocal microscopy. Labeled CRM(197) was presented on APC surface and co-localized with MHC II (yellow). Labeled unconjugated 14 or 19F PS did not go to the APC surface, but PS labeled 14-CRM(197) and 19F-CRM(197) was internalized and co-localized with MHC II. Monoclonal antibody to type 14 PS bound to intracellular type 14 PS and PS-CRM(197). Brefeldin A and chloroquine blocked both CRM(197) and PS labeled 14-CRM(197) and 19F-CRM(197) from co-localizing with MHC II. These data suggest that the PS component of the CRM(197) glycoconjugate enters the endosome, travels with CRM(197) peptides to the APC surface and co-localizes with MHC II.

Coupled dictionary learning for joint MR image restoration and segmentation

NASA Astrophysics Data System (ADS)

Yang, Xuesong; Fan, Yong

2018-03-01

To achieve better segmentation of MR images, image restoration is typically used as a preprocessing step, especially for low-quality MR images. Recent studies have demonstrated that dictionary learning methods could achieve promising performance for both image restoration and image segmentation. These methods typically learn paired dictionaries of image patches from different sources and use a common sparse representation to characterize paired image patches, such as low-quality image patches and their corresponding high quality counterparts for the image restoration, and image patches and their corresponding segmentation labels for the image segmentation. Since learning these dictionaries jointly in a unified framework may improve the image restoration and segmentation simultaneously, we propose a coupled dictionary learning method to concurrently learn dictionaries for joint image restoration and image segmentation based on sparse representations in a multi-atlas image segmentation framework. Particularly, three dictionaries, including a dictionary of low quality image patches, a dictionary of high quality image patches, and a dictionary of segmentation label patches, are learned in a unified framework so that the learned dictionaries of image restoration and segmentation can benefit each other. Our method has been evaluated for segmenting the hippocampus in MR T1 images collected with scanners of different magnetic field strengths. The experimental results have demonstrated that our method achieved better image restoration and segmentation performance than state of the art dictionary learning and sparse representation based image restoration and image segmentation methods.

The cell wall of Arabidopsis thaliana influences actin network dynamics.

PubMed

Tolmie, Frances; Poulet, Axel; McKenna, Joseph; Sassmann, Stefan; Graumann, Katja; Deeks, Michael; Runions, John

2017-07-20

In plant cells, molecular connections link the cell wall-plasma membrane-actin cytoskeleton to form a continuum. It is hypothesized that the cell wall provides stable anchor points around which the actin cytoskeleton remodels. Here we use live cell imaging of fluorescently labelled marker proteins to quantify the organization and dynamics of the actin cytoskeleton and to determine the impact of disrupting connections within the continuum. Labelling of the actin cytoskeleton with green fluorescent protein (GFP)-fimbrin actin-binding domain 2 (FABD2) resulted in a network composed of fine filaments and thicker bundles that appeared as a highly dynamic remodelling meshwork. This differed substantially from the GFP-Lifeact-labelled network that appeared much more sparse with thick bundles that underwent 'simple movement', in which the bundles slightly change position, but in such a manner that the structure of the network was not substantially altered during the time of observation. Label-dependent differences in actin network morphology and remodelling necessitated development of two new image analysis techniques. The first of these, 'pairwise image subtraction', was applied to measurement of the more rapidly remodelling actin network labelled with GFP-FABD2, while the second, 'cumulative fluorescence intensity', was used to measure bulk remodelling of the actin cytoskeleton when labelled with GFP-Lifeact. In each case, these analysis techniques show that the actin cytoskeleton has a decreased rate of bulk remodelling when the cell wall-plasma membrane-actin continuum is disrupted either by plasmolysis or with isoxaben, a drug that specifically inhibits cellulose deposition. Changes in the rate of actin remodelling also affect its functionality, as observed by alteration in Golgi body motility. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Semi-Supervised Clustering for High-Dimensional and Sparse Features

ERIC Educational Resources Information Center

Yan, Su

2010-01-01

Clustering is one of the most common data mining tasks, used frequently for data organization and analysis in various application domains. Traditional machine learning approaches to clustering are fully automated and unsupervised where class labels are unknown a priori. In real application domains, however, some "weak" form of side…

Review of Sparse Representation-Based Classification Methods on EEG Signal Processing for Epilepsy Detection, Brain-Computer Interface and Cognitive Impairment

PubMed Central

Wen, Dong; Jia, Peilei; Lian, Qiusheng; Zhou, Yanhong; Lu, Chengbiao

2016-01-01

At present, the sparse representation-based classification (SRC) has become an important approach in electroencephalograph (EEG) signal analysis, by which the data is sparsely represented on the basis of a fixed dictionary or learned dictionary and classified based on the reconstruction criteria. SRC methods have been used to analyze the EEG signals of epilepsy, cognitive impairment and brain computer interface (BCI), which made rapid progress including the improvement in computational accuracy, efficiency and robustness. However, these methods have deficiencies in real-time performance, generalization ability and the dependence of labeled sample in the analysis of the EEG signals. This mini review described the advantages and disadvantages of the SRC methods in the EEG signal analysis with the expectation that these methods can provide the better tools for analyzing EEG signals. PMID:27458376

Sparse Coding of Natural Human Motion Yields Eigenmotions Consistent Across People

NASA Astrophysics Data System (ADS)

Thomik, Andreas; Faisal, A. Aldo

2015-03-01

Providing a precise mathematical description of the structure of natural human movement is a challenging problem. We use a data-driven approach to seek a generative model of movement capturing the underlying simplicity of spatial and temporal structure of behaviour observed in daily life. In perception, the analysis of natural scenes has shown that sparse codes of such scenes are information theoretic efficient descriptors with direct neuronal correlates. Translating from perception to action, we identify a generative model of movement generation by the human motor system. Using wearable full-hand motion capture, we measure the digit movement of the human hand in daily life. We learn a dictionary of ``eigenmotions'' which we use for sparse encoding of the movement data. We show that the dictionaries are generally well preserved across subjects with small deviations accounting for individuality of the person and variability in tasks. Further, the dictionary elements represent motions which can naturally describe hand movements. Our findings suggest the motor system can compose complex movement behaviours out of the spatially and temporally sparse activation of ``eigenmotion'' neurons, and is consistent with data on grasp-type specificity of specialised neurons in the premotor cortex. Andreas is supported by the Luxemburg Research Fund (1229297).

Sparse, decorrelated odor coding in the mushroom body enhances learned odor discrimination.

PubMed

Lin, Andrew C; Bygrave, Alexei M; de Calignon, Alix; Lee, Tzumin; Miesenböck, Gero

2014-04-01

Sparse coding may be a general strategy of neural systems for augmenting memory capacity. In Drosophila melanogaster, sparse odor coding by the Kenyon cells of the mushroom body is thought to generate a large number of precisely addressable locations for the storage of odor-specific memories. However, it remains untested how sparse coding relates to behavioral performance. Here we demonstrate that sparseness is controlled by a negative feedback circuit between Kenyon cells and the GABAergic anterior paired lateral (APL) neuron. Systematic activation and blockade of each leg of this feedback circuit showed that Kenyon cells activated APL and APL inhibited Kenyon cells. Disrupting the Kenyon cell-APL feedback loop decreased the sparseness of Kenyon cell odor responses, increased inter-odor correlations and prevented flies from learning to discriminate similar, but not dissimilar, odors. These results suggest that feedback inhibition suppresses Kenyon cell activity to maintain sparse, decorrelated odor coding and thus the odor specificity of memories.

Disclaimer labels on fashion magazine advertisements: effects on social comparison and body dissatisfaction.

PubMed

Tiggemann, Marika; Slater, Amy; Bury, Belinda; Hawkins, Kimberley; Firth, Bonny

2013-01-01

Recent proposals across a number of Western countries have suggested that idealised media images should carry some sort of disclaimer informing readers when these images have been digitally enhanced. The present studies aimed to experimentally investigate the impact on women's body dissatisfaction of the addition of such warning labels to fashion magazine advertisements. Participants were 120 and 114 female undergraduate students in Experiment 1 and Experiment 2 respectively. In both experiments, participants viewed fashion magazine advertisements with either no warning label, a generic warning label, or a specific more detailed warning label. In neither experiment was there a significant effect of type of label. However, state appearance comparison was found to predict change in body dissatisfaction irrespective of condition. Unexpectedly, trait appearance comparison moderated the effect of label on body dissatisfaction, such that for women high on trait appearance comparison, exposure to specific warning labels actually resulted in increased body dissatisfaction. In sum, the present results showed no benefit of warning labels in ameliorating the known negative effect of viewing thin-ideal media images, and even suggested that one form of warning (specific) might be harmful for some individuals. Accordingly, it was concluded that more extensive research is required to guide the most effective use of disclaimer labels. Copyright © 2012 Elsevier Ltd. All rights reserved.

An exploratory study of drinkers views of health information and warning labels on alcohol containers.

PubMed

Thomson, Lisa M; Vandenberg, Brian; Fitzgerald, John L

2012-03-01

To identify general and specific features of health information warning labels on alcohol beverage containers that could potentially inform the development and implementation of a new labelling regime in Australia. Mixed methods, including a cross-sectional population survey and a qualitative study of knowledge, attitudes and behaviours regarding alcohol beverage labelling. The population survey used computer-assisted telephone interviews of 1500 persons in Victoria, Australia to gauge the level of support for health information and warning labels. The qualitative study used six focus groups to test the suitability of 12 prototype labels that were placed in situ on a variety of alcohol beverage containers. The telephone survey found 80% to 90% support for a range of information that could potentially be mandated by government authorities for inclusion on labels (nutritional information, alcohol content, health warning, images). Focus group testing of the prototype label designs found that labels should be integrated with other alcohol-related health messages, such as government social advertising campaigns, and specific labels should be matched appropriately to specific consumer groups and beverage types. There are high levels of public support for health information and warning labels on alcohol beverages. This study contributes much needed empirical guidance for developing alcohol beverage labelling strategies in an Australian context. © 2011 Australasian Professional Society on Alcohol and other Drugs.

Enhanced low-rank representation via sparse manifold adaption for semi-supervised learning.

PubMed

Peng, Yong; Lu, Bao-Liang; Wang, Suhang

2015-05-01

Constructing an informative and discriminative graph plays an important role in various pattern recognition tasks such as clustering and classification. Among the existing graph-based learning models, low-rank representation (LRR) is a very competitive one, which has been extensively employed in spectral clustering and semi-supervised learning (SSL). In SSL, the graph is composed of both labeled and unlabeled samples, where the edge weights are calculated based on the LRR coefficients. However, most of existing LRR related approaches fail to consider the geometrical structure of data, which has been shown beneficial for discriminative tasks. In this paper, we propose an enhanced LRR via sparse manifold adaption, termed manifold low-rank representation (MLRR), to learn low-rank data representation. MLRR can explicitly take the data local manifold structure into consideration, which can be identified by the geometric sparsity idea; specifically, the local tangent space of each data point was sought by solving a sparse representation objective. Therefore, the graph to depict the relationship of data points can be built once the manifold information is obtained. We incorporate a regularizer into LRR to make the learned coefficients preserve the geometric constraints revealed in the data space. As a result, MLRR combines both the global information emphasized by low-rank property and the local information emphasized by the identified manifold structure. Extensive experimental results on semi-supervised classification tasks demonstrate that MLRR is an excellent method in comparison with several state-of-the-art graph construction approaches. Copyright © 2015 Elsevier Ltd. All rights reserved.

16 CFR 309.21 - Labeling requirements for used covered vehicles.

Code of Federal Regulations, 2012 CFR

2012-01-01

... numbers, bar codes, and vehicle identification numbers consistent with Figure 6. (c) Type size and setting... vehicles. 309.21 Section 309.21 Commercial Practices FEDERAL TRADE COMMISSION REGULATIONS UNDER SPECIFIC ACTS OF CONGRESS LABELING REQUIREMENTS FOR ALTERNATIVE FUELS AND ALTERNATIVE FUELED VEHICLES...

16 CFR 309.21 - Labeling requirements for used covered vehicles.

Code of Federal Regulations, 2013 CFR

2013-01-01

... numbers, bar codes, and vehicle identification numbers consistent with Figure 6. (c) Type size and setting... vehicles. 309.21 Section 309.21 Commercial Practices FEDERAL TRADE COMMISSION REGULATIONS UNDER SPECIFIC ACTS OF CONGRESS LABELING REQUIREMENTS FOR ALTERNATIVE FUELS AND ALTERNATIVE FUELED VEHICLES...

16 CFR 309.20 - Labeling requirements for new covered vehicles.

Code of Federal Regulations, 2013 CFR

2013-01-01

... numbers, bar codes, and vehicle identification numbers consistent with Figures 4, 5, and 5.1. (c) Type... vehicles. 309.20 Section 309.20 Commercial Practices FEDERAL TRADE COMMISSION REGULATIONS UNDER SPECIFIC ACTS OF CONGRESS LABELING REQUIREMENTS FOR ALTERNATIVE FUELS AND ALTERNATIVE FUELED VEHICLES...

16 CFR 309.20 - Labeling requirements for new covered vehicles.

Code of Federal Regulations, 2012 CFR

2012-01-01

... numbers, bar codes, and vehicle identification numbers consistent with Figures 4, 5, and 5.1. (c) Type... vehicles. 309.20 Section 309.20 Commercial Practices FEDERAL TRADE COMMISSION REGULATIONS UNDER SPECIFIC ACTS OF CONGRESS LABELING REQUIREMENTS FOR ALTERNATIVE FUELS AND ALTERNATIVE FUELED VEHICLES...

Algorithm for selection of optimized EPR distance restraints for de novo protein structure determination

PubMed Central

Kazmier, Kelli; Alexander, Nathan S.; Meiler, Jens; Mchaourab, Hassane S.

2010-01-01

A hybrid protein structure determination approach combining sparse Electron Paramagnetic Resonance (EPR) distance restraints and Rosetta de novo protein folding has been previously demonstrated to yield high quality models (Alexander et al., 2008). However, widespread application of this methodology to proteins of unknown structures is hindered by the lack of a general strategy to place spin label pairs in the primary sequence. In this work, we report the development of an algorithm that optimally selects spin labeling positions for the purpose of distance measurements by EPR. For the α-helical subdomain of T4 lysozyme (T4L), simulated restraints that maximize sequence separation between the two spin labels while simultaneously ensuring pairwise connectivity of secondary structure elements yielded vastly improved models by Rosetta folding. 50% of all these models have the correct fold compared to only 21% and 8% correctly folded models when randomly placed restraints or no restraints are used, respectively. Moreover, the improvements in model quality require a limited number of optimized restraints, the number of which is determined by the pairwise connectivities of T4L α-helices. The predicted improvement in Rosetta model quality was verified by experimental determination of distances between spin labels pairs selected by the algorithm. Overall, our results reinforce the rationale for the combined use of sparse EPR distance restraints and de novo folding. By alleviating the experimental bottleneck associated with restraint selection, this algorithm sets the stage for extending computational structure determination to larger, traditionally elusive protein topologies of critical structural and biochemical importance. PMID:21074624

Photoaffinity labeling of protoporphyrinogen oxidase, the molecular target of diphenylether-type herbicides.

PubMed

Camadro, J M; Matringe, M; Thome, F; Brouillet, N; Mornet, R; Labbe, P

1995-05-01

Diphenylether-type herbicides are extremely potent inhibitors of protoporphyrinogen oxidase, a membrane-bound enzyme involved in the heme and chlorophyll biosynthesis pathways. Tritiated acifluorfen and a diazoketone derivative of tritiated acifluorfen were specifically bound to a single class of high-affinity binding sites on yeast mitochondrial membranes with apparent dissociation constants of 7 nM and 12.5 nM, respectively. The maximum density of specific binding sites, determined by Scatchard analysis, was 3 pmol.mg-1 protein. Protoporphyrinogen oxidase specific activity was estimated to be 2500 nmol protoporphyrinogen oxidized h-1.mol-1 enzyme. The diazoketone derivative of tritiated acifluorfen was used to specifically photolabel yeast protoporphyrinogen oxidase. The specifically labeled polypeptide in wild-type mitochondrial membranes had an apparent molecular mass of 55 kDa, identical to the molecular mass of the purified enzyme. This photolabeled polypeptide was not detected in a protoporphyrinogen-oxidase-deficient yeast strain, but the membranes contained an equivalent amount of inactive immunoreactive protoporphyrinogen oxidase protein.

Analysis of Monte Carlo accelerated iterative methods for sparse linear systems: Analysis of Monte Carlo accelerated iterative methods for sparse linear systems

DOE PAGES

Benzi, Michele; Evans, Thomas M.; Hamilton, Steven P.; ...

2017-03-05

Here, we consider hybrid deterministic-stochastic iterative algorithms for the solution of large, sparse linear systems. Starting from a convergent splitting of the coefficient matrix, we analyze various types of Monte Carlo acceleration schemes applied to the original preconditioned Richardson (stationary) iteration. We expect that these methods will have considerable potential for resiliency to faults when implemented on massively parallel machines. We also establish sufficient conditions for the convergence of the hybrid schemes, and we investigate different types of preconditioners including sparse approximate inverses. Numerical experiments on linear systems arising from the discretization of partial differential equations are presented.

Exploiting Attribute Correlations: A Novel Trace Lasso-Based Weakly Supervised Dictionary Learning Method.

PubMed

Wu, Lin; Wang, Yang; Pan, Shirui

2017-12-01

It is now well established that sparse representation models are working effectively for many visual recognition tasks, and have pushed forward the success of dictionary learning therein. Recent studies over dictionary learning focus on learning discriminative atoms instead of purely reconstructive ones. However, the existence of intraclass diversities (i.e., data objects within the same category but exhibit large visual dissimilarities), and interclass similarities (i.e., data objects from distinct classes but share much visual similarities), makes it challenging to learn effective recognition models. To this end, a large number of labeled data objects are required to learn models which can effectively characterize these subtle differences. However, labeled data objects are always limited to access, committing it difficult to learn a monolithic dictionary that can be discriminative enough. To address the above limitations, in this paper, we propose a weakly-supervised dictionary learning method to automatically learn a discriminative dictionary by fully exploiting visual attribute correlations rather than label priors. In particular, the intrinsic attribute correlations are deployed as a critical cue to guide the process of object categorization, and then a set of subdictionaries are jointly learned with respect to each category. The resulting dictionary is highly discriminative and leads to intraclass diversity aware sparse representations. Extensive experiments on image classification and object recognition are conducted to show the effectiveness of our approach.

In vivo nanoparticle imaging of innate immune cells can serve as a marker of disease severity in a model of multiple sclerosis.

PubMed

Kirschbaum, Klara; Sonner, Jana K; Zeller, Matthias W; Deumelandt, Katrin; Bode, Julia; Sharma, Rakesh; Krüwel, Thomas; Fischer, Manuel; Hoffmann, Angelika; Costa da Silva, Milene; Muckenthaler, Martina U; Wick, Wolfgang; Tews, Björn; Chen, John W; Heiland, Sabine; Bendszus, Martin; Platten, Michael; Breckwoldt, Michael O

2016-11-15

Innate immune cells play a key role in the pathogenesis of multiple sclerosis and experimental autoimmune encephalomyelitis (EAE). Current clinical imaging is restricted to visualizing secondary effects of inflammation, such as gliosis and blood-brain barrier disruption. Advanced molecular imaging, such as iron oxide nanoparticle imaging, can allow direct imaging of cellular and molecular activity, but the exact cell types that phagocytose nanoparticles in vivo and how phagocytic activity relates to disease severity is not well understood. In this study we used MRI to map inflammatory infiltrates using high-field MRI and fluorescently labeled cross-linked iron oxide nanoparticles for cell tracking. We confirmed nanoparticle uptake and MR detectability ex vivo. Using in vivo MRI, we identified extensive nanoparticle signal in the cerebellar white matter and circumscribed cortical gray matter lesions that developed during the disease course (4.6-fold increase of nanoparticle accumulation in EAE compared with healthy controls, P < 0.001). Nanoparticles showed good cellular specificity for innate immune cells in vivo, labeling activated microglia, infiltrating macrophages, and neutrophils, whereas there was only sparse uptake by adaptive immune cells. Importantly, nanoparticle signal correlated better with clinical disease than conventional gadolinium (Gd) imaging (r, 0.83 for nanoparticles vs. 0.71 for Gd-imaging, P < 0.001). We validated our approach using the Food and Drug Administration-approved iron oxide nanoparticle ferumoxytol. Our results show that noninvasive molecular imaging of innate immune responses can serve as an imaging biomarker of disease activity in autoimmune-mediated neuroinflammation with potential clinical applications in a wide range of inflammatory diseases.

Expression, limited proteolysis and preliminary crystallographic analysis of IpaD, a component of the Shigella flexneri type III secretion system

PubMed Central

Johnson, Steven; Roversi, Pietro; Espina, Marianela; Deane, Janet E.; Birket, Susan; Picking, William D.; Blocker, Ariel; Picking, Wendy L.; Lea, Susan M.

2006-01-01

IpaD, the putative needle-tip protein of the Shigella flexneri type III secretion system, has been overexpressed and purified. Crystals were grown of the native protein in space group P212121, with unit-cell parameters a = 55.9, b = 100.7, c = 112.0 Å, and data were collected to 2.9 Å resolution. Analysis of the native Patterson map revealed a peak at 50% of the origin on the Harker section v = 0.5, suggesting twofold non-crystallographic symmetry parallel to the b crystallographic axis. As attempts to derivatize or grow selenomethionine-labelled protein crystals failed, in-drop proteolysis was used to produce new crystal forms. A trace amount of subtilisin Carlsberg was added to IpaD before sparse-matrix screening, resulting in the production of several new crystal forms. This approach produced SeMet-labelled crystals and diffraction data were collected to 3.2 Å resolution. The SeMet crystals belong to space group C2, with unit-cell parameters a = 139.4, b = 45.0, c = 99.5 Å, β = 107.9°. An anomalous difference Patterson map revealed peaks on the Harker section v = 0, while the self-rotation function indicates the presence of a twofold noncrystallographic symmetry axis, which is consistent with two molecules per asymmetric unit. PMID:16946465

Expression, limited proteolysis and preliminary crystallographic analysis of IpaD, a component of the Shigella flexneri type III secretion system.

PubMed

Johnson, Steven; Roversi, Pietro; Espina, Marianela; Deane, Janet E; Birket, Susan; Picking, William D; Blocker, Ariel; Picking, Wendy L; Lea, Susan M

2006-09-01

IpaD, the putative needle-tip protein of the Shigella flexneri type III secretion system, has been overexpressed and purified. Crystals were grown of the native protein in space group P2(1)2(1)2(1), with unit-cell parameters a = 55.9, b = 100.7, c = 112.0 A, and data were collected to 2.9 A resolution. Analysis of the native Patterson map revealed a peak at 50% of the origin on the Harker section v = 0.5, suggesting twofold non-crystallographic symmetry parallel to the b crystallographic axis. As attempts to derivatize or grow selenomethionine-labelled protein crystals failed, in-drop proteolysis was used to produce new crystal forms. A trace amount of subtilisin Carlsberg was added to IpaD before sparse-matrix screening, resulting in the production of several new crystal forms. This approach produced SeMet-labelled crystals and diffraction data were collected to 3.2 A resolution. The SeMet crystals belong to space group C2, with unit-cell parameters a = 139.4, b = 45.0, c = 99.5 A, beta = 107.9 degrees . An anomalous difference Patterson map revealed peaks on the Harker section v = 0, while the self-rotation function indicates the presence of a twofold noncrystallographic symmetry axis, which is consistent with two molecules per asymmetric unit.

Evidence for sparse synergies in grasping actions.

PubMed

Prevete, Roberto; Donnarumma, Francesco; d'Avella, Andrea; Pezzulo, Giovanni

2018-01-12

Converging evidence shows that hand-actions are controlled at the level of synergies and not single muscles. One intriguing aspect of synergy-based action-representation is that it may be intrinsically sparse and the same synergies can be shared across several distinct types of hand-actions. Here, adopting a normative angle, we consider three hypotheses for hand-action optimal-control: sparse-combination hypothesis (SC) - sparsity in the mapping between synergies and actions - i.e., actions implemented using a sparse combination of synergies; sparse-elements hypothesis (SE) - sparsity in synergy representation - i.e., the mapping between degrees-of-freedom (DoF) and synergies is sparse; double-sparsity hypothesis (DS) - a novel view combining both SC and SE - i.e., both the mapping between DoF and synergies and between synergies and actions are sparse, each action implementing a sparse combination of synergies (as in SC), each using a limited set of DoFs (as in SE). We evaluate these hypotheses using hand kinematic data from six human subjects performing nine different types of reach-to-grasp actions. Our results support DS, suggesting that the best action representation is based on a relatively large set of synergies, each involving a reduced number of degrees-of-freedom, and that distinct sets of synergies may be involved in distinct tasks.

The morphological and chemical characteristics of striatal neurons immunoreactive for the alpha1-subunit of the GABA(A) receptor in the rat.

PubMed

Waldvogel, H J; Kubota, Y; Trevallyan, S C; Kawaguchi, Y; Fritschy, J M; Mohler, H; Faull, R L

1997-10-01

The distribution, morphology and chemical characteristics of neurons immunoreactive for the alpha1-subunit of the GABA(A) receptor in the striatum of the basal ganglia in the rat brain were investigated at the light, confocal and electron microscope levels using single, double and triple immunohistochemical labelling techniques. The results showed that alpha1-subunit immunoreactive neurons were sparsely distributed throughout the rat striatum. Double and triple labelling results showed that all the alpha1-subunit-immunoreactive neurons were positive for glutamate decarboxylase and immunoreactive for the beta2,3 and gamma2 subunits of the GABA(A) receptor. Three types of alpha1-subunit-immunoreactive neurons were identified in the striatum on the basis of cellular morphology and chemical characteristics. The most numerous alpha1-subunit-immunoreactive neurons were medium-sized, aspiny neurons with a widely branching dendritic tree. They were parvalbumin-negative and were located mainly in the dorsolateral regions of the striatum. Electron microscopy showed that these neurons had an indented nuclear membrane, typical of striatal interneurons, and were surrounded by small numbers of axon terminals which established alpha1-subunit-immunoreactive synaptic contacts with the soma and dendrites. These cells were classified as type 1 alpha1-subunit-immunoreactive neurons and comprised 75% of the total population of alpha1-subunit-immunoreactive neurons in the striatum. The remaining alpha1-subunit-immunoreactive neurons comprised of a heterogeneous population of large-sized neurons localized in the ventral and medial regions of the striatum. The most numerous large-sized cells were parvalbumin-negative, had two to three relatively short branching dendrites and were designated type 2 alpha1-subunit-immunoreactive neurons. Electron microscopy showed that the type 2 neurons were characterized by a highly convoluted nuclear membrane and were sparsely covered with small axon terminals. The type 2 neurons comprised 20% of the total population of alpha1-subunit-immunoreactive neurons. The remaining large-sized alpha1-immunoreactive cells were designated type 3 cells; they were positive for parvalbumin and were distinguished by long branching dendrites extending dorsally for 600-800 microm into the striatum. These neurons comprised 5% of the total population of alpha1-subunit-immunoreactive neurons and were surrounded by enkephalin-immunoreactive terminals. Electron microscopy showed that the alpha1-subunit type 3 neurons had an indented nuclear membrane and were densely covered with small axon terminals which established alpha1-subunit-immunoreactive symmetrical synaptic contacts with the soma and dendrites. These results provide a detailed characterization of the distribution, morphology and chemical characteristics of the alpha1-subunit-immunoreactive neurons in the rat striatum and suggest that the type 1 and type 2 neurons comprise of separate populations of striatal interneurons while the type 3 neurons may represent the large striatonigral projection neurons described by Bolam et al. [Bolam J. P., Somogyi P., Totterdell S. and Smith A. D. (1981) Neuroscience 6, 2141-2157.].

Multifunctional PSCA antibody fragments for PET and optical prostate cancer imaging

DTIC Science & Technology

2017-10-01

INVESTIGATOR: Anna M. Wu CONTRACTING ORGANIZATION: University of California, Los Angeles Los Angeles, CA 90095-1406 REPORT DATE : October 2017 TYPE OF...cys- minibodies and cys-diabodies) can be labeled with radioisotopes for non-invasive PET imaging for use at multiple points in the prostate cancer...optimize and test multifunctional, F-18, and alternatively labeled fragments Major Task 3. New technologies: alternative site-specific labeling methods

A coarse-to-fine approach for medical hyperspectral image classification with sparse representation

NASA Astrophysics Data System (ADS)

Chang, Lan; Zhang, Mengmeng; Li, Wei

2017-10-01

A coarse-to-fine approach with sparse representation is proposed for medical hyperspectral image classification in this work. Segmentation technique with different scales is employed to exploit edges of the input image, where coarse super-pixel patches provide global classification information while fine ones further provide detail information. Different from common RGB image, hyperspectral image has multi bands to adjust the cluster center with more high precision. After segmentation, each super pixel is classified by recently-developed sparse representation-based classification (SRC), which assigns label for testing samples in one local patch by means of sparse linear combination of all the training samples. Furthermore, segmentation with multiple scales is employed because single scale is not suitable for complicate distribution of medical hyperspectral imagery. Finally, classification results for different sizes of super pixel are fused by some fusion strategy, offering at least two benefits: (1) the final result is obviously superior to that of segmentation with single scale, and (2) the fusion process significantly simplifies the choice of scales. Experimental results using real medical hyperspectral images demonstrate that the proposed method outperforms the state-of-the-art SRC.

Sparse Regression as a Sparse Eigenvalue Problem

NASA Technical Reports Server (NTRS)

Moghaddam, Baback; Gruber, Amit; Weiss, Yair; Avidan, Shai

2008-01-01

We extend the l0-norm "subspectral" algorithms for sparse-LDA [5] and sparse-PCA [6] to general quadratic costs such as MSE in linear (kernel) regression. The resulting "Sparse Least Squares" (SLS) problem is also NP-hard, by way of its equivalence to a rank-1 sparse eigenvalue problem (e.g., binary sparse-LDA [7]). Specifically, for a general quadratic cost we use a highly-efficient technique for direct eigenvalue computation using partitioned matrix inverses which leads to dramatic x103 speed-ups over standard eigenvalue decomposition. This increased efficiency mitigates the O(n4) scaling behaviour that up to now has limited the previous algorithms' utility for high-dimensional learning problems. Moreover, the new computation prioritizes the role of the less-myopic backward elimination stage which becomes more efficient than forward selection. Similarly, branch-and-bound search for Exact Sparse Least Squares (ESLS) also benefits from partitioned matrix inverse techniques. Our Greedy Sparse Least Squares (GSLS) generalizes Natarajan's algorithm [9] also known as Order-Recursive Matching Pursuit (ORMP). Specifically, the forward half of GSLS is exactly equivalent to ORMP but more efficient. By including the backward pass, which only doubles the computation, we can achieve lower MSE than ORMP. Experimental comparisons to the state-of-the-art LARS algorithm [3] show forward-GSLS is faster, more accurate and more flexible in terms of choice of regularization

High affinity receptor labeling based on basic leucine zipper domain peptides conjugated with pH-sensitive fluorescent dye: Visualization of AMPA-type glutamate receptor endocytosis in living neurons.

PubMed

Hayashi, Ayako; Asanuma, Daisuke; Kamiya, Mako; Urano, Yasuteru; Okabe, Shigeo

2016-01-01

Techniques to visualize receptor trafficking in living neurons are important, but currently available methods are limited in their labeling efficiency, specificity and reliability. Here we report a method for receptor labeling with a basic leucine zipper domain peptide (ZIP) and a binding cassette specific to ZIP. Receptors are tagged with a ZIP-binding cassette at their extracellular domain. Tagged receptors expressed in cultured cells were labeled with exogenously applied fluorescently labeled ZIP with low background and high affinity. To test if ZIP labeling is useful in monitoring endocytosis and intracellular trafficking, we next conjugated ZIP with a pH-sensitive dye RhP-M (ZIP-RhP-M). ZIP binding to its binding cassette was pH-resistant and RhP-M fluorescence dramatically increased in acidic environment. Thus AMPA-type glutamate receptors (AMPARs) labeled by ZIP-RhP-M can report receptor endocytosis and subsequent intracellular trafficking. Application of ZIP-RhP-M to cultured hippocampal neurons expressing AMPARs tagged with a ZIP-binding cassette resulted in appearance of fluorescent puncta in PSD-95-positive large spines, suggesting local endocytosis and acidification of AMPARs in individual mature spines. This spine pool of AMPARs in acidic environment was distinct from the early endosomes labeled by transferrin uptake. These results suggest that receptor labeling by ZIP-RhP-M is a useful technique for monitoring endocytosis and intracellular trafficking. This article is part of the Special Issue entitled 'Synaptopathy--from Biology to Therapy'. Copyright © 2015 Elsevier Ltd. All rights reserved.

Combining DCQGMP-Based Sparse Decomposition and MPDR Beamformer for Multi-Type Interferences Mitigation for GNSS Receivers.

PubMed

Guo, Qiang; Qi, Liangang

2017-04-10

In the coexistence of multiple types of interfering signals, the performance of interference suppression methods based on time and frequency domains is degraded seriously, and the technique using an antenna array requires a large enough size and huge hardware costs. To combat multi-type interferences better for GNSS receivers, this paper proposes a cascaded multi-type interferences mitigation method combining improved double chain quantum genetic matching pursuit (DCQGMP)-based sparse decomposition and an MPDR beamformer. The key idea behind the proposed method is that the multiple types of interfering signals can be excised by taking advantage of their sparse features in different domains. In the first stage, the single-tone (multi-tone) and linear chirp interfering signals are canceled by sparse decomposition according to their sparsity in the over-complete dictionary. In order to improve the timeliness of matching pursuit (MP)-based sparse decomposition, a DCQGMP is introduced by combining an improved double chain quantum genetic algorithm (DCQGA) and the MP algorithm, and the DCQGMP algorithm is extended to handle the multi-channel signals according to the correlation among the signals in different channels. In the second stage, the minimum power distortionless response (MPDR) beamformer is utilized to nullify the residuary interferences (e.g., wideband Gaussian noise interferences). Several simulation results show that the proposed method can not only improve the interference mitigation degree of freedom (DoF) of the array antenna, but also effectively deal with the interference arriving from the same direction with the GNSS signal, which can be sparse represented in the over-complete dictionary. Moreover, it does not bring serious distortions into the navigation signal.

Combining DCQGMP-Based Sparse Decomposition and MPDR Beamformer for Multi-Type Interferences Mitigation for GNSS Receivers

PubMed Central

Guo, Qiang; Qi, Liangang

2017-01-01

In the coexistence of multiple types of interfering signals, the performance of interference suppression methods based on time and frequency domains is degraded seriously, and the technique using an antenna array requires a large enough size and huge hardware costs. To combat multi-type interferences better for GNSS receivers, this paper proposes a cascaded multi-type interferences mitigation method combining improved double chain quantum genetic matching pursuit (DCQGMP)-based sparse decomposition and an MPDR beamformer. The key idea behind the proposed method is that the multiple types of interfering signals can be excised by taking advantage of their sparse features in different domains. In the first stage, the single-tone (multi-tone) and linear chirp interfering signals are canceled by sparse decomposition according to their sparsity in the over-complete dictionary. In order to improve the timeliness of matching pursuit (MP)-based sparse decomposition, a DCQGMP is introduced by combining an improved double chain quantum genetic algorithm (DCQGA) and the MP algorithm, and the DCQGMP algorithm is extended to handle the multi-channel signals according to the correlation among the signals in different channels. In the second stage, the minimum power distortionless response (MPDR) beamformer is utilized to nullify the residuary interferences (e.g., wideband Gaussian noise interferences). Several simulation results show that the proposed method can not only improve the interference mitigation degree of freedom (DoF) of the array antenna, but also effectively deal with the interference arriving from the same direction with the GNSS signal, which can be sparse represented in the over-complete dictionary. Moreover, it does not bring serious distortions into the navigation signal. PMID:28394290

Cell Kinetic and Histomorphometric Analysis of Microgravitational Osteopenia: PARE.03B

NASA Technical Reports Server (NTRS)

Roberts, W. Eugene; Garetto, Lawrence P.

1998-01-01

Previous methods of identifying cells undergoing DNA synthesis (S-phase) utilized 3H-thymidine (3HT) autoradiography. 5-Bromo-2'-deoxyuridine (BrdU) immunohistochemistry is a nonradioactive alternative method. This experiment compared the two methods using the nuclear volume model for osteoblast histogenesis in two different embedding media. Twenty Sprague-Dawley rats were used, with half receiving 3HT (1 micro-Ci/g) and the other half BrdU (50 micro-g/g). Condyles were embedded (one side in paraffin, the other in plastic) and S-phase nuclei were identified using either autoradiography or immunohistochemistry. The fractional distribution of preosteoblast cell types and the percentage of labeled cells (within each cell fraction and label index) were calculated and expressed as mean +/- standard error. Chi-Square analysis showed only a minor difference in the fractional distribution of cell types. However, there were,significant differences (p less than 0.05) by ANOVA, in the nuclear labeling of specific cell types. With the exception of the less-differentiated A+A' cells, more BrdU label was consistently detected in paraffin than in plastic-embedded sections. In general, more nuclei were labeled with 3H-thymidine than with BrdU in both types of embedding media (Fig 2.). Labeling index data (labeled cells/total cells sampled x 100) indicated that BrdU in paraffin, but not plastic gave the same results as 3HT in either embedding method. Thus, we conclude that the two labeling methods do not yield the same results.

Comparison of two front-of-package nutrition labeling schemes, and their explanation, on consumers' perception of product healthfulness and food choice.

PubMed

Lundeberg, Pamela J; Graham, Dan J; Mohr, Gina S

2018-06-01

Front-of-package (FOP) nutrition labels are increasingly used to present nutritional information to consumers. A variety of FOP nutrition schemes exist for presenting condensed nutrition information. The present study directly compared two symbolic FOP labeling systems - traffic light and star-based schemes - with specific regard to healthfulness perception and purchase intention for a variety of products. Additionally, this study investigated which method of message framing (gain, loss, gain + loss) would best enable individuals to effectively utilize the FOP labels. College students (n = 306) viewed food packages featuring either star or traffic light FOP labels and rated the healthfulness of each product and their likelihood of purchasing the product. Within each label type, participants were presented with differently-framed instructions regarding how to use the labels. Participants who viewed the star labels rated products with the lowest healthfulness as significantly less healthful and rated products with the highest healthfulness as significantly more healthful compared to participants who viewed those same products with traffic light labels. Purchase intention did not differ by label type. Additionally, including any type of framing (gain, loss, or gain + loss) assisted consumers in differentiating between foods with mid-range vs. low nutritional value. Star-based labels led more healthful foods to be seen as even more healthful and less healthful foods to be seen as even less healthful compared to the same foods with traffic light labels. Additionally, results indicate a benefit of including framing information for FOP nutrition label instructions; however, no individual frame led to significantly different behavior compared to the other frames. While ratings of product healthfulness were influenced by the framing and the label type, purchase intention was not impacted by either of these factors. Copyright © 2018 Elsevier Ltd. All rights reserved.

Protein C-Terminal Labeling and Biotinylation Using Synthetic Peptide and Split-Intein

PubMed Central

Volkmann, Gerrit; Liu, Xiang-Qin

2009-01-01

Background Site-specific protein labeling or modification can facilitate the characterization of proteins with respect to their structure, folding, and interaction with other proteins. However, current methods of site-specific protein labeling are few and with limitations, therefore new methods are needed to satisfy the increasing need and sophistications of protein labeling. Methodology A method of protein C-terminal labeling was developed using a non-canonical split-intein, through an intein-catalyzed trans-splicing reaction between a protein and a small synthetic peptide carrying the desired labeling groups. As demonstrations of this method, three different proteins were efficiently labeled at their C-termini with two different labels (fluorescein and biotin) either in solution or on a solid surface, and a transferrin receptor protein was labeled on the membrane surface of live mammalian cells. Protein biotinylation and immobilization on a streptavidin-coated surface were also achieved in a cell lysate without prior purification of the target protein. Conclusions We have produced a method of site-specific labeling or modification at the C-termini of recombinant proteins. This method compares favorably with previous protein labeling methods and has several unique advantages. It is expected to have many potential applications in protein engineering and research, which include fluorescent labeling for monitoring protein folding, location, and trafficking in cells, and biotinylation for protein immobilization on streptavidin-coated surfaces including protein microchips. The types of chemical labeling may be limited only by the ability of chemical synthesis to produce the small C-intein peptide containing the desired chemical groups. PMID:20027230

Nutrition labelling is a trade policy issue: lessons from an analysis of specific trade concerns at the World Trade Organization.

PubMed

Thow, Anne Marie; Jones, Alexandra; Hawkes, Corinna; Ali, Iqra; Labonté, Ronald

2017-01-12

Interpretive nutrition labels provide simplified nutrient-specific text and/or symbols on the front of pre-packaged foods, to encourage and enable consumers to make healthier choices. This type of labelling has been proposed as part of a comprehensive policy response to the global epidemic of non-communicable diseases. However, regulation of nutrition labelling falls under the remit of not just the health sector but also trade. Specific Trade Concerns have been raised at the World Trade Organization's Technical Barriers to Trade Committee regarding interpretive nutrition labelling initiatives in Thailand, Chile, Indonesia, Peru and Ecuador. This paper presents an analysis of the discussions of these concerns. Although nutrition labelling was identified as a legitimate policy objective, queries were raised regarding the justification of the specific labelling measures proposed, and the scientific evidence for effectiveness of such measures. Concerns were also raised regarding the consistency of the measures with international standards. Drawing on policy learning theory, we identified four lessons for public health policy makers, including: strategic framing of nutrition labelling policy objectives; pro-active policy engagement between trade and health to identify potential trade issues; identifying ways to minimize potential 'practical' trade concerns; and engagement with the Codex Alimentarius Commission to develop international guidance on interpretative labelling. This analysis indicates that while there is potential for trade sector concerns to stifle innovation in nutrition labelling policy, care in how interpretive nutrition labelling measures are crafted in light of trade commitments can minimize such a risk and help ensure that trade policy is coherent with nutrition action. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

64Cu antibody-targeting of the T-cell receptor and subsequent internalization enables in vivo tracking of lymphocytes by PET

PubMed Central

Griessinger, Christoph M.; Maurer, Andreas; Kesenheimer, Christian; Kehlbach, Rainer; Reischl, Gerald; Ehrlichmann, Walter; Bukala, Daniel; Harant, Maren; Cay, Funda; Brück, Jürgen; Nordin, Renate; Kohlhofer, Ursula; Rammensee, Hans-Georg; Quintanilla-Martinez, Leticia; Schaller, Martin; Röcken, Martin; Pichler, Bernd J.; Kneilling, Manfred

2015-01-01

T cells are key players in inflammation, autoimmune diseases, and immunotherapy. Thus, holistic and noninvasive in vivo characterizations of the temporal distribution and homing dynamics of lymphocytes in mammals are of special interest. Herein, we show that PET-based T-cell labeling facilitates quantitative, highly sensitive, and holistic monitoring of T-cell homing patterns in vivo. We developed a new T-cell receptor (TCR)-specific labeling approach for the intracellular labeling of mouse T cells. We found that continuous TCR plasma membrane turnover and the endocytosis of the specific 64Cu-monoclonal antibody (mAb)–TCR complex enables a stable labeling of T cells. The TCR–mAb complex was internalized within 24 h, whereas antigen recognition was not impaired. Harmful effects of the label on the viability, DNA-damage and apoptosis-necrosis induction, could be minimized while yielding a high contrast in in vivo PET images. We were able to follow and quantify the specific homing of systemically applied 64Cu-labeled chicken ovalbumin (cOVA)-TCR transgenic T cells into the pulmonary and perithymic lymph nodes (LNs) of mice with cOVA-induced airway delayed-type hypersensitivity reaction (DTHR) but not into pulmonary and perithymic LNs of naïve control mice or mice diseased from turkey or pheasant OVA-induced DTHR. Our protocol provides consequent advancements in the detection of small accumulations of immune cells in single LNs and specific homing to the sites of inflammation by PET using the internalization of TCR-specific mAbs as a specific label of T cells. Thus, our labeling approach is applicable to other cells with constant membrane receptor turnover. PMID:25587131

Improving EEG-Based Driver Fatigue Classification Using Sparse-Deep Belief Networks.

PubMed

Chai, Rifai; Ling, Sai Ho; San, Phyo Phyo; Naik, Ganesh R; Nguyen, Tuan N; Tran, Yvonne; Craig, Ashley; Nguyen, Hung T

2017-01-01

This paper presents an improvement of classification performance for electroencephalography (EEG)-based driver fatigue classification between fatigue and alert states with the data collected from 43 participants. The system employs autoregressive (AR) modeling as the features extraction algorithm, and sparse-deep belief networks (sparse-DBN) as the classification algorithm. Compared to other classifiers, sparse-DBN is a semi supervised learning method which combines unsupervised learning for modeling features in the pre-training layer and supervised learning for classification in the following layer. The sparsity in sparse-DBN is achieved with a regularization term that penalizes a deviation of the expected activation of hidden units from a fixed low-level prevents the network from overfitting and is able to learn low-level structures as well as high-level structures. For comparison, the artificial neural networks (ANN), Bayesian neural networks (BNN), and original deep belief networks (DBN) classifiers are used. The classification results show that using AR feature extractor and DBN classifiers, the classification performance achieves an improved classification performance with a of sensitivity of 90.8%, a specificity of 90.4%, an accuracy of 90.6%, and an area under the receiver operating curve (AUROC) of 0.94 compared to ANN (sensitivity at 80.8%, specificity at 77.8%, accuracy at 79.3% with AUC-ROC of 0.83) and BNN classifiers (sensitivity at 84.3%, specificity at 83%, accuracy at 83.6% with AUROC of 0.87). Using the sparse-DBN classifier, the classification performance improved further with sensitivity of 93.9%, a specificity of 92.3%, and an accuracy of 93.1% with AUROC of 0.96. Overall, the sparse-DBN classifier improved accuracy by 13.8, 9.5, and 2.5% over ANN, BNN, and DBN classifiers, respectively.

Improving EEG-Based Driver Fatigue Classification Using Sparse-Deep Belief Networks

PubMed Central

Chai, Rifai; Ling, Sai Ho; San, Phyo Phyo; Naik, Ganesh R.; Nguyen, Tuan N.; Tran, Yvonne; Craig, Ashley; Nguyen, Hung T.

2017-01-01

This paper presents an improvement of classification performance for electroencephalography (EEG)-based driver fatigue classification between fatigue and alert states with the data collected from 43 participants. The system employs autoregressive (AR) modeling as the features extraction algorithm, and sparse-deep belief networks (sparse-DBN) as the classification algorithm. Compared to other classifiers, sparse-DBN is a semi supervised learning method which combines unsupervised learning for modeling features in the pre-training layer and supervised learning for classification in the following layer. The sparsity in sparse-DBN is achieved with a regularization term that penalizes a deviation of the expected activation of hidden units from a fixed low-level prevents the network from overfitting and is able to learn low-level structures as well as high-level structures. For comparison, the artificial neural networks (ANN), Bayesian neural networks (BNN), and original deep belief networks (DBN) classifiers are used. The classification results show that using AR feature extractor and DBN classifiers, the classification performance achieves an improved classification performance with a of sensitivity of 90.8%, a specificity of 90.4%, an accuracy of 90.6%, and an area under the receiver operating curve (AUROC) of 0.94 compared to ANN (sensitivity at 80.8%, specificity at 77.8%, accuracy at 79.3% with AUC-ROC of 0.83) and BNN classifiers (sensitivity at 84.3%, specificity at 83%, accuracy at 83.6% with AUROC of 0.87). Using the sparse-DBN classifier, the classification performance improved further with sensitivity of 93.9%, a specificity of 92.3%, and an accuracy of 93.1% with AUROC of 0.96. Overall, the sparse-DBN classifier improved accuracy by 13.8, 9.5, and 2.5% over ANN, BNN, and DBN classifiers, respectively. PMID:28326009

Scaffolding Collaborative Argumentation in Asynchronous Discussions with Message Constraints and Message Labels

ERIC Educational Resources Information Center

Jeong, Allan; Joung, Sunyoung

2007-01-01

This study examined the effects of message constraints and labels on collaborative argumentation in asynchronous online discussions. Thirty-eight undergraduate students in an introductory educational technology course were assigned to one of three groups. In one group, students posted specific types of messages using a prescribed set of message…

Hematopoietic stem cell-specific GFP-expressing transgenic mice generated by genetic excision of a pan-hematopoietic reporter gene.

PubMed

Perez-Cunningham, Jessica; Boyer, Scott W; Landon, Mark; Forsberg, E Camilla

2016-08-01

Selective labeling of specific cell types by expression of green fluorescent protein (GFP) within the hematopoietic system would have great utility in identifying, localizing, and tracking different cell populations in flow cytometry, microscopy, lineage tracing, and transplantation assays. In this report, we describe the generation and characterization of a new transgenic mouse line with specific GFP labeling of all nucleated hematopoietic cells and platelets. This new "Vav-GFP" mouse line labels the vast majority of hematopoietic cells with GFP during both embryonic development and adulthood, with particularly high expression in hematopoietic stem and progenitor cells (HSPCs). With the exception of transient labeling of fetal endothelial cells, GFP expression is highly selective for hematopoietic cells and persists in donor-derived progeny after transplantation of HSPCs. Finally, we also demonstrate that the loxP-flanked reporter allows for specific GFP labeling of different hematopoietic cell subsets when crossed to various Cre reporter lines. By crossing Vav-GFP mice to Flk2-Cre mice, we obtained robust and highly selective GFP expression in hematopoietic stem cells (HSCs). These data describe a new mouse model capable of directing GFP labeling exclusively of hematopoietic cells or exclusively of HSCs. Copyright © 2016 ISEH - International Society for Experimental Hematology. Published by Elsevier Inc. All rights reserved.

Deep neural ensemble for retinal vessel segmentation in fundus images towards achieving label-free angiography.

PubMed

Lahiri, A; Roy, Abhijit Guha; Sheet, Debdoot; Biswas, Prabir Kumar

2016-08-01

Automated segmentation of retinal blood vessels in label-free fundus images entails a pivotal role in computed aided diagnosis of ophthalmic pathologies, viz., diabetic retinopathy, hypertensive disorders and cardiovascular diseases. The challenge remains active in medical image analysis research due to varied distribution of blood vessels, which manifest variations in their dimensions of physical appearance against a noisy background. In this paper we formulate the segmentation challenge as a classification task. Specifically, we employ unsupervised hierarchical feature learning using ensemble of two level of sparsely trained denoised stacked autoencoder. First level training with bootstrap samples ensures decoupling and second level ensemble formed by different network architectures ensures architectural revision. We show that ensemble training of auto-encoders fosters diversity in learning dictionary of visual kernels for vessel segmentation. SoftMax classifier is used for fine tuning each member autoencoder and multiple strategies are explored for 2-level fusion of ensemble members. On DRIVE dataset, we achieve maximum average accuracy of 95.33% with an impressively low standard deviation of 0.003 and Kappa agreement coefficient of 0.708. Comparison with other major algorithms substantiates the high efficacy of our model.

d-LSD-induced c-Fos expression occurs in a population of oligodendrocytes in rat prefrontal cortex.

PubMed

Reissig, Chad J; Rabin, Richard A; Winter, Jerrold C; Dlugos, Cynthia A

2008-03-31

Induction of mRNA or protein for immediate-early genes, such as c-fos, is used to identify brain areas, specific cell types, and neuronal circuits that become activated in response to various stimuli including psychoactive drugs. The objective of the present study was to identify the cell types in the prefrontal cortex in which lysergic acid diethylamide (d-LSD) induces c-Fos expression. Systemic administration of d-LSD resulted in a dose-dependent increase in c-Fos immunoreactivity. Although c-Fos-positive cells were found in all cortical layers, they were most numerous in layers III, IV, and V. d-LSD-induced c-Fos immunoreactivity was found in cells co-labeled with anti-neuron-specific enolase or anti-oligodendrocyte Oligo1. The Oligo1-labeled cells had small, round bodies and nuclear diameters characteristic of oligodendrocytes. Studies using confocal microscopy confirmed colocalization of c-Fos-labeled nuclei in NeuN-labeled neurons. Astrocytes and microglia labeled with glial fibrillary acidic protein antibody and OX-42 antibody, respectively, did not display LSD-induced c-Fos expression. Pyramidal neurons labeled with anti-neurofilament antibody also did not show induction of c-Fos immunoreactivity after systemic d-LSD administration. The present study demonstrates that d-LSD induced expression of c-Fos in the prefrontal cortex occurs in subpopulations of neurons and in oligodendrocytes, but not in pyramidal neurons, astrocytes, and microglia.

Hierarchical Nanogold Labels to Improve the Sensitivity of Lateral Flow Immunoassay

NASA Astrophysics Data System (ADS)

Serebrennikova, Kseniya; Samsonova, Jeanne; Osipov, Alexander

2018-06-01

Lateral flow immunoassay (LFIA) is a widely used express method and offers advantages such as a short analysis time, simplicity of testing and result evaluation. However, an LFIA based on gold nanospheres lacks the desired sensitivity, thereby limiting its wide applications. In this study, spherical nanogold labels along with new types of nanogold labels such as gold nanopopcorns and nanostars were prepared, characterized, and applied for LFIA of model protein antigen procalcitonin. It was found that the label with a structure close to spherical provided more uniform distribution of specific antibodies on its surface, indicative of its suitability for this type of analysis. LFIA using gold nanopopcorns as a label allowed procalcitonin detection over a linear range of 0.5-10 ng mL-1 with the limit of detection of 0.1 ng mL-1, which was fivefold higher than the sensitivity of the assay with gold nanospheres. Another approach to improve the sensitivity of the assay included the silver enhancement method, which was used to compare the amplification of LFIA for procalcitonin detection. The sensitivity of procalcitonin determination by this method was 10 times better the sensitivity of the conventional LFIA with gold nanosphere as a label. The proposed approach of LFIA based on gold nanopopcorns improved the detection sensitivity without additional steps and prevented the increased consumption of specific reagents (antibodies).

Joint Sparse Recovery With Semisupervised MUSIC

NASA Astrophysics Data System (ADS)

Wen, Zaidao; Hou, Biao; Jiao, Licheng

2017-05-01

Discrete multiple signal classification (MUSIC) with its low computational cost and mild condition requirement becomes a significant noniterative algorithm for joint sparse recovery (JSR). However, it fails in rank defective problem caused by coherent or limited amount of multiple measurement vectors (MMVs). In this letter, we provide a novel sight to address this problem by interpreting JSR as a binary classification problem with respect to atoms. Meanwhile, MUSIC essentially constructs a supervised classifier based on the labeled MMVs so that its performance will heavily depend on the quality and quantity of these training samples. From this viewpoint, we develop a semisupervised MUSIC (SS-MUSIC) in the spirit of machine learning, which declares that the insufficient supervised information in the training samples can be compensated from those unlabeled atoms. Instead of constructing a classifier in a fully supervised manner, we iteratively refine a semisupervised classifier by exploiting the labeled MMVs and some reliable unlabeled atoms simultaneously. Through this way, the required conditions and iterations can be greatly relaxed and reduced. Numerical experimental results demonstrate that SS-MUSIC can achieve much better recovery performances than other MUSIC extended algorithms as well as some typical greedy algorithms for JSR in terms of iterations and recovery probability.

Effect of Climate Change on Vegetation Phenology of Different Land Cover Types on the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Cheng, M.; Jin, J.

2017-12-01

Vegetation phenology is one of the most sensitive bio-indicators of climate change, and it has received increasing interests in the context of global warming. As one of the most sensitive areas to global change, the Tibetan Plateau is a unique region to study the trends in vegetation phenology in response to climate change because of its unique vegetation composition, climate features and low-level human disturbance. Although some studies have aroused wide controversies about the actual plant phenology patterns in the Tibetan Plateau, yet the reasons remain unclear. In particular, the phenology characteristics of sparse herbaceous or sparse shrub and evergreen forest that are mostly located in the northwest and southeast of the Tibetan Plateau remain less studied. In this study, the spatio-temporal patterns of the start (SOS), end (EOS) and length (LOS) of the vegetation growing season for six vegetation types in the Tibetan Plateau, including evergreen broadleaf forests, evergreen coniferous forests, evergreen shrub, meadow, steppe and sparse herbaceous or sparse shrub, were quantified from 1982 to 2014 using NOAA/AVHRR NDVI data set at a spatial resolution of 0.05°×0.05° and 7-day intervals using NDVI relative change rate threshold and sixth order polynomial fit models. Assisted with the monthly precipitation and temperature data, the relative effects of changing climates on the variability of phenology were also examined. Diverse phenological changes were observed for different land cover types, with an advancing start of growing season (SOS), delaying end of growing season (EOS) and increasing length of growing season (LOS) in the eastern Tibetan Plateau where meadow was the dominant vegetation type, but with the opposite changes in the steppe and sparse herbaceous or sparse shrub regions which are mostly located in the northwestern and western edges of the Tibetan Plateau. Correlation analysis indicated that sufficient preseason precipitation may delay the SOS of evergreen forests in the southeastern Plateau and advance the SOS of steppe and sparse herbaceous or sparse shrub in relatively arid areas, while the advance of SOS in meadow areas could be related to higher preseason temperature.

Revealing the Hidden Relationship by Sparse Modules in Complex Networks with a Large-Scale Analysis

PubMed Central

Jiao, Qing-Ju; Huang, Yan; Liu, Wei; Wang, Xiao-Fan; Chen, Xiao-Shuang; Shen, Hong-Bin

2013-01-01

One of the remarkable features of networks is module that can provide useful insights into not only network organizations but also functional behaviors between their components. Comprehensive efforts have been devoted to investigating cohesive modules in the past decade. However, it is still not clear whether there are important structural characteristics of the nodes that do not belong to any cohesive module. In order to answer this question, we performed a large-scale analysis on 25 complex networks with different types and scales using our recently developed BTS (bintree seeking) algorithm, which is able to detect both cohesive and sparse modules in the network. Our results reveal that the sparse modules composed by the cohesively isolated nodes widely co-exist with the cohesive modules. Detailed analysis shows that both types of modules provide better characterization for the division of a network into functional units than merely cohesive modules, because the sparse modules possibly re-organize the nodes in the so-called cohesive modules, which lack obvious modular significance, into meaningful groups. Compared with cohesive modules, the sizes of sparse ones are generally smaller. Sparse modules are also found to have preferences in social and biological networks than others. PMID:23762457

Calendar Year 2007 Program Benefits for U.S. EPA Energy Star Labeled Products: Expanded Methodology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanchez, Marla; Homan, Gregory; Lai, Judy

2009-09-24

This report provides a top-level summary of national savings achieved by the Energy Star voluntary product labeling program. To best quantify and analyze savings for all products, we developed a bottom-up product-based model. Each Energy Star product type is characterized by product-specific inputs that result in a product savings estimate. Our results show that through 2007, U.S. EPA Energy Star labeled products saved 5.5 Quads of primary energy and avoided 100 MtC of emissions. Although Energy Star-labeled products encompass over forty product types, only five of those product types accounted for 65percent of all Energy Star carbon reductions achieved tomore » date, including (listed in order of savings magnitude)monitors, printers, residential light fixtures, televisions, and furnaces. The forecast shows that U.S. EPA?s program is expected to save 12.2 Quads of primary energy and avoid 215 MtC of emissions over the period of 2008?2015.« less

Construction of a viral T2A-peptide based knock-in mouse model for enhanced Cre recombinase activity and fluorescent labeling of podocytes.

PubMed

Koehler, Sybille; Brähler, Sebastian; Braun, Fabian; Hagmann, Henning; Rinschen, Markus M; Späth, Martin R; Höhne, Martin; Wunderlich, F Thomas; Schermer, Bernhard; Benzing, Thomas; Brinkkoetter, Paul T

2017-06-01

Podocyte injury is a key event in glomerular disease leading to proteinuria and opening the path toward glomerular scarring. As a consequence, glomerular research strives to discover molecular mechanisms and signaling pathways affecting podocyte health. The hNphs2.Cre mouse model has been a valuable tool to manipulate podocyte-specific genes and to label podocytes for lineage tracing and purification. Here we designed a novel podocyte-specific tricistronic Cre mouse model combining codon improved Cre expression and fluorescent cell labeling with mTomato under the control of the endogenous Nphs2 promoter using viral T2A-peptides. Independent expression of endogenous podocin, codon improved Cre, and mTomato was confirmed by immunofluorescence, fluorescent activated cell sorting and protein analyses. Nphs2 pod.T2A.ciCre.T2A.mTomato/wild-type mice developed normally and did not show any signs of glomerular disease or off-target effects under basal conditions and in states of disease. Nphs2 pod.T2A.ciCre.T2A.mTomato/wild-type -mediated gene recombination was superior to conventional hNphs2.Cre mice-mediated gene recombination. Last, we compared Cre efficiency in a disease model by mating Nphs2 pod.T2A.ciCre.T2A.mTomato/wild-type and hNphs2.Cre mice to Phb2 fl/fl mice. The podocyte-specific Phb2 knockout by Nphs2 pod.T2A.ciCre.T2A.mTomato/wild-type mice resulted in an aggravated glomerular injury as compared to a podocyte-specific Phb2 gene deletion triggered by hNphs2.Cre. Thus, we generated the first tricistronic podocyte mouse model combining enhanced Cre recombinase efficiency and fluorescent labeling in podocytes without the need for additional matings with conventional reporter mouse lines. Copyright © 2016 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

Amino acid selective unlabeling for sequence specific resonance assignments in proteins

PubMed Central

Krishnarjuna, B.; Jaipuria, Garima; Thakur, Anushikha

2010-01-01

Sequence specific resonance assignment constitutes an important step towards high-resolution structure determination of proteins by NMR and is aided by selective identification and assignment of amino acid types. The traditional approach to selective labeling yields only the chemical shifts of the particular amino acid being selected and does not help in establishing a link between adjacent residues along the polypeptide chain, which is important for sequential assignments. An alternative approach is the method of amino acid selective ‘unlabeling’ or reverse labeling, which involves selective unlabeling of specific amino acid types against a uniformly 13C/15N labeled background. Based on this method, we present a novel approach for sequential assignments in proteins. The method involves a new NMR experiment named, {12COi–15Ni+1}-filtered HSQC, which aids in linking the 1HN/15N resonances of the selectively unlabeled residue, i, and its C-terminal neighbor, i + 1, in HN-detected double and triple resonance spectra. This leads to the assignment of a tri-peptide segment from the knowledge of the amino acid types of residues: i − 1, i and i + 1, thereby speeding up the sequential assignment process. The method has the advantage of being relatively inexpensive, applicable to 2H labeled protein and can be coupled with cell-free synthesis and/or automated assignment approaches. A detailed survey involving unlabeling of different amino acid types individually or in pairs reveals that the proposed approach is also robust to misincorporation of 14N at undesired sites. Taken together, this study represents the first application of selective unlabeling for sequence specific resonance assignments and opens up new avenues to using this methodology in protein structural studies. Electronic supplementary material The online version of this article (doi:10.1007/s10858-010-9459-z) contains supplementary material, which is available to authorized users. PMID:21153044

Estimating Highway Volumes Using Vehicle Probe Data - Proof of Concept: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hou, Yi; Young, Stanley E; Sadabadi, Kaveh

This paper examines the feasibility of using sampled commercial probe data in combination with validated continuous counter data to accurately estimate vehicle volume across the entire roadway network, for any hour during the year. Currently either real time or archived volume data for roadways at specific times are extremely sparse. Most volume data are average annual daily traffic (AADT) measures derived from the Highway Performance Monitoring System (HPMS). Although methods to factor the AADT to hourly averages for typical day of week exist, actual volume data is limited to a sparse collection of locations in which volumes are continuously recorded.more » This paper explores the use of commercial probe data to generate accurate volume measures that span the highway network providing ubiquitous coverage in space, and specific point-in-time measures for a specific date and time. The paper examines the need for the data, fundamental accuracy limitations based on a basic statistical model that take into account the sampling nature of probe data, and early results from a proof of concept exercise revealing the potential of probe type data calibrated with public continuous count data to meet end user expectations in terms of accuracy of volume estimates.« less

Visualizing long-term single-molecule dynamics in vivo by stochastic protein labeling.

PubMed

Liu, Hui; Dong, Peng; Ioannou, Maria S; Li, Li; Shea, Jamien; Pasolli, H Amalia; Grimm, Jonathan B; Rivlin, Patricia K; Lavis, Luke D; Koyama, Minoru; Liu, Zhe

2018-01-09

Our ability to unambiguously image and track individual molecules in live cells is limited by packing of multiple copies of labeled molecules within the resolution limit. Here we devise a universal genetic strategy to precisely control copy number of fluorescently labeled molecules in a cell. This system has a dynamic range of ∼10,000-fold, enabling sparse labeling of proteins expressed at different abundance levels. Combined with photostable labels, this system extends the duration of automated single-molecule tracking by two orders of magnitude. We demonstrate long-term imaging of synaptic vesicle dynamics in cultured neurons as well as in intact zebrafish. We found axon initial segment utilizes a "waterfall" mechanism gating synaptic vesicle transport polarity by promoting anterograde transport processivity. Long-time observation also reveals that transcription factor hops between clustered binding sites in spatially restricted subnuclear regions, suggesting that topological structures in the nucleus shape local gene activities by a sequestering mechanism. This strategy thus greatly expands the spatiotemporal length scales of live-cell single-molecule measurements, enabling new experiments to quantitatively understand complex control of molecular dynamics in vivo.

An efficient sparse matrix multiplication scheme for the CYBER 205 computer

NASA Technical Reports Server (NTRS)

Lambiotte, Jules J., Jr.

1988-01-01

This paper describes the development of an efficient algorithm for computing the product of a matrix and vector on a CYBER 205 vector computer. The desire to provide software which allows the user to choose between the often conflicting goals of minimizing central processing unit (CPU) time or storage requirements has led to a diagonal-based algorithm in which one of four types of storage is selected for each diagonal. The candidate storage types employed were chosen to be efficient on the CYBER 205 for diagonals which have nonzero structure which is dense, moderately sparse, very sparse and short, or very sparse and long; however, for many densities, no diagonal type is most efficient with respect to both resource requirements, and a trade-off must be made. For each diagonal, an initialization subroutine estimates the CPU time and storage required for each storage type based on results from previously performed numerical experimentation. These requirements are adjusted by weights provided by the user which reflect the relative importance the user places on the two resources. The adjusted resource requirements are then compared to select the most efficient storage and computational scheme.

Cell lineage tracing during Xenopus tail regeneration.

PubMed

Gargioli, Cesare; Slack, Jonathan M W

2004-06-01

The tail of the Xenopus tadpole will regenerate following amputation, and all three of the main axial structures - the spinal cord, the notochord and the segmented myotomes - are found in the regenerated tail. We have investigated the cellular origin of each of these three tissue types during regeneration. We produced Xenopus laevis embryos transgenic for the CMV (Simian Cytomegalovirus) promoter driving GFP (Green Fluorescent Protein) ubiquitously throughout the embryo. Single tissues were then specifically labelled by making grafts at the neurula stage from transgenic donors to unlabelled hosts. When the hosts have developed to tadpoles, they carry a region of the appropriate tissue labelled with GFP. These tails were amputated through the labelled region and the distribution of labelled cells in the regenerate was followed. We also labelled myofibres using the Cre-lox method. The results show that the spinal cord and the notochord regenerate from the same tissue type in the stump, with no labelling of other tissues. In the case of the muscle, we show that the myofibres of the regenerate arise from satellite cells and not from the pre-existing myofibres. This shows that metaplasia between differentiated cell types does not occur, and that the process of Xenopus tail regeneration is more akin to tissue renewal in mammals than to urodele tail regeneration.

Volatile profile in the accurate labelling of monofloral honey. The case of lavender and thyme honey.

PubMed

Escriche, Isabel; Sobrino-Gregorio, Lara; Conchado, Andrea; Juan-Borrás, Marisol

2017-07-01

The proliferation of hybrid plant varieties without pollen, such as lavender, has complicated the classification of specific types of honey. This study evaluated the correlation between the proclaimed type of monofloral honey (lavender or thyme) as appears on the label with the actual percentage of pollen. In addition, physicochemical parameters, colour, olfacto-gustatory profile, and volatile compounds were tested. All of the samples labelled as lavender were wrongly classified according to the usual commercial criteria (minimum 10% of pollen Lavandula spp.). In the case of lavender honey, there was significant agreement between commercial labelling and classification through organoleptic perception (81.8%), and above all between the commercial labelling and the volatile compounds (90.9%). For thyme honey, agreement for both parameters was 90.0%. These results offer compelling evidence that the volatile compounds are useful for the classification of lavender honey with low levels of pollen since this technique agrees well with the organoleptic analysis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Semantic Classification of Diseases in Discharge Summaries Using a Context-aware Rule-based Classifier

PubMed Central

Solt, Illés; Tikk, Domonkos; Gál, Viktor; Kardkovács, Zsolt T.

2009-01-01

Objective Automated and disease-specific classification of textual clinical discharge summaries is of great importance in human life science, as it helps physicians to make medical studies by providing statistically relevant data for analysis. This can be further facilitated if, at the labeling of discharge summaries, semantic labels are also extracted from text, such as whether a given disease is present, absent, questionable in a patient, or is unmentioned in the document. The authors present a classification technique that successfully solves the semantic classification task. Design The authors introduce a context-aware rule-based semantic classification technique for use on clinical discharge summaries. The classification is performed in subsequent steps. First, some misleading parts are removed from the text; then the text is partitioned into positive, negative, and uncertain context segments, then a sequence of binary classifiers is applied to assign the appropriate semantic labels. Measurement For evaluation the authors used the documents of the i2b2 Obesity Challenge and adopted its evaluation measures: F1-macro and F1-micro for measurements. Results On the two subtasks of the Obesity Challenge (textual and intuitive classification) the system performed very well, and achieved a F1-macro = 0.80 for the textual and F1-macro = 0.67 for the intuitive tasks, and obtained second place at the textual and first place at the intuitive subtasks of the challenge. Conclusions The authors show in the paper that a simple rule-based classifier can tackle the semantic classification task more successfully than machine learning techniques, if the training data are limited and some semantic labels are very sparse. PMID:19390101

Iris Image Classification Based on Hierarchical Visual Codebook.

PubMed

Zhenan Sun; Hui Zhang; Tieniu Tan; Jianyu Wang

2014-06-01

Iris recognition as a reliable method for personal identification has been well-studied with the objective to assign the class label of each iris image to a unique subject. In contrast, iris image classification aims to classify an iris image to an application specific category, e.g., iris liveness detection (classification of genuine and fake iris images), race classification (e.g., classification of iris images of Asian and non-Asian subjects), coarse-to-fine iris identification (classification of all iris images in the central database into multiple categories). This paper proposes a general framework for iris image classification based on texture analysis. A novel texture pattern representation method called Hierarchical Visual Codebook (HVC) is proposed to encode the texture primitives of iris images. The proposed HVC method is an integration of two existing Bag-of-Words models, namely Vocabulary Tree (VT), and Locality-constrained Linear Coding (LLC). The HVC adopts a coarse-to-fine visual coding strategy and takes advantages of both VT and LLC for accurate and sparse representation of iris texture. Extensive experimental results demonstrate that the proposed iris image classification method achieves state-of-the-art performance for iris liveness detection, race classification, and coarse-to-fine iris identification. A comprehensive fake iris image database simulating four types of iris spoof attacks is developed as the benchmark for research of iris liveness detection.

Cell Kinetic and Histomorphometric Analysis of Microgravitational Osteopenia: PARE.03B

NASA Technical Reports Server (NTRS)

Roberts, W. Eugene; Garetto, Lawrence P.

1998-01-01

Previous methods of identifying cells undergoing DNA synthesis (S-phase) utilized H-3 thymidine (3HT) autoradiography. 5-Bromo-2'-deoxyuridine (BrdU) immunohistochemistry is a nonradioactive alternative method. This experiment compared the two methods using the nuclear volume model for osteoblast histogenesis in two different embedding media. Twenty Sprague-Dawley rats were used, with half receiving 3HT (1 micro Ci/g) and the other half BrdU (50 microgram/g). Condyies were embedded (one side in paraffin, the other in plastic) and S-phase nuclei were identified using either autoradiography or immunohistochemistry. The fractional distribution of preosteoblast cell types and the percentage of labeled cells (within each cell fraction and label index) were calculated and expressed as mean q standard error. Chi-Square analysis showed only a minor difference in the fractional distribution of cell types. However, there were significant differences (p less than 0.05) by ANOVA, in the nuclear labeling of specific cell types. With the exception of the less-differentiated A+A'cells, more BrdU label was consistently detected in paraffin than in plastic-embedded sections. In general, more nuclei were labeled with 3H-thymidine than with BrdU in both types of embedding media. Labeling index data (labeled cells/total cells sampled x 100) indicated that BrdU in paraffin, but not plastic gave the same results as 3HT in either embedding method. Thus, we conclude that the two labeling methods do not yield the same results for the nuclear volume model and that embedding media is an important factor whenusing BrdU. As a result of this work, 3HT was chosen for used in the PARE.03 flight experiments.

Fluorescein-labeled β-Glucosidase as a Bacterial Stain

PubMed Central

Pital, Abe; Janowitz, Sheldon L.; Hudak, Charles E.; Lewis, Evelyn E.

1967-01-01

Fluorescein isothiocyanate-labeled β-glucosidase was used as a simple staining reagent with selected gram-positive and gram-negative organisms. Staining in situ appeared to be dependent on the presence of accessible glycosidic-type linkages in the bacterial cell wall. Extensive wall damage or lysis did not occur when stained cells were suspended in washing and mounting solutions. The apparent specificity of labeled enzyme for wall substance was tested by blocking reactions, staining of isolated cell walls, and failure to stain substances lacking appropriate glycosidic linkages. Severe cell wall lesions were produced after prolonged contact with labeled enzyme, and this phenomenon may also be related to staining specificity. Gram-negative organisms and spores were poorly stained unless protected glycopeptide substrate was previously exposed by treatment of cells with thioglycolic acid or dilute alkaline sodium hypochlorite solution. A potential for staining tissues and cell lines may also exist. Some possible applications of labeled enzymes are briefly discussed. Images Fig. 1 Fig. 2 Fig. 3 Fig. 4 PMID:4169543

In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images.

PubMed

Christiansen, Eric M; Yang, Samuel J; Ando, D Michael; Javaherian, Ashkan; Skibinski, Gaia; Lipnick, Scott; Mount, Elliot; O'Neil, Alison; Shah, Kevan; Lee, Alicia K; Goyal, Piyush; Fedus, William; Poplin, Ryan; Esteva, Andre; Berndl, Marc; Rubin, Lee L; Nelson, Philip; Finkbeiner, Steven

2018-04-19

Microscopy is a central method in life sciences. Many popular methods, such as antibody labeling, are used to add physical fluorescent labels to specific cellular constituents. However, these approaches have significant drawbacks, including inconsistency; limitations in the number of simultaneous labels because of spectral overlap; and necessary perturbations of the experiment, such as fixing the cells, to generate the measurement. Here, we show that a computational machine-learning approach, which we call "in silico labeling" (ISL), reliably predicts some fluorescent labels from transmitted-light images of unlabeled fixed or live biological samples. ISL predicts a range of labels, such as those for nuclei, cell type (e.g., neural), and cell state (e.g., cell death). Because prediction happens in silico, the method is consistent, is not limited by spectral overlap, and does not disturb the experiment. ISL generates biological measurements that would otherwise be problematic or impossible to acquire. Copyright © 2018 Elsevier Inc. All rights reserved.

Espin cytoskeletal proteins in the sensory cells of rodent taste buds

PubMed Central

Sekerková, Gabriella; Freeman, David; Mugnaini, Enrico; Bartles, James R.

2010-01-01

Espins are multifunctional actin-bundling proteins that are highly enriched in the microvilli of certain chemosensory and mechanosensory cells, where they are believed to regulate the integrity and/or dimensions of the parallel-actin-bundle cytoskeletal scaffold. We have determined that, in rats and mice, affinity purified espin antibody intensely labels the lingual and palatal taste buds of the oral cavity and taste buds in the pharyngo-laryngeal region. Intense immunolabeling was observed in the apical, microvillar region of taste buds, while the level of cytoplasmic labeling in taste bud cells was considerably lower. Taste bud cells contain tightly packed collections of sensory cells (light, or type II plus type III) and supporting cells (dark, or type I), which can be distinguished by microscopic features and cell type-specific markers. On the basis of results obtained using an antigen-retrieval method in conjunction with double immunofluorescence for espin and sensory taste cell-specific markers, we propose that espins are expressed predominantly in the sensory cells of rat circumvallate taste buds. In confocal images, we counted 21.5±0.3 espin-positive cells/taste bud, in agreement with a previous report showing 20.7±1.3 light cells/taste bud when counted at the ultrastructural level. The espin antibody labeled spindle-shaped cells with round nuclei and showed 100% colocalization with cell-specific markers recognizing all type II [inositol 1,4,5-trisphosphate receptor type III (IP3R3),α-gustducin, protein-specific gene product 9.5 (PGP9.5)] and a subpopulation of type III (IP3R3, PGP9.5) taste cells. On average, 72%, 50%, and 32% of the espin-positive taste cells were labeled with antibodies to IP3R3, α-gustducin, and PGP9.5, respectively. Upon sectional analysis, the taste buds of rat circumvallate papillae commonly revealed a multi-tiered, espin-positive apical cytoskeletal apparatus. One espin-positive zone, a collection of ~3 μm-long microvilli occupying the taste pore, was separated by an espin-depleted zone from a second espin-positive zone situated lower within the taste pit. This latter zone included espin-positive rod-like structures that occasionally extended basally to a depth of 10-12 μm into the cytoplasm of taste cells. We propose that the espin-positive zone in the taste pit coincides with actin bundles in association with the microvilli of type II taste cells, whereas the espin-positive microvilli in the taste pore are the single microvilli of type III taste cells. PMID:16841162

Dual-process theory and consumer response to front-of-package nutrition label formats.

PubMed

Sanjari, S Setareh; Jahn, Steffen; Boztug, Yasemin

2017-11-01

Nutrition labeling literature yields fragmented results about the effect of front-of-package (FOP) nutrition label formats on healthy food choice. Specifically, it is unclear which type of nutrition label format is effective across different shopping situations. To address this gap, the present review investigates the available nutrition labeling literature through the prism of dual-process theory, which posits that decisions are made either quickly and automatically (system 1) or slowly and deliberately (system 2). A systematically performed review of nutrition labeling literature returned 59 papers that provide findings that can be explained according to dual-process theory. The findings of these studies suggest that the effectiveness of nutrition label formats is influenced by the consumer's dominant processing system, which is a function of specific contexts and personal variables (eg, motivation, nutrition knowledge, time pressure, and depletion). Examination of reported findings through a situational processing perspective reveals that consumers might prefer different FOP nutrition label formats in different situations and can exhibit varying responses to the same label format across situations. This review offers several suggestions for policy makers and researchers to help improve current FOP nutrition label formats. © The Author(s) 2017. Published by Oxford University Press on behalf of the International Life Sciences Institute. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Deformably registering and annotating whole CLARITY brains to an atlas via masked LDDMM

NASA Astrophysics Data System (ADS)

Kutten, Kwame S.; Vogelstein, Joshua T.; Charon, Nicolas; Ye, Li; Deisseroth, Karl; Miller, Michael I.

2016-04-01

The CLARITY method renders brains optically transparent to enable high-resolution imaging in the structurally intact brain. Anatomically annotating CLARITY brains is necessary for discovering which regions contain signals of interest. Manually annotating whole-brain, terabyte CLARITY images is difficult, time-consuming, subjective, and error-prone. Automatically registering CLARITY images to a pre-annotated brain atlas offers a solution, but is difficult for several reasons. Removal of the brain from the skull and subsequent storage and processing cause variable non-rigid deformations, thus compounding inter-subject anatomical variability. Additionally, the signal in CLARITY images arises from various biochemical contrast agents which only sparsely label brain structures. This sparse labeling challenges the most commonly used registration algorithms that need to match image histogram statistics to the more densely labeled histological brain atlases. The standard method is a multiscale Mutual Information B-spline algorithm that dynamically generates an average template as an intermediate registration target. We determined that this method performs poorly when registering CLARITY brains to the Allen Institute's Mouse Reference Atlas (ARA), because the image histogram statistics are poorly matched. Therefore, we developed a method (Mask-LDDMM) for registering CLARITY images, that automatically finds the brain boundary and learns the optimal deformation between the brain and atlas masks. Using Mask-LDDMM without an average template provided better results than the standard approach when registering CLARITY brains to the ARA. The LDDMM pipelines developed here provide a fast automated way to anatomically annotate CLARITY images; our code is available as open source software at http://NeuroData.io.

Heparanase Localization during Palatogenesis in Mice

PubMed Central

Hirata, Azumi; Katayama, Kentaro; Tsuji, Takehito; Natsume, Nagato; Sugahara, Toshio; Koga, Yuichi; Otsuki, Yoshinori; Nakamura, Hiroaki

2013-01-01

Palatogenesis is directed by epithelial-mesenchymal interactions and results partly from remodeling of the extracellular matrix (ECM) of the palatal shelves. Here, we assessed heparanase distribution in developing mouse palates. No heparanase was observed in the vertically oriented palatal shelves in early stages of palate formation. As palate formation progressed, the palatal shelves were reorganized and arranged horizontally above the tongue, and heparanase localized to the epithelial cells of these shelves. When the palatal bilateral shelves first made contact, the heparanase localized to epithelial cells at the tips of shelves. Later in fusing palatal shelves, the cells of the medial epithelial seam (MES) were labeled with intense heparanase signal. In contrast, the basement membrane heparan sulfate (HS) was scarcely observed in the palatal shelves in contact. Moreover, perlecan labeling was sparse in the basement membrane of the MES, on which laminin and type IV collagen were observed. Moreover, we assessed the distribution of matrix metalloproteinase- (MMP-) 9, MMP-2, and MMP-3 in developing mouse palates and these MMPs were observed in the MES. Our findings indicated that heparanase was important for palate formation because it mediated degradation of the ECM of palatal shelves. Heparanase may, in concert with other proteases, participate in the regression of the MES. PMID:23509775

Off-label prescribing for children with chronic diseases in Nigeria; findings and implications.

PubMed

Oshikoya, Kazeem Adeola; Oreagba, Ibrahim Adekunle; Godman, Brian; Fadare, Joseph; Orubu, Samuel; Massele, Amos; Senbanjo, Idowu Odunayo

2017-09-01

Prescribing medicines in an off-label manner for children with chronic conditions is sparsely documented, even more so among developing countries. This needs addressing. The objective of this research was to investigate the extent of off-label prescribing among children with epilepsy, asthma, and sickle cell anaemia in Nigeria. Prescriptions for children ≤16 years documented in their case files that attended paediatric clinics in Lagos, Nigeria, for these three conditions between January and October 2015, were reviewed retrospectively to extract data on the medicines prescribed. British National Formulary for children and American Hospital Formulary Service Drug information were used as references. 477 patients received 1746 prescriptions. Off-label prescriptions were seen in 7.7% of prescriptions, related to dose (93; 68.9%), indication (22; 16.3%), and age (20; 14.8%). Nervous system (525; 30.1%) and anti-infective (441; 25.2%) medicines were the most prescribed but only 9.5% and 8.2% of the respective prescriptions were off-label. Children with epilepsy received the most number (94; 69.6%) of off-label prescriptions. The three chronic conditions did not associate significantly with the category of off-label medicine prescribed (p = 0.925). Off-label prescribing for children with epilepsy, asthma and sickle cell anaemia occurs. Encouragingly, the overall rate appears low in Nigeria.

Use of direct fluorescence labeling and confocal microscopy to determine the biodistribution of two protein therapeutics, Cerezyme and Ceredase.

PubMed

Piepenhagen, Peter A; Vanpatten, Scott; Hughes, Heather; Waire, James; Murray, James; Andrews, Laura; Edmunds, Tim; O'Callaghan, Michael; Thurberg, Beth L

2010-07-01

Efficient targeting of therapeutic reagents to tissues and cell types of interest is critical to achieving therapeutic efficacy and avoiding unwanted side effects due to offtarget uptake. To increase assay efficiency and reduce the number of animals used per experiment during preclinical development, we used a combination of direct fluorescence labeling and confocal microscopy to simultaneously examine the biodistribution of two therapeutic proteins, Cerezyme and Ceredase, in the same animals. We show that the fluorescent tags do not interfere with protein uptake and localization. We are able to detect Cerezyme and Ceredase in intact cells and organs and demonstrate colocalization within target cells using confocal microscopy. In addition, the relative amount of protein internalized by different cell types can be quantified using cell type-specific markers and morphometric analysis. This approach provides an easy and straightforward means of assessing the tissue and cell type-specific biodistribution of multiple protein therapeutics in target organs using a minimal number of animals. (c) 2009 Wiley-Liss, Inc.

Deformable MR Prostate Segmentation via Deep Feature Learning and Sparse Patch Matching

PubMed Central

Guo, Yanrong; Gao, Yaozong

2016-01-01

Automatic and reliable segmentation of the prostate is an important but difficult task for various clinical applications such as prostate cancer radiotherapy. The main challenges for accurate MR prostate localization lie in two aspects: (1) inhomogeneous and inconsistent appearance around prostate boundary, and (2) the large shape variation across different patients. To tackle these two problems, we propose a new deformable MR prostate segmentation method by unifying deep feature learning with the sparse patch matching. First, instead of directly using handcrafted features, we propose to learn the latent feature representation from prostate MR images by the stacked sparse auto-encoder (SSAE). Since the deep learning algorithm learns the feature hierarchy from the data, the learned features are often more concise and effective than the handcrafted features in describing the underlying data. To improve the discriminability of learned features, we further refine the feature representation in a supervised fashion. Second, based on the learned features, a sparse patch matching method is proposed to infer a prostate likelihood map by transferring the prostate labels from multiple atlases to the new prostate MR image. Finally, a deformable segmentation is used to integrate a sparse shape model with the prostate likelihood map for achieving the final segmentation. The proposed method has been extensively evaluated on the dataset that contains 66 T2-wighted prostate MR images. Experimental results show that the deep-learned features are more effective than the handcrafted features in guiding MR prostate segmentation. Moreover, our method shows superior performance than other state-of-the-art segmentation methods. PMID:26685226

Brief announcement: Hypergraph parititioning for parallel sparse matrix-matrix multiplication

DOE PAGES

Ballard, Grey; Druinsky, Alex; Knight, Nicholas; ...

2015-01-01

The performance of parallel algorithms for sparse matrix-matrix multiplication is typically determined by the amount of interprocessor communication performed, which in turn depends on the nonzero structure of the input matrices. In this paper, we characterize the communication cost of a sparse matrix-matrix multiplication algorithm in terms of the size of a cut of an associated hypergraph that encodes the computation for a given input nonzero structure. Obtaining an optimal algorithm corresponds to solving a hypergraph partitioning problem. Furthermore, our hypergraph model generalizes several existing models for sparse matrix-vector multiplication, and we can leverage hypergraph partitioners developed for that computationmore » to improve application-specific algorithms for multiplying sparse matrices.« less

Joint Patch and Multi-label Learning for Facial Action Unit Detection

PubMed Central

Zhao, Kaili; Chu, Wen-Sheng; De la Torre, Fernando; Cohn, Jeffrey F.; Zhang, Honggang

2016-01-01

The face is one of the most powerful channel of nonverbal communication. The most commonly used taxonomy to describe facial behaviour is the Facial Action Coding System (FACS). FACS segments the visible effects of facial muscle activation into 30+ action units (AUs). AUs, which may occur alone and in thousands of combinations, can describe nearly all-possible facial expressions. Most existing methods for automatic AU detection treat the problem using one-vs-all classifiers and fail to exploit dependencies among AU and facial features. We introduce joint-patch and multi-label learning (JPML) to address these issues. JPML leverages group sparsity by selecting a sparse subset of facial patches while learning a multi-label classifier. In four of five comparisons on three diverse datasets, CK+, GFT, and BP4D, JPML produced the highest average F1 scores in comparison with state-of-the art. PMID:27382243

Unified commutation-pruning technique for efficient computation of composite DFTs

NASA Astrophysics Data System (ADS)

Castro-Palazuelos, David E.; Medina-Melendrez, Modesto Gpe.; Torres-Roman, Deni L.; Shkvarko, Yuriy V.

2015-12-01

An efficient computation of a composite length discrete Fourier transform (DFT), as well as a fast Fourier transform (FFT) of both time and space data sequences in uncertain (non-sparse or sparse) computational scenarios, requires specific processing algorithms. Traditional algorithms typically employ some pruning methods without any commutations, which prevents them from attaining the potential computational efficiency. In this paper, we propose an alternative unified approach with automatic commutations between three computational modalities aimed at efficient computations of the pruned DFTs adapted for variable composite lengths of the non-sparse input-output data. The first modality is an implementation of the direct computation of a composite length DFT, the second one employs the second-order recursive filtering method, and the third one performs the new pruned decomposed transform. The pruned decomposed transform algorithm performs the decimation in time or space (DIT) data acquisition domain and, then, decimation in frequency (DIF). The unified combination of these three algorithms is addressed as the DFTCOMM technique. Based on the treatment of the combinational-type hypotheses testing optimization problem of preferable allocations between all feasible commuting-pruning modalities, we have found the global optimal solution to the pruning problem that always requires a fewer or, at most, the same number of arithmetic operations than other feasible modalities. The DFTCOMM method outperforms the existing competing pruning techniques in the sense of attainable savings in the number of required arithmetic operations. It requires fewer or at most the same number of arithmetic operations for its execution than any other of the competing pruning methods reported in the literature. Finally, we provide the comparison of the DFTCOMM with the recently developed sparse fast Fourier transform (SFFT) algorithmic family. We feature that, in the sensing scenarios with sparse/non-sparse data Fourier spectrum, the DFTCOMM technique manifests robustness against such model uncertainties in the sense of insensitivity for sparsity/non-sparsity restrictions and the variability of the operating parameters.

Inverse problems with nonnegative and sparse solutions: algorithms and application to the phase retrieval problem

NASA Astrophysics Data System (ADS)

Quy Muoi, Pham; Nho Hào, Dinh; Sahoo, Sujit Kumar; Tang, Dongliang; Cong, Nguyen Huu; Dang, Cuong

2018-05-01

In this paper, we study a gradient-type method and a semismooth Newton method for minimization problems in regularizing inverse problems with nonnegative and sparse solutions. We propose a special penalty functional forcing the minimizers of regularized minimization problems to be nonnegative and sparse, and then we apply the proposed algorithms in a practical the problem. The strong convergence of the gradient-type method and the local superlinear convergence of the semismooth Newton method are proven. Then, we use these algorithms for the phase retrieval problem and illustrate their efficiency in numerical examples, particularly in the practical problem of optical imaging through scattering media where all the noises from experiment are presented.

Practical cell labeling with magnetite cationic liposomes for cell manipulation.

PubMed

Ito, Hiroshi; Nonogaki, Yurika; Kato, Ryuji; Honda, Hiroyuki

2010-07-01

Personalization of the cell culture process for cell therapy is an ideal strategy to obtain maximum treatment effects. In a previous report, we proposed a strategy using a magnetic manipulation device that combined a palm-top size device and a cell-labeling method using magnetite cationic liposomes (MCLs) to enable feasible personalized cell processing. In the present study, we focused on optimizing the MCL-labeling technique with respect to cell manipulation in small devices. From detailed analysis with different cell types, 4 pg/cell of MCL-label was found to be obtained immediately after mixing with MCLs, which was sufficient for magnetic cell manipulation. The amount of label increased within 24 h depending on cell type, although in all cases it decreased along with cell doubling, indicating that the labeling potential of MCLs was limited. The role of free MCLs not involved in labeling was also investigated; MCLs' role was found to be a supportive one that maximized the manipulation performance up to 100%. We also determined optimum conditions to manipulate adherent cells by MCL labeling using the MCL dispersed in trypsin solution. Considering labeling feasibility and practical performance with 10(3)-10(5) cells for personalized cell processing, we determined that 10 microg/ml of label without incubation time (0 h incubation) was the universal MCL-labeling condition. We propose the optimum specifications for a device to be combined with this method. 2010. Published by Elsevier B.V.

The Influence of Nutrition Labeling and Point-of-Purchase Information on Food Behaviours.

PubMed

Volkova, Ekaterina; Ni Mhurchu, Cliona

2015-03-01

Point-of-purchase information on packaged food has been a highly debated topic. Various types of nutrition labels and point-of-purchase information have been studied to determine their ability to attract consumers' attention, be well understood and promote healthy food choices. Country-specific regulatory and monitoring frameworks have been implemented to ensure reliability and accuracy of such information. However, the impact of such information on consumers' behaviour remains contentious. This review summarizes recent evidence on the real-world effectiveness of nutrition labels and point-of-purchase information.

Analysis of lymphopoietic stem cells with a monoclonal antibody to the rat transferrin receptor.

PubMed Central

Jefferies, W A; Brandon, M R; Williams, A F; Hunt, S V

1985-01-01

A mouse monoclonal IgG2a antibody, designated MRC OX-26, is shown to be specific for the rat transferrin receptor, but does not block transferrin binding. The antibody labelled a myeloma, three leukaemia cell lines and normal dividing cells of various types, but also bound to a number of nondividing normal tissues. No labelling of lymphopoietic stem cells could be detected, even though approximately 25% of bone marrow and over 95% of fetal liver cells were clearly labelled. Images Figure 1 Figure 3 PMID:2981766

Formal Recognition of the Species of the Anopheles Maculatus Group (Diptera: Culicidae) Occurring in Thailand, Including the Descriptions of Two New Species and a Preliminary Key to Females

DTIC Science & Technology

1986-01-01

Theobald, 1903 ~Nyssorhynchus). Change to subspecific rank by Christophers, 1931. RESTORED TO SPECIFIC RANK. maculosa James and Liston, 1903 (NeoceZ...single specimen in the BM bearing four labels with the following information: ’? Type or paratype/S.P.C//Willmori/var/ maculosa //This is labelled by

Duke Workshop on High-Dimensional Data Sensing and Analysis

DTIC Science & Technology

2015-05-06

Bayesian sparse factor analysis formulation of Chen et al . ( 2011 ) this work develops multi-label PCA (MLPCA), a generative dimension reduction...version of this problem was recently treated by Banerjee et al . [1], Ravikumar et al . [2], Kolar and Xing [3], and Ho ̈fling and Tibshirani [4]. As...Not applicable. Final Report Duke Workshop on High-Dimensional Data Sensing and Analysis Workshop Dates: July 26-28, 2011

Testing of Error-Correcting Sparse Permutation Channel Codes

NASA Technical Reports Server (NTRS)

Shcheglov, Kirill, V.; Orlov, Sergei S.

2008-01-01

A computer program performs Monte Carlo direct numerical simulations for testing sparse permutation channel codes, which offer strong error-correction capabilities at high code rates and are considered especially suitable for storage of digital data in holographic and volume memories. A word in a code of this type is characterized by, among other things, a sparseness parameter (M) and a fixed number (K) of 1 or "on" bits in a channel block length of N.

A catalog of the types of Staphylinidae (Insecta, Coleoptera) deposited in the Museo Argentino de Ciencias Naturales, Buenos Aires (MACN).

PubMed

Bachmann, Axel O; Chani-Posse, Mariana; Guala, Mariel E; Newton, Alfred F

2017-01-22

The type specimens (all current categories) of Staphylinidae deposited in this Museum are listed; names are recorded, most of them represented by name-bearing types (primary types). The specific and subspecific names are alphabetically ordered in a single list, followed by the generic names (and subgeneric ones, if they were stated) spelled as they were published; later combinations and/ or current binomina are mentioned insofar these are known to the authors. Two lists are added: 2. Specimens labeled as types of names not found in the literature and probably never published, or published as nomina nuda; and 3. Specimens labeled as types, but not originally designated as such. An appendix provides a systematically arranged list of all names discussed, with indication of where they are discussed in the text.

Sparsely sampling the sky: Regular vs. random sampling

NASA Astrophysics Data System (ADS)

Paykari, P.; Pires, S.; Starck, J.-L.; Jaffe, A. H.

2015-09-01

Aims: The next generation of galaxy surveys, aiming to observe millions of galaxies, are expensive both in time and money. This raises questions regarding the optimal investment of this time and money for future surveys. In a previous work, we have shown that a sparse sampling strategy could be a powerful substitute for the - usually favoured - contiguous observation of the sky. In our previous paper, regular sparse sampling was investigated, where the sparse observed patches were regularly distributed on the sky. The regularity of the mask introduces a periodic pattern in the window function, which induces periodic correlations at specific scales. Methods: In this paper, we use a Bayesian experimental design to investigate a "random" sparse sampling approach, where the observed patches are randomly distributed over the total sparsely sampled area. Results: We find that in this setting, the induced correlation is evenly distributed amongst all scales as there is no preferred scale in the window function. Conclusions: This is desirable when we are interested in any specific scale in the galaxy power spectrum, such as the matter-radiation equality scale. As the figure of merit shows, however, there is no preference between regular and random sampling to constrain the overall galaxy power spectrum and the cosmological parameters.

The Non-Specific Binding of Fluorescent-Labeled MiRNAs on Cell Surface by Hydrophobic Interaction.

PubMed

Lu, Ting; Lin, Zongwei; Ren, Jianwei; Yao, Peng; Wang, Xiaowei; Wang, Zhe; Zhang, Qunye

2016-01-01

MicroRNAs are small noncoding RNAs about 22 nt long that play key roles in almost all biological processes and diseases. The fluorescent labeling and lipofection are two common methods for changing the levels and locating the position of cellular miRNAs. Despite many studies about the mechanism of DNA/RNA lipofection, little is known about the characteristics, mechanisms and specificity of lipofection of fluorescent-labeled miRNAs. Therefore, miRNAs labeled with different fluorescent dyes were transfected into adherent and suspension cells using lipofection reagent. Then, the non-specific binding and its mechanism were investigated by flow cytometer and laser confocal microscopy. The results showed that miRNAs labeled with Cy5 (cyanine fluorescent dye) could firmly bind to the surface of adherent cells (Hela) and suspended cells (K562) even without lipofection reagent. The binding of miRNAs labeled with FAM (carboxyl fluorescein) to K562 cells was obvious, but it was not significant in Hela cells. After lipofectamine reagent was added, most of the fluorescently labeled miRNAs binding to the surface of Hela cells were transfected into intra-cell because of the high transfection efficiency, however, most of them were still binding to the surface of K562 cells. Moreover, the high-salt buffer which could destroy the electrostatic interactions did not affect the above-mentioned non-specific binding, but the organic solvent which could destroy the hydrophobic interactions eliminated it. These results implied that the fluorescent-labeled miRNAs could non-specifically bind to the cell surface by hydrophobic interaction. It would lead to significant errors in the estimation of transfection efficiency only according to the cellular fluorescence intensity. Therefore, other methods to evaluate the transfection efficiency and more appropriate fluorescent dyes should be used according to the cell types for the accuracy of results.

46 CFR 160.040-6 - Marking and labeling.

Code of Federal Regulations, 2013 CFR

2013-10-01

...: SPECIFICATIONS AND APPROVAL LIFESAVING EQUIPMENT Line-Throwing Appliance, Impulse-Projected Rocket Type (and... rocket-projectiles shall be legibly marked with the name of the manufacturer, the model designation, the...

46 CFR 160.040-6 - Marking and labeling.

Code of Federal Regulations, 2011 CFR

2011-10-01

...: SPECIFICATIONS AND APPROVAL LIFESAVING EQUIPMENT Line-Throwing Appliance, Impulse-Projected Rocket Type (and... rocket-projectiles shall be legibly marked with the name of the manufacturer, the model designation, the...

46 CFR 160.040-6 - Marking and labeling.

Code of Federal Regulations, 2014 CFR

2014-10-01

...: SPECIFICATIONS AND APPROVAL LIFESAVING EQUIPMENT Line-Throwing Appliance, Impulse-Projected Rocket Type (and... rocket-projectiles shall be legibly marked with the name of the manufacturer, the model designation, the...

46 CFR 160.040-6 - Marking and labeling.

Code of Federal Regulations, 2012 CFR

2012-10-01

...: SPECIFICATIONS AND APPROVAL LIFESAVING EQUIPMENT Line-Throwing Appliance, Impulse-Projected Rocket Type (and... rocket-projectiles shall be legibly marked with the name of the manufacturer, the model designation, the...

46 CFR 160.040-6 - Marking and labeling.

Code of Federal Regulations, 2010 CFR

2010-10-01

...: SPECIFICATIONS AND APPROVAL LIFESAVING EQUIPMENT Line-Throwing Appliance, Impulse-Projected Rocket Type (and... rocket-projectiles shall be legibly marked with the name of the manufacturer, the model designation, the...

Vagal innervation of the aldosterone-sensitive HSD2 neurons in the NTS

PubMed Central

Shin, Jung-Won; Geerling, Joel C.; Loewy, Arthur D.

2009-01-01

The nucleus of the solitary tract (NTS) contains a unique subpopulation of aldosterone-sensitive neurons. These neurons express the enzyme 11-β-hydroxysteroid dehydrogenase type 2 (HSD2) and are activated by sodium deprivation. They are located in the caudal NTS, a region which is densely innervated by the vagus nerve, suggesting that they could receive direct viscerosensory input from the periphery. To test this possibility, we injected the highly sensitive axonal tracer biotinylated dextran amine (BDA) into the left nodose ganglion in rats. Using confocal microscopy, we observed a sparse input from the vagus to most HSD2 neurons. Roughly 80% of the ipsilateral HSD2 neurons exhibited at least one close contact with a BDA-labeled vagal bouton, although most of these cells received only a few total contacts. Most of these contacts were axo-dendritic (~80%), while ~20% were axo-somatic. In contrast, the synaptic vesicular transporters VGLUT2 or GAD7 labeled much larger populations of boutons contacting HSD2-labeled dendrites and somata, suggesting that direct input from the vagus may only account for a minority of the information integrated by these neurons. In summary, the aldosterone-sensitive HSD2 neurons in the NTS appear to receive a small amount of direct viscerosensory input from the vagus nerve. The peripheral sites of origin and functional significance of this projection remain unknown. Combined with previously-identified central sources of input to these cells, the present finding indicates that the HSD2 neurons integrate humoral information with input from a variety of neural afferents. PMID:19010311

The impact of front-of-pack nutrition labels on consumer product evaluation and choice: an experimental study.

PubMed

Hamlin, Robert P; McNeill, Lisa S; Moore, Vanessa

2015-08-01

The present research was an experimental test that aimed to quantify the impact of two dominant front-of-pack (FOP) nutritional label formats on consumer evaluations of food products that carried them. The two FOP label types tested were the traffic light label and the Percentage Daily Intake. A 4×5 partially replicated Latin square design was used that allowed the impact of the FOP labels to be isolated from the effects of the product and the consumers who were performing the evaluations. The experiment was conducted on campus at the University of Otago, New Zealand. The participants were 250 university students selected at random who met qualifying criteria of independent living and regular purchase of the products used in the research. They were not aware of the purpose of the research. The presence of FOP labels led to significant and positive changes in consumer purchase intentions towards the products that carried them. These changes were not affected by the nature of FOP labels used, their size or the product nutritional status (good/bad) that they were reporting. The result is consistent with the participants paying attention to the FOP label and then using it as an adimensional cue indicating product desirability. As such, it represents a complete functional failure of both of these FOP label types in this specific instance. This result supports calls for further research on the performance of these FOP labels before any move to compulsory deployment is made.

Local structure preserving sparse coding for infrared target recognition

PubMed Central

Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lianfa

2017-01-01

Sparse coding performs well in image classification. However, robust target recognition requires a lot of comprehensive template images and the sparse learning process is complex. We incorporate sparsity into a template matching concept to construct a local sparse structure matching (LSSM) model for general infrared target recognition. A local structure preserving sparse coding (LSPSc) formulation is proposed to simultaneously preserve the local sparse and structural information of objects. By adding a spatial local structure constraint into the classical sparse coding algorithm, LSPSc can improve the stability of sparse representation for targets and inhibit background interference in infrared images. Furthermore, a kernel LSPSc (K-LSPSc) formulation is proposed, which extends LSPSc to the kernel space to weaken the influence of the linear structure constraint in nonlinear natural data. Because of the anti-interference and fault-tolerant capabilities, both LSPSc- and K-LSPSc-based LSSM can implement target identification based on a simple template set, which just needs several images containing enough local sparse structures to learn a sufficient sparse structure dictionary of a target class. Specifically, this LSSM approach has stable performance in the target detection with scene, shape and occlusions variations. High performance is demonstrated on several datasets, indicating robust infrared target recognition in diverse environments and imaging conditions. PMID:28323824

Evidence for carboxyl-terminal processing and glycolipid-anchoring of human carcinoembryonic antigen.

PubMed

Takami, N; Misumi, Y; Kuroki, M; Matsuoka, Y; Ikehara, Y

1988-09-05

We have investigated the post-translational modification of carcinoembryonic antigen (CEA) for membrane-anchoring in QGP-1 cells derived from a human pancreatic carcinoma. Pulse-chase experiments with [3H]leucine demonstrated that CEA was initially synthesized as a precursor form with Mr 150,000 having N-linked high-mannose-type oligosaccharides, which was then converted to a mature form with Mr 200,000 containing the complex type sugar chains. The mature protein thus labeled was found to be released from the cell surface by treatment with phosphatidylinositol-specific phospholipase C, suggesting that CEA is a phosphatidylinositol-linked membrane protein. This was confirmed by metabolic incorporation into CEA of 3H-labeled compounds such as ethanolamine, myo-inositol, palmitic acid, and stearic acid. The 3H-labeled fatty acids incorporated were specifically removed from the protein by nitrous acid deamination as well as by phosphatidylinositol-specific phospholipase C treatment. Since the available cDNA sequence predicts that CEA contains a single methionine residue only in its carboxyl-terminal hydrophobic domain, processing of the carboxyl terminus was examined by pulse-chase experiments with [35S]methionine. It was found that CEA with Mr 150,000 was initially labeled with [35S]methionine but its radioactivity was immediately lost with chase. Taken together, these results suggest that CEA is anchored to the membrane by simultaneously occurring proteolysis of the carboxyl terminus and replacement by the glycophospholipid immediately after the synthesis.

Chemical Topography of Efferent Projections from the Median Preoptic Nucleus to Pontine Monoaminergic Cell Groups in the Rat

NASA Technical Reports Server (NTRS)

Zardetto-Smith, Andrea M.; Johnson, Alan Kim

1995-01-01

This study examined efferent output from the median preoptic nucleus (MNPO) to pontine noradrenergic and serotonergic cell groups using an anterograde tracing technique (Phaseolus vulgaris leucoagglutinin, PHA-L) combined with glucose oxidase immunocytochemistry to serotonin (5-HT) or to dopamine-beta-hydroxylase (DBH). Injections of PHA-L into the ventral MNPO resulted in moderate axonal labeling within the region of the B7 and B8 serotonergic groups in the dorsal raphe. PHA-L labeled fibers and punctate processes were observed in close apposition to many of the 5-HT immunoreactive neurons in these regions. In contrast, sparse terminal labeling was found within the B5 group in the raphe pontis nucleus, and only trace fiber labeling observed in the B3 and B6 groups. Efferents from the MNPO also provided moderate innervation to the A6 and A7 noradrenergic groups. PHA-L labeled punctate processes were found most frequently in close apposition to DBH-immunoreactive neurons at mid- to caudal levels of the locus coeruleus. Some labeled axons were also present within the A7 and A5 groups. Additionally, a close apposition between labeled MNPO efferents and 5-HT fibers within the lateral parabrachial nucleus was observed. The results indicate the MNPO provides a topographic innervation of monoaminergic groups in the upper brainstem.

Chemical Topography of Efferent Projections from the Median Preoptic Nucleus to Pontine Monoaminergic Cell Groups in the Rat

NASA Technical Reports Server (NTRS)

Zardetto-Smith, Andrea M.; Johnson, Alan Kim

1995-01-01

This study examined efferent output from the median preoptic nucleus (MnPO) to pontine noradrenergic and serotonergic cell groups using an anterograde tracing technique (Phaseolus vulgaris leucoagglutinin, PHA-L) combined with glucose oxidase immunocytochemistry to scrotonin (5-HT) or to dopamine-(beta)-hydroxylase (DBH). Injections of PHA-L into the ventral MNPO resulted in moderate axonal labeling within the region of the B7 and B8 serotonergic groups in the dorsal raphe. PHA-L labeled fibers and punctate processes were observed in close apposition to many of the 5-HT immunoreactive neurons in these regions, In contrast, sparse terminal labeling was found within the B5 group in the raphe pontis nucleus, and only trace fiber labeling observed in the B3 and B6 groups. Efferents from the MNPO also provided moderate innervation to the A6 and A7 noradrenergic groups. PHA-L labeled punctate processes were found most frequently in close apposition to DBH-immunorcactive neurons at mid- to caudal levels of the locus coeruleus. Some labeled axons were also present within the A7 and A5 groups. Additionally, a close apposition between labeled MNPO efferents and 5-HT fibers within the lateral parabrachial nucleus was observed, The results indicate the MNPO provides a topographic innerva- tion of monoaminergic groups in the upper brainstem.

Lectin histochemistry of the rat lymph node: visualisation of stroma, blood vessels, sinuses, and macrophages. A contribution to the concept of an immune accessory role of sinus-lining endothelia.

PubMed

Düllmann, Jochen; Van Damme, Els J M; Peumans, Willy J; Ziesenitz, Maike; Schumacher, Udo

2002-01-01

The lectin Chelidonium majus agglutinin (CMA) was previously shown to visualise endothelia of all blood vessels and those lining sinuses of red pulp, stromal reticular meshwok (RM) and dendritic cells of lymphatic follicles in white pulp of the spleen in rats. The aim of the present study was the analysis of CMA and some other lectins in labelling RM, vascular structures and macrophages in lymph nodes of rats. It appeared that CMA stained the entire RM, dendritic cells, lining cells of sinuses and all types of blood vessels. Sinus-lining cells of lymph nodes were labelled with CMA and mannose-, GalNac-, and sialic acid-specific lectins. Moreover, lymph node macrophages were labelled above all by mannose specific lectins. The broad lectin-binding pattern of sinuses--not observed in rat spleen- and CMA-reactivity of both sinus-lining and dendritic cells corroborates the hypothesis that lymph node sinus-lining endothelia are precursors or a special type of immune accessory cells.

Nonparametric, Coupled ,Bayesian ,Dictionary ,and Classifier Learning for Hyperspectral Classification.

PubMed

Akhtar, Naveed; Mian, Ajmal

2017-10-03

We present a principled approach to learn a discriminative dictionary along a linear classifier for hyperspectral classification. Our approach places Gaussian Process priors over the dictionary to account for the relative smoothness of the natural spectra, whereas the classifier parameters are sampled from multivariate Gaussians. We employ two Beta-Bernoulli processes to jointly infer the dictionary and the classifier. These processes are coupled under the same sets of Bernoulli distributions. In our approach, these distributions signify the frequency of the dictionary atom usage in representing class-specific training spectra, which also makes the dictionary discriminative. Due to the coupling between the dictionary and the classifier, the popularity of the atoms for representing different classes gets encoded into the classifier. This helps in predicting the class labels of test spectra that are first represented over the dictionary by solving a simultaneous sparse optimization problem. The labels of the spectra are predicted by feeding the resulting representations to the classifier. Our approach exploits the nonparametric Bayesian framework to automatically infer the dictionary size--the key parameter in discriminative dictionary learning. Moreover, it also has the desirable property of adaptively learning the association between the dictionary atoms and the class labels by itself. We use Gibbs sampling to infer the posterior probability distributions over the dictionary and the classifier under the proposed model, for which, we derive analytical expressions. To establish the effectiveness of our approach, we test it on benchmark hyperspectral images. The classification performance is compared with the state-of-the-art dictionary learning-based classification methods.

Boosting multi-state models.

PubMed

Reulen, Holger; Kneib, Thomas

2016-04-01

One important goal in multi-state modelling is to explore information about conditional transition-type-specific hazard rate functions by estimating influencing effects of explanatory variables. This may be performed using single transition-type-specific models if these covariate effects are assumed to be different across transition-types. To investigate whether this assumption holds or whether one of the effects is equal across several transition-types (cross-transition-type effect), a combined model has to be applied, for instance with the use of a stratified partial likelihood formulation. Here, prior knowledge about the underlying covariate effect mechanisms is often sparse, especially about ineffectivenesses of transition-type-specific or cross-transition-type effects. As a consequence, data-driven variable selection is an important task: a large number of estimable effects has to be taken into account if joint modelling of all transition-types is performed. A related but subsequent task is model choice: is an effect satisfactory estimated assuming linearity, or is the true underlying nature strongly deviating from linearity? This article introduces component-wise Functional Gradient Descent Boosting (short boosting) for multi-state models, an approach performing unsupervised variable selection and model choice simultaneously within a single estimation run. We demonstrate that features and advantages in the application of boosting introduced and illustrated in classical regression scenarios remain present in the transfer to multi-state models. As a consequence, boosting provides an effective means to answer questions about ineffectiveness and non-linearity of single transition-type-specific or cross-transition-type effects.

Exhaustive Search for Sparse Variable Selection in Linear Regression

NASA Astrophysics Data System (ADS)

Igarashi, Yasuhiko; Takenaka, Hikaru; Nakanishi-Ohno, Yoshinori; Uemura, Makoto; Ikeda, Shiro; Okada, Masato

2018-04-01

We propose a K-sparse exhaustive search (ES-K) method and a K-sparse approximate exhaustive search method (AES-K) for selecting variables in linear regression. With these methods, K-sparse combinations of variables are tested exhaustively assuming that the optimal combination of explanatory variables is K-sparse. By collecting the results of exhaustively computing ES-K, various approximate methods for selecting sparse variables can be summarized as density of states. With this density of states, we can compare different methods for selecting sparse variables such as relaxation and sampling. For large problems where the combinatorial explosion of explanatory variables is crucial, the AES-K method enables density of states to be effectively reconstructed by using the replica-exchange Monte Carlo method and the multiple histogram method. Applying the ES-K and AES-K methods to type Ia supernova data, we confirmed the conventional understanding in astronomy when an appropriate K is given beforehand. However, we found the difficulty to determine K from the data. Using virtual measurement and analysis, we argue that this is caused by data shortage.

Subcellular distribution of glutathione and its dynamic changes under oxidative stress in the yeast Saccharomyces cerevisiae

PubMed Central

Zechmann, Bernd; Liou, Liang-Chun; Koffler, Barbara E; Horvat, Lucija; Tomašić, Ana; Fulgosi, Hrvoje; Zhang, Zhaojie

2011-01-01

Glutathione is an important antioxidant in most prokaryotes and eukaryotes. It detoxifies reactive oxygen species and is also involved in the modulation of gene expression, in redox signaling, and in the regulation of enzymatic activities. In this study, the subcellular distribution of glutathione was studied in Saccharomyces cerevisiae by quantitative immunoelectron microscopy. Highest glutathione contents were detected in mitochondria and subsequently in the cytosol, nuclei, cell walls, and vacuoles. The induction of oxidative stress by hydrogen peroxide (H2O2) led to changes in glutathione-specific labeling. Three cell types were identified. Cell types I and II contained more glutathione than control cells. Cell type II differed from cell type I in showing a decrease in glutathione-specific labeling solely in mitochondria. Cell type III contained much less glutathione contents than the control and showed the strongest decrease in mitochondria, suggesting that high and stable levels of glutathione in mitochondria are important for the protection and survival of the cells during oxidative stress. Additionally, large amounts of glutathione were relocated and stored in vacuoles in cell type III, suggesting the importance of the sequestration of glutathione in vacuoles under oxidative stress. PMID:22093747

Quantification of localized vertebral deformities using a sparse wavelet-based shape model.

PubMed

Zewail, R; Elsafi, A; Durdle, N

2008-01-01

Medical experts often examine hundreds of spine x-ray images to determine existence of various pathologies. Common pathologies of interest are anterior osteophites, disc space narrowing, and wedging. By careful inspection of the outline shapes of the vertebral bodies, experts are able to identify and assess vertebral abnormalities with respect to the pathology under investigation. In this paper, we present a novel method for quantification of vertebral deformation using a sparse shape model. Using wavelets and Independent component analysis (ICA), we construct a sparse shape model that benefits from the approximation power of wavelets and the capability of ICA to capture higher order statistics in wavelet space. The new model is able to capture localized pathology-related shape deformations, hence it allows for quantification of vertebral shape variations. We investigate the capability of the model to predict localized pathology related deformations. Next, using support-vector machines, we demonstrate the diagnostic capabilities of the method through the discrimination of anterior osteophites in lumbar vertebrae. Experiments were conducted using a set of 150 contours from digital x-ray images of lumbar spine. Each vertebra is labeled as normal or abnormal. Results reported in this work focus on anterior osteophites as the pathology of interest.

A Modified Sparse Representation Method for Facial Expression Recognition.

PubMed

Wang, Wei; Xu, LiHong

2016-01-01

In this paper, we carry on research on a facial expression recognition method, which is based on modified sparse representation recognition (MSRR) method. On the first stage, we use Haar-like+LPP to extract feature and reduce dimension. On the second stage, we adopt LC-K-SVD (Label Consistent K-SVD) method to train the dictionary, instead of adopting directly the dictionary from samples, and add block dictionary training into the training process. On the third stage, stOMP (stagewise orthogonal matching pursuit) method is used to speed up the convergence of OMP (orthogonal matching pursuit). Besides, a dynamic regularization factor is added to iteration process to suppress noises and enhance accuracy. We verify the proposed method from the aspect of training samples, dimension, feature extraction and dimension reduction methods and noises in self-built database and Japan's JAFFE and CMU's CK database. Further, we compare this sparse method with classic SVM and RVM and analyze the recognition effect and time efficiency. The result of simulation experiment has shown that the coefficient of MSRR method contains classifying information, which is capable of improving the computing speed and achieving a satisfying recognition result.

A Modified Sparse Representation Method for Facial Expression Recognition

PubMed Central

Wang, Wei; Xu, LiHong

2016-01-01

In this paper, we carry on research on a facial expression recognition method, which is based on modified sparse representation recognition (MSRR) method. On the first stage, we use Haar-like+LPP to extract feature and reduce dimension. On the second stage, we adopt LC-K-SVD (Label Consistent K-SVD) method to train the dictionary, instead of adopting directly the dictionary from samples, and add block dictionary training into the training process. On the third stage, stOMP (stagewise orthogonal matching pursuit) method is used to speed up the convergence of OMP (orthogonal matching pursuit). Besides, a dynamic regularization factor is added to iteration process to suppress noises and enhance accuracy. We verify the proposed method from the aspect of training samples, dimension, feature extraction and dimension reduction methods and noises in self-built database and Japan's JAFFE and CMU's CK database. Further, we compare this sparse method with classic SVM and RVM and analyze the recognition effect and time efficiency. The result of simulation experiment has shown that the coefficient of MSRR method contains classifying information, which is capable of improving the computing speed and achieving a satisfying recognition result. PMID:26880878

Uptake and subcellular distribution of [3H]arachidonic acid in murine fibrosarcoma cells measured by electron microscope autoradiography

PubMed Central

1985-01-01

We have used quantitative electron microscope autoradiography to study uptake and distribution of arachidonate in HSDM1C1 murine fibrosarcoma cells and in EPU-1B, a mutant HSDM1C1 line defective in high affinity arachidonate uptake. Cells were labeled with [3H]arachidonate for 15 min, 40 min, 2 h, or 24 h. Label was found almost exclusively in cellular phospholipids; 92-96% of incorporated radioactivity was retained in cells during fixation and tissue processing. All incorporated radioactivity was found to be associated with cellular membranes. Endoplasmic reticulum (ER) contained the bulk of [3H]arachidonate at all time points in both cell types, while mitochondria, which contain a large portion of cellular membrane, were labeled slowly and to substantially lower specific activity. Plasma membrane (PM) also labeled slowly, achieving a specific activity only one-sixth that of ER at 15 min in HSDM1C1 cells (6% of total label) and one-third of ER in EPU-1B (10% of total label). Nuclear membrane (NM) exhibited the highest specific activity of labeling at 15 min in HSDM1C1 cells (twice that of ER) but was not preferentially labeled in the mutant. Over 24 h, PM label intensity increased to that of ER in both cell lines. However, NM activity diminished in HSDM1C1 cells by 24 h to a small fraction of that in ER. In response to agonists, HSDM1C1 cells release labeled arachidonate for eicosanoid synthesis most readily when they have been labeled for short times. Our results therefore suggest that NM and ER, sites of cyclooxygenase in murine fibroblasts, are probably sources for release of [3H]arachidonate, whereas PM and mitochondria are unlikely to be major sources of eicosanoid precursors. PMID:3926781

Interactive fluorophore and quencher pairs for labeling fluorescent nucleic acid hybridization probes.

PubMed

Marras, Salvatore A E

2008-03-01

The use of fluorescent nucleic acid hybridization probes that generate a fluorescence signal only when they bind to their target enables real-time monitoring of nucleic acid amplification assays. Real-time nucleic acid amplification assays markedly improves the ability to obtain qualitative and quantitative results. Furthermore, these assays can be carried out in sealed tubes, eliminating carryover contamination. Fluorescent nucleic acid hybridization probes are available in a wide range of different fluorophore and quencher pairs. Multiple hybridization probes, each designed for the detection of a different nucleic acid sequence and each labeled with a differently colored fluorophore, can be added to the same nucleic acid amplification reaction, enabling the development of high-throughput multiplex assays. In order to develop robust, highly sensitive and specific real-time nucleic acid amplification assays it is important to carefully select the fluorophore and quencher labels of hybridization probes. Selection criteria are based on the type of hybridization probe used in the assay, the number of targets to be detected, and the type of apparatus available to perform the assay. This article provides an overview of different aspects of choosing appropriate labels for the different types of fluorescent hybridization probes used with different types of spectrofluorometric thermal cyclers currently available.

Distinct populations of endoderm cells converge to generate the embryonic liver bud and ventral foregut tissues.

PubMed

Tremblay, Kimberly D; Zaret, Kenneth S

2005-04-01

The location and movement of mammalian gut tissue progenitors, prior to the expression of tissue-specific genes, has been unknown, but this knowledge is essential to identify transitions that lead to cell type specification. To address this, we used vital dyes to label exposed anterior endoderm cells of early somite stage mouse embryos, cultured the embryos into the tissue bud phase of development, and determined the tissue fate of the dye labeled cells. This approach was performed at three embryonic stages that are prior to, or coincident with, foregut tissue patterning (1-3 somites, 4-6 somites, and 7-10 somites). Short-term labeling experiments tracked the movement of tissue progenitor cells during foregut closure. Surprisingly, we found that two distinct types of endoderm-progenitor cells, lateral and medial, arising from three spatially separated embryonic domains, converge to generate the epithelial cells of the liver bud. Whereas the lateral endoderm-progenitors give rise to descendants that are constrained in tissue fate and position along the anterior-posterior axis of the gut, the medial gut endoderm-progenitors give rise to descendants that stream along the anterior-posterior axis at the ventral midline and contribute to multiple gut tissues. The fate map reveals extensive morphogenetic movement of progenitors prior to tissue specification, it permits a detailed analysis of endoderm tissue patterning, and it illustrates that diverse progenitor domains can give rise to individual tissue cell types.

SU-E-J-212: Identifying Bones From MRI: A Dictionary Learnign and Sparse Regression Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruan, D; Yang, Y; Cao, M

2014-06-01

Purpose: To develop an efficient and robust scheme to identify bony anatomy based on MRI-only simulation images. Methods: MRI offers important soft tissue contrast and functional information, yet its lack of correlation to electron-density has placed it as an auxiliary modality to CT in radiotherapy simulation and adaptation. An effective scheme to identify bony anatomy is an important first step towards MR-only simulation/treatment paradigm and would satisfy most practical purposes. We utilize a UTE acquisition sequence to achieve visibility of the bone. By contrast to manual + bulk or registration-to identify bones, we propose a novel learning-based approach for improvedmore » robustness to MR artefacts and environmental changes. Specifically, local information is encoded with MR image patch, and the corresponding label is extracted (during training) from simulation CT aligned to the UTE. Within each class (bone vs. nonbone), an overcomplete dictionary is learned so that typical patches within the proper class can be represented as a sparse combination of the dictionary entries. For testing, an acquired UTE-MRI is divided to patches using a sliding scheme, where each patch is sparsely regressed against both bone and nonbone dictionaries, and subsequently claimed to be associated with the class with the smaller residual. Results: The proposed method has been applied to the pilot site of brain imaging and it has showed general good performance, with dice similarity coefficient of greater than 0.9 in a crossvalidation study using 4 datasets. Importantly, it is robust towards consistent foreign objects (e.g., headset) and the artefacts relates to Gibbs and field heterogeneity. Conclusion: A learning perspective has been developed for inferring bone structures based on UTE MRI. The imaging setting is subject to minimal motion effects and the post-processing is efficient. The improved efficiency and robustness enables a first translation to MR-only routine. The scheme generalizes to multiple tissue classes.« less

Efficient transformation of an auditory population code in a small sensory system.

PubMed

Clemens, Jan; Kutzki, Olaf; Ronacher, Bernhard; Schreiber, Susanne; Wohlgemuth, Sandra

2011-08-16

Optimal coding principles are implemented in many large sensory systems. They include the systematic transformation of external stimuli into a sparse and decorrelated neuronal representation, enabling a flexible readout of stimulus properties. Are these principles also applicable to size-constrained systems, which have to rely on a limited number of neurons and may only have to fulfill specific and restricted tasks? We studied this question in an insect system--the early auditory pathway of grasshoppers. Grasshoppers use genetically fixed songs to recognize mates. The first steps of neural processing of songs take place in a small three-layer feed-forward network comprising only a few dozen neurons. We analyzed the transformation of the neural code within this network. Indeed, grasshoppers create a decorrelated and sparse representation, in accordance with optimal coding theory. Whereas the neuronal input layer is best read out as a summed population, a labeled-line population code for temporal features of the song is established after only two processing steps. At this stage, information about song identity is maximal for a population decoder that preserves neuronal identity. We conclude that optimal coding principles do apply to the early auditory system of the grasshopper, despite its size constraints. The inputs, however, are not encoded in a systematic, map-like fashion as in many larger sensory systems. Already at its periphery, part of the grasshopper auditory system seems to focus on behaviorally relevant features, and is in this property more reminiscent of higher sensory areas in vertebrates.

Network dynamics underlying the formation of sparse, informative representations in the hippocampus.

PubMed

Karlsson, Mattias P; Frank, Loren M

2008-12-24

During development, activity-dependent processes increase the specificity of neural responses to stimuli, but the role that this type of process plays in adult plasticity is unclear. We examined the dynamics of hippocampal activity as animals learned about new environments to understand how neural selectivity changes with experience. Hippocampal principal neurons fire when the animal is located in a particular subregion of its environment, and in any given environment the hippocampal representation is sparse: less than half of the neurons in areas CA1 and CA3 are active whereas the rest are essentially silent. Here we show that different dynamics govern the evolution of this sparsity in CA1 and upstream area CA3. CA1, but not CA3, produces twice as many spikes in novel compared with familiar environments. This high rate firing continues during sharp wave ripple events in a subsequent rest period. The overall CA1 population rate declines and the number of active cells decreases as the environment becomes familiar and task performance improves, but the decline in rate is not uniform across neurons. Instead, the activity of cells with initial peak spatial rates above approximately 12 Hz is enhanced, whereas the activity of cells with lower initial peak rates is suppressed. The result of these changes is that the active CA1 population comes to consist of a relatively small group of cells with strong spatial tuning. This process is not evident in CA3, indicating that a region-specific and long timescale process operates in CA1 to create a sparse, spatially informative population of neurons.

Liver segmentation from CT images using a sparse priori statistical shape model (SP-SSM).

PubMed

Wang, Xuehu; Zheng, Yongchang; Gan, Lan; Wang, Xuan; Sang, Xinting; Kong, Xiangfeng; Zhao, Jie

2017-01-01

This study proposes a new liver segmentation method based on a sparse a priori statistical shape model (SP-SSM). First, mark points are selected in the liver a priori model and the original image. Then, the a priori shape and its mark points are used to obtain a dictionary for the liver boundary information. Second, the sparse coefficient is calculated based on the correspondence between mark points in the original image and those in the a priori model, and then the sparse statistical model is established by combining the sparse coefficients and the dictionary. Finally, the intensity energy and boundary energy models are built based on the intensity information and the specific boundary information of the original image. Then, the sparse matching constraint model is established based on the sparse coding theory. These models jointly drive the iterative deformation of the sparse statistical model to approximate and accurately extract the liver boundaries. This method can solve the problems of deformation model initialization and a priori method accuracy using the sparse dictionary. The SP-SSM can achieve a mean overlap error of 4.8% and a mean volume difference of 1.8%, whereas the average symmetric surface distance and the root mean square symmetric surface distance can reach 0.8 mm and 1.4 mm, respectively.

Regional differences in lectin binding patterns of vestibular hair cells

NASA Technical Reports Server (NTRS)

Baird, Richard A.; Schuff, N. R.; Bancroft, J.

1994-01-01

Surface glycoconjugates of hair cells and supporting cells in the vestibular endorgans of the bullfrog were identified using biotinylated lectins with different carbohydrate specificities. Lectin binding in hair cells was consistent with the presence of glucose and mannose (CON A), galactose (RCA-I), N-acetylgalactosamine (VVA), but not fucose (UEA-I) residues. Hair cells in the bullfrog sacculus, unlike those in the utriculus and semicircular canals, did not stain for N-acetylglucosamine (WGA) or N-acetylgalactosamine (VVA). By contrast, WGA and, to a lesser extent, VVA, differentially stained utricular and semicircular canal hair cells, labeling hair cells located in peripheral, but not central, regions. In mammals, WGA uniformly labeled Type 1 hair cells while labeling, as in the bullfrog, Type 2 hair cells only in peripheral regions. These regional variations were retained after enzymatic digestion. We conclude that vestibular hair cells differ in their surface glycoconjugates and that differences in lectin binding patterns can be used to identify hair cell types and to infer the epithelial origin of isolated vestibular hair cells.

Exploration of labeling by near infrared dyes of the polyproline linker for bivalent-type CXCR4 ligands.

PubMed

Nomura, Wataru; Aikawa, Haruo; Taketomi, Shohei; Tanabe, Miho; Mizuguchi, Takaaki; Tamamura, Hirokazu

2015-11-01

We have previously used poly-L-proline linkers for the development of bivalent-type ligands for the chemokine receptor, CXCR4. The bivalent ligands with optimum linkers showed specific binding to CXCR4, suggesting the existence of CXCR4 possibly as a dimer on the cell membrane, and enabled definition of the amount of CXCR4 expressed. This paper reports the synthesis by a copper-catalyzed azide-alkyne cycloaddition reaction as the key reaction, of bivalent CXCR4 ligands with near infrared (NIR) dyes at the terminus or the center of the poly-L-proline linker. Some of the NIR-labeled ligands, which would be valuable probes useful in studies of the behavior of cells expressing CXCR4, have been obtained. The information concerning the effects of the labeling positions of NIR dyes on their binding properties is useful for the design of modified bivalent-type CXCR4 ligands. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fusion of GFP to the M.EcoKI DNA methyltransferase produces a new probe of Type I DNA restriction and modification enzymes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Kai; Roberts, Gareth A.; Stephanou, Augoustinos S.

2010-07-23

Research highlights: {yields} Successful fusion of GFP to M.EcoKI DNA methyltransferase. {yields} GFP located at C-terminal of sequence specificity subunit does not later enzyme activity. {yields} FRET confirms structural model of M.EcoKI bound to DNA. -- Abstract: We describe the fusion of enhanced green fluorescent protein to the C-terminus of the HsdS DNA sequence-specificity subunit of the Type I DNA modification methyltransferase M.EcoKI. The fusion expresses well in vivo and assembles with the two HsdM modification subunits. The fusion protein functions as a sequence-specific DNA methyltransferase protecting DNA against digestion by the EcoKI restriction endonuclease. The purified enzyme shows Foerstermore » resonance energy transfer to fluorescently-labelled DNA duplexes containing the target sequence and to fluorescently-labelled ocr protein, a DNA mimic that binds to the M.EcoKI enzyme. Distances determined from the energy transfer experiments corroborate the structural model of M.EcoKI.« less

Mixture of Segmenters with Discriminative Spatial Regularization and Sparse Weight Selection*

PubMed Central

Chen, Ting; Rangarajan, Anand; Eisenschenk, Stephan J.

2011-01-01

This paper presents a novel segmentation algorithm which automatically learns the combination of weak segmenters and builds a strong one based on the assumption that the locally weighted combination varies w.r.t. both the weak segmenters and the training images. We learn the weighted combination during the training stage using a discriminative spatial regularization which depends on training set labels. A closed form solution to the cost function is derived for this approach. In the testing stage, a sparse regularization scheme is imposed to avoid overfitting. To the best of our knowledge, such a segmentation technique has never been reported in literature and we empirically show that it significantly improves on the performances of the weak segmenters. After showcasing the performance of the algorithm in the context of atlas-based segmentation, we present comparisons to the existing weak segmenter combination strategies on a hippocampal data set. PMID:22003748

Preparation of near-infrared-labeled targeted contrast agents for clinical translation

NASA Astrophysics Data System (ADS)

Olive, D. Michael

2011-03-01

Targeted fluorophore-labeled contrast agents are moving toward translation to human surgical use. To prepare for future clinical use, we examined the performance of potential ligands targeting the epidermal growth factor receptor, α5β3 integrins, and GLUT transporters for their suitability as directed contrast agents. Each agent was labeled with IRDye 800CW, and near-infrared dye with excitation/emission wavelengths of 789/805 nm, which we determined had favorable toxicity characteristics. The probe molecules examined consisted of Affibodies, nanobodies, peptides, and the sugar 2-deoxy-D-glucose. Each probe was tested for specific and non-specific binding in cell based assays. All probe types showed good performance in mouse models for detecting either spontaneous tumors or tumor xenografts in vivo. Each of the probes tested show promise for future human clinical studies.

Biclustering sparse binary genomic data.

PubMed

van Uitert, Miranda; Meuleman, Wouter; Wessels, Lodewyk

2008-12-01

Genomic datasets often consist of large, binary, sparse data matrices. In such a dataset, one is often interested in finding contiguous blocks that (mostly) contain ones. This is a biclustering problem, and while many algorithms have been proposed to deal with gene expression data, only two algorithms have been proposed that specifically deal with binary matrices. None of the gene expression biclustering algorithms can handle the large number of zeros in sparse binary matrices. The two proposed binary algorithms failed to produce meaningful results. In this article, we present a new algorithm that is able to extract biclusters from sparse, binary datasets. A powerful feature is that biclusters with different numbers of rows and columns can be detected, varying from many rows to few columns and few rows to many columns. It allows the user to guide the search towards biclusters of specific dimensions. When applying our algorithm to an input matrix derived from TRANSFAC, we find transcription factors with distinctly dissimilar binding motifs, but a clear set of common targets that are significantly enriched for GO categories.

Crooked fingers and sparse hair: an interesting case of trichorhinophalangeal syndrome type 1.

PubMed

Narayanan, Ramakrishna; Chennareddy, Srinivasa

2015-01-27

Trichorhinophalangeal syndrome type 1 is a rare skeletal dysplasia of autosomal-dominant inheritance due to defects in the TRPS-1 gene. The syndrome is characterised by sparse slow-growing hair, a bulbous pear-shaped nose, cone-shaped epiphyses and deformities of the interphalangeal joints resembling those in rheumatoid arthritis. We present a case of trichorhinophalangeal syndrome in a 23-year-old man who presented with symmetrical painless progressive deformity of the fingers in both hands. 2015 BMJ Publishing Group Ltd.

In vitro evaluation of the monoclonal antibody 64Cu-IgG M75 against human carbonic anhydrase IX and its in vivo imaging.

PubMed

Čepa, Adam; Ráliš, Jan; Král, Vlastimil; Paurová, Monika; Kučka, Jan; Humajová, Jana; Lázníček, Milan; Lebeda, Ondřej

2018-03-01

Specific oncology diagnostics requires new types of the selective radiopharmaceuticals, particularly those suitable for the molecular PET imaging. The aim of this work is to present a new, specific PET-immunodiagnostic radiopharmaceutical based on the monoclonal antibody IgG M75 targeting human carbonic anhydrase IX labelled with 64 Cu (T ½ = 12.70h) and its in vitro and in vivo evaluation. The antibody IgG M75 was conjugated with a non-commercial copper-specific chelator "phosphinate" and then labelled with the positron emitter 64 Cu. Stability of the labelled conjugated was tested in human serum. The immunoreactivity of the labelled conjugate was evaluated in vitro on a suitable cell cultures of the colorectal carcinoma (HT-29) and its imaging properties were estimated in vivo on a mouse model with inoculated colorectal carcinoma HT-29 imaged on a µPET/CT. The tested radioimmunoconjugate was obtained in a specific activity of 0.25-0.5 MBq/µg. In vitro uptake experiments revealed specific binding to the HT-29 cells (45 ± 2.8% of the total added activity) and the measured K D value was found to be 9.2nM. Imaging clearly demonstrated significant uptake of the labelled monoclonal antibody in the tumour at 18h post administration. The radioimmunoconjugate 64 Cu-PS-IgG M75 seems to be a suitable candidate for PET diagnostics of hypoxic tumours expressing human carbonic anhydrase IX. Copyright © 2017 Elsevier Ltd. All rights reserved.

FDA drug labeling: rich resources to facilitate precision medicine, drug safety, and regulatory science.

PubMed

Fang, Hong; Harris, Stephen C; Liu, Zhichao; Zhou, Guangxu; Zhang, Guoping; Xu, Joshua; Rosario, Lilliam; Howard, Paul C; Tong, Weida

2016-10-01

Here, we provide a concise overview of US Food and Drug Administration (FDA) drug labeling, which details drug products, drug-drug interactions, adverse drug reactions (ADRs), and more. Labeling data have been collected over several decades by the FDA and are an important resource for regulatory research and decision making. However, navigating through this data is challenging. To aid such navigation, the FDALabel database was developed, which contains a set of approximately 80000 labeling data. The full-text searching capability of FDALabel and querying based on any combination of specific sections, document types, market categories, market date, and other labeling information makes it a powerful and attractive tool for a variety of applications. Here, we illustrate the utility of FDALabel using case scenarios in pharmacogenomics biomarkers and ADR studies. Published by Elsevier Ltd.

Tuning a Protein-Labeling Reaction to Achieve Highly Site Selective Lysine Conjugation.

PubMed

Pham, Grace H; Ou, Weijia; Bursulaya, Badry; DiDonato, Michael; Herath, Ananda; Jin, Yunho; Hao, Xueshi; Loren, Jon; Spraggon, Glen; Brock, Ansgar; Uno, Tetsuo; Geierstanger, Bernhard H; Cellitti, Susan E

2018-04-16

Activated esters are widely used to label proteins at lysine side chains and N termini. These reagents are useful for labeling virtually any protein, but robust reactivity toward primary amines generally precludes site-selective modification. In a unique case, fluorophenyl esters are shown to preferentially label human kappa antibodies at a single lysine (Lys188) within the light-chain constant domain. Neighboring residues His189 and Asp151 contribute to the accelerated rate of labeling at Lys188 relative to the ≈40 other lysine sites. Enriched Lys188 labeling can be enhanced from 50-70 % to >95 % by any of these approaches: lowering reaction temperature, applying flow chemistry, or mutagenesis of specific residues in the surrounding protein environment. Our results demonstrated that activated esters with fluoro-substituted aromatic leaving groups, including a fluoronaphthyl ester, can be generally useful reagents for site-selective lysine labeling of antibodies and other immunoglobulin-type proteins. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Segmentation of MR images via discriminative dictionary learning and sparse coding: application to hippocampus labeling.

PubMed

Tong, Tong; Wolz, Robin; Coupé, Pierrick; Hajnal, Joseph V; Rueckert, Daniel

2013-08-01

We propose a novel method for the automatic segmentation of brain MRI images by using discriminative dictionary learning and sparse coding techniques. In the proposed method, dictionaries and classifiers are learned simultaneously from a set of brain atlases, which can then be used for the reconstruction and segmentation of an unseen target image. The proposed segmentation strategy is based on image reconstruction, which is in contrast to most existing atlas-based labeling approaches that rely on comparing image similarities between atlases and target images. In addition, we propose a Fixed Discriminative Dictionary Learning for Segmentation (F-DDLS) strategy, which can learn dictionaries offline and perform segmentations online, enabling a significant speed-up in the segmentation stage. The proposed method has been evaluated for the hippocampus segmentation of 80 healthy ICBM subjects and 202 ADNI images. The robustness of the proposed method, especially of our F-DDLS strategy, was validated by training and testing on different subject groups in the ADNI database. The influence of different parameters was studied and the performance of the proposed method was also compared with that of the nonlocal patch-based approach. The proposed method achieved a median Dice coefficient of 0.879 on 202 ADNI images and 0.890 on 80 ICBM subjects, which is competitive compared with state-of-the-art methods. Copyright © 2013 Elsevier Inc. All rights reserved.

Comparison of Test Procedures and Energy Efficiency Criteria in Selected International Standards and Labeling Programs for Clothes Washers, Water Dispensers, Vending Machines and CFLs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fridley, David; Zheng, Nina; Zhou, Nan

Since the late 1970s, energy labeling programs and mandatory energy performance standards have been used in many different countries to improve the efficiency levels of major residential and commercial equipment. As more countries and regions launch programs covering a greater range of products that are traded worldwide, greater attention has been given to harmonizing the specific efficiency criteria in these programs and the test methods for measurements. For example, an international compact fluorescent light (CFL) harmonization initiative was launched in 2006 to focus on collaboration between Australia, China, Europe and North America. Given the long history of standards and labelingmore » programs, most major energy-consuming residential appliances and commercial equipment are already covered under minimum energy performance standards (MEPS) and/or energy labels. For these products, such as clothes washers and CFLs, harmonization may still be possible when national MEPS or labeling thresholds are revised. Greater opportunity for harmonization exists in newer energy-consuming products that are not commonly regulated but are under consideration for new standards and labeling programs. This may include commercial products such as water dispensers and vending machines, which are only covered by MEPS or energy labels in a few countries or regions. As China continues to expand its appliance standards and labeling programs and revise existing standards and labels, it is important to learn from recent international experiences with efficiency criteria and test procedures for the same products. Specifically, various types of standards and labeling programs already exist in North America, Europe and throughout Asia for products in China's 2010 standards and labeling programs, namely clothes washers, water dispensers, vending machines and CFLs. This report thus examines similarities and critical differences in energy efficiency values, test procedure specifications and other technical performance requirements in existing international programs in order to shed light on where Chinese programs currently stands and considerations for their 2010 programs.« less

Spondylo-meta-epiphyseal dysplasia (SMED), short limb-hand type: a congenital familial skeletal dysplasia with distinctive features and histopathology.

PubMed

Borochowitz, Z; Langer, L O; Gruber, H E; Lachman, R; Katznelson, M B; Rimoin, D L

1993-02-01

We report on a "new" severe short-limb bone dysplasia which can be labeled descriptively a spondylo-meta-epiphyseal dysplasia. The 3 patients were born to 2 unrelated Sepharadic Jewish families and a Puerto Rican family. Clinical abnormalities include small stature with short limbs including short hands, a short nose with wide nasal bridge and wide nostrils, a long philtrum, ocular hypertelorism, retro/micrognathia, and a narrow chest. Radiological abnormalities include platyspondyly, short tubular bones with very abnormal metaphyses and epiphyses beyond early infancy, short ribs, and a typical evolution of bony changes over time. Chondroosseous morphology and ultrastructure document sparse matrix and degenerating chondrocytes surrounded by dense amorphous material in the 1 patient studied. Consanguinity is present in 1 family. In addition to the described patient, 2 other short-limb sibs, who did not survive infancy, were born into this family. Even in the absence of any photographic or radiologic documentation of these other 2 infants, autosomal recessive mode of inheritance seems probable.

Single molecule optical measurements of orientation and rotations of biological macromolecules.

PubMed

Shroder, Deborah Y; Lippert, Lisa G; Goldman, Yale E

2016-11-22

Subdomains of macromolecules often undergo large orientation changes during their catalytic cycles that are essential for their activity. Tracking these rearrangements in real time opens a powerful window into the link between protein structure and functional output. Site-specific labeling of individual molecules with polarized optical probes and measurement of their spatial orientation can give insight into the crucial conformational changes, dynamics, and fluctuations of macromolecules. Here we describe the range of single molecule optical technologies that can extract orientation information from these probes, review the relevant types of probes and labeling techniques, and highlight the advantages and disadvantages of these technologies for addressing specific inquiries.

Multi-threaded Sparse Matrix Sparse Matrix Multiplication for Many-Core and GPU Architectures.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deveci, Mehmet; Trott, Christian Robert; Rajamanickam, Sivasankaran

Sparse Matrix-Matrix multiplication is a key kernel that has applications in several domains such as scientific computing and graph analysis. Several algorithms have been studied in the past for this foundational kernel. In this paper, we develop parallel algorithms for sparse matrix- matrix multiplication with a focus on performance portability across different high performance computing architectures. The performance of these algorithms depend on the data structures used in them. We compare different types of accumulators in these algorithms and demonstrate the performance difference between these data structures. Furthermore, we develop a meta-algorithm, kkSpGEMM, to choose the right algorithm and datamore » structure based on the characteristics of the problem. We show performance comparisons on three architectures and demonstrate the need for the community to develop two phase sparse matrix-matrix multiplication implementations for efficient reuse of the data structures involved.« less

The effect of magnetic nanoparticles on neuronal differentiation of induced pluripotent stem cell-derived neural precursors

PubMed Central

Jiráková, Klára; Šeneklová, Monika; Jirák, Daniel; Turnovcová, Karolína; Vosmanská, Magda; Babič, Michal; Horák, Daniel; Veverka, Pavel; Jendelová, Pavla

2016-01-01

Introduction Magnetic resonance (MR) imaging is suitable for noninvasive long-term tracking. We labeled human induced pluripotent stem cell-derived neural precursors (iPSC-NPs) with two types of iron-based nanoparticles, silica-coated cobalt zinc ferrite nanoparticles (CZF) and poly-l-lysine-coated iron oxide superparamagnetic nanoparticles (PLL-coated γ-Fe2O3) and studied their effect on proliferation and neuronal differentiation. Materials and methods We investigated the effect of these two contrast agents on neural precursor cell proliferation and differentiation capability. We further defined the intracellular localization and labeling efficiency and analyzed labeled cells by MR. Results Cell proliferation was not affected by PLL-coated γ-Fe2O3 but was slowed down in cells labeled with CZF. Labeling efficiency, iron content and relaxation rates measured by MR were lower in cells labeled with CZF when compared to PLL-coated γ-Fe2O3. Cytoplasmic localization of both types of nanoparticles was confirmed by transmission electron microscopy. Flow cytometry and immunocytochemical analysis of specific markers expressed during neuronal differentiation did not show any significant differences between unlabeled cells or cells labeled with both magnetic nanoparticles. Conclusion Our results show that cells labeled with PLL-coated γ-Fe2O3 are suitable for MR detection, did not affect the differentiation potential of iPSC-NPs and are suitable for in vivo cell therapies in experimental models of central nervous system disorders. PMID:27920532

Binding of the host-specific toxins from Helminthosporium maydis race T and Phyllosticta maydis to mitochondria isolated from Zea mays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Frantzen, K.A.

1985-01-01

Helminthosphorium maydis race I and Phyllosticta maydis, the causal agents of southern and yellow corn leaf blights, respectively, produce host-specific toxins. The toxic specificity of these natural products is identical to the host-specificity of the pathogens for certain varieties of corn. Susceptible genotypes carry the Texas type of cytoplasmic male sterility. Isolated mitochondria from susceptible plant species are highly sensitive to these toxins, whereas other plant species, including resistant corn varieties, and their mitochondria are not. The mitochondrion may be the primary cellular site of action for these toxins. The toxins from H. maydis and P. maydis were tritiated bymore » reduction with borotritide salts. The labeled products had a high specific activity (3.8 to 8 Ci/mmole), high biological activity, and specificity identical to that of the native toxins. A filtration binding assay was developed to investigate the binding characteristics of these labeled toxins to isolated mitochondria. Mitochondria isolated from both cytoplasmic male sterile (Texas) and normal corn demonstrated similar binding characteristics including ligand displaceable binding with both labeled toxins. Ligand displaceable binding was also detectable in mitochondria from soybeans, a nonhost plant for these fungi. The ability to displace the bound labeled toxins was generally correlated with the biological activity of the competing toxin. The results of this study suggest that a receptor site hypothesis for the mode of action of these toxins may not be valid.« less

Label-free haemogram using wavelength modulated Raman spectroscopy for identifying immune-cell subset

NASA Astrophysics Data System (ADS)

Ashok, Praveen C.; Praveen, Bavishna B.; Campbell, Elaine C.; Dholakia, Kishan; Powis, Simon J.

2014-03-01

Leucocytes in the blood of mammals form a powerful protective system against a wide range of dangerous pathogens. There are several types of immune cells that has specific role in the whole immune system. The number and type of immune cells alter in the disease state and identifying the type of immune cell provides information about a person's state of health. There are several immune cell subsets that are essentially morphologically identical and require external labeling to enable discrimination. Here we demonstrate the feasibility of using Wavelength Modulated Raman Spectroscopy (WMRS) with suitable machine learning algorithms as a label-free method to distinguish between different closely lying immune cell subset. Principal Component Analysis (PCA) was performed on WMRS data from single cells, obtained using confocal Raman microscopy for feature reduction, followed by Support Vector Machine (SVM) for binary discrimination of various cell subset, which yielded an accuracy >85%. The method was successful in discriminating between untouched and unfixed purified populations of CD4+CD3+ and CD8+CD3+ T lymphocyte subsets, and CD56+CD3- natural killer cells with a high degree of specificity. It was also proved sensitive enough to identify unique Raman signatures that allow clear discrimination between dendritic cell subsets, comprising CD303+CD45+ plasmacytoid and CD1c+CD141+ myeloid dendritic cells. The results of this study clearly show that WMRS is highly sensitive and can distinguish between cell types that are morphologically identical.

Isolation of mouse pancreatic alpha, beta, duct and acinar populations with cell surface markers.

PubMed

Dorrell, Craig; Grompe, Maria T; Pan, Fong Cheng; Zhong, Yongping; Canaday, Pamela S; Shultz, Leonard D; Greiner, Dale L; Wright, Chris V; Streeter, Philip R; Grompe, Markus

2011-06-06

Tools permitting the isolation of live pancreatic cell subsets for culture and/or molecular analysis are limited. To address this, we developed a collection of monoclonal antibodies with selective surface labeling of endocrine and exocrine pancreatic cell types. Cell type labeling specificity and cell surface reactivity were validated on mouse pancreatic sections and by gene expression analysis of cells isolated using FACS. Five antibodies which marked populations of particular interest were used to isolate and study viable populations of purified pancreatic ducts, acinar cells, and subsets of acinar cells from whole pancreatic tissue or of alpha or beta cells from isolated mouse islets. Gene expression analysis showed the presence of known endocrine markers in alpha and beta cell populations and revealed that TTR and DPPIV are primarily expressed in alpha cells whereas DGKB and GPM6A have a beta cell specific expression profile. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Small-molecule-based protein-labeling technology in live cell studies: probe-design concepts and applications.

PubMed

Mizukami, Shin; Hori, Yuichiro; Kikuchi, Kazuya

2014-01-21

The use of genetic engineering techniques allows researchers to combine functional proteins with fluorescent proteins (FPs) to produce fusion proteins that can be visualized in living cells, tissues, and animals. However, several limitations of FPs, such as slow maturation kinetics or issues with photostability under laser illumination, have led researchers to examine new technologies beyond FP-based imaging. Recently, new protein-labeling technologies using protein/peptide tags and tag-specific probes have attracted increasing attention. Although several protein-labeling systems are com mercially available, researchers continue to work on addressing some of the limitations of this technology. To reduce the level of background fluorescence from unlabeled probes, researchers have pursued fluorogenic labeling, in which the labeling probes do not fluoresce until the target proteins are labeled. In this Account, we review two different fluorogenic protein-labeling systems that we have recently developed. First we give a brief history of protein labeling technologies and describe the challenges involved in protein labeling. In the second section, we discuss a fluorogenic labeling system based on a noncatalytic mutant of β-lactamase, which forms specific covalent bonds with β-lactam antibiotics such as ampicillin or cephalosporin. Based on fluorescence (or Förster) resonance energy transfer and other physicochemical principles, we have developed several types of fluorogenic labeling probes. To extend the utility of this labeling system, we took advantage of a hydrophobic β-lactam prodrug structure to achieve intracellular protein labeling. We also describe a small protein tag, photoactive yellow protein (PYP)-tag, and its probes. By utilizing a quenching mechanism based on close intramolecular contact, we incorporated a turn-on switch into the probes for fluorogenic protein labeling. One of these probes allowed us to rapidly image a protein while avoiding washout. In the future, we expect that protein-labeling systems with finely designed probes will lead to novel methodologies that allow researchers to image biomolecules and to perturb protein functions.

Label-free NIR reflectance imaging as a complimentary tool for two-photon fluorescence microscopy: multimodal investigation of stroke (Conference Presentation)

NASA Astrophysics Data System (ADS)

Allegra Mascaro, Anna Letizia; Costantini, Irene; Margoni, Emilia; Iannello, Giulio; Bria, Alessandro; Sacconi, Leonardo; Pavone, Francesco S.

2016-03-01

Two-photon imaging combined with targeted fluorescent indicators is extensively used for visualizing critical features of brain functionality and structural plasticity. Back-scattered photons from the NIR laser provide complimentary information without introducing any exogenous labelling. Here, we describe a versatile approach that, by collecting the reflected NIR light, provides structural details on the myelinated axons and blood vessels in the brain, both in fixed samples and in live animals. Indeed, by combining NIR reflectance and two-photon imaging of a slice of hippocampus from Thy1-GFPm mice, we show the presence of randomly oriented axons intermingled with sparsely fluorescent neuronal processes. The back-scattered photons guide the contextualization of the fluorescence structure within brain atlas thanks to the recognition of characteristic hippocampal structures. Label-free detection of axonal elongations over the layer 2/3 of mouse cortex under a cranial window was also possible in live brain. Finally, blood flow could be measured in vivo, thus validating label free NIR reflectance as a tool for monitoring hemodynamic fluctuations. The prospective versatility of this label-free technique complimentary to two-photon fluorescence microscopy is demonstrated in a mouse model of photothrombotic stroke in which the axonal degeneration and blood flow remodeling can be investigated simultaneously.

Detection of human papillomavirus (HPV) DNA in human prostatic tissues by polymerase chain reaction (PCR).

PubMed

Sarkar, F H; Sakr, W A; Li, Y W; Sreepathi, P; Crissman, J D

1993-01-01

Human papillomavirus (HPV) infections are strongly linked to the pathogenesis of uterine cervical neoplasms, and have been implicated in other cancers of the female genital tract. In contrast, the association of HPV with the cancers of the male urogenital tract is less evident, except in anal and penile cancers. However, recent studies reporting the prevalence of HPV infections in human prostate cancers (60-100% HPV 16 positive vs. no infection of HPV) have raised controversies regarding the prevalence of HPV in benign and neoplastic human prostate. We investigated the prevalence of HPV infections in prostatic intraepithelial neoplasia (PIN) and prostatic adenocarcinomas in 23 surgically resected prostates. Polymerase chain reaction (PCR) was used to amplify HPV 6b/11, 16, and 18 specific DNA sequences, using type specific HPV primers selected from the transforming gene E6-E7. The areas of PIN and cancer in 6 microns H&E stained tissue sections were identified, and respective areas of PIN and cancer were isolated from the adjacent serial sections and used for DNA amplification and HPV detection (Fig. 1). Our results demonstrated the presence of HPV 16 in three carcinomas (13%), using type specific primers in PCR amplified samples. We were not able to demonstrate the presence of other HPV types (HPV 6b/11 or HPV 18) in any of the samples using specific primers. Two of these prostates showed relatively strong positive signals by dot blot analysis, when hybridized with a 32P-labeled HPV 16 type specific oligonucleotide probe. One more sample showed weak positivity, when hybridized with a 32P-labeled HPV 16 type specific oligonucleotide probe. Subsequently, we have confirmed these results by Southern hybridization of the samples transferred to nylon membrane after agarose gel electrophoresis and detected by HPV 16 type specific oligonucleotide probe, using chemiluminescent assay. We, therefore, conclude that HPV infections of the prostate in general are not as common as has been previously claimed by other investigators.

Fundamentals of Clinical Pharmacology With Application for Pregnant Women.

PubMed

Patil, Avinash S; Sheng, Jessica; Dotters-Katz, Sarah K; Schmoll, Maria S; Onslow, Mitchell; Pierson, Rebecca C

2017-05-01

Medication use is common in pregnancy, yet for most medications the optimal formulation and dosage have not been described specifically for pregnant women. Often, adverse effects are only discovered anecdotally or after extensive off-label use occurs. Since pharmacologic research that includes pregnant women is sparse and animal studies are often not applicable to the human fetus, providers must use knowledge of drug behavior and normal physiologic changes of pregnancy to personalize treatment for pregnant women. In this review, we present an overview of the basic concepts of clinical pharmacology: pharmacokinetics, pharmacodynamics, and pharmacogenomics. The normal physiologic changes of pregnancy are presented as a framework to understand alterations in drug behavior. A clinical vignette that addresses 4 pregnancy scenarios involving medications-preterm birth, vaccination, herpes simplex virus infection, and codeine toxicity-is provided to illustrate application of core clinical pharmacologic concepts. Discussion of relevant literature illustrates the challenges of offering individualized pharmacologic therapy in pregnancy. © 2017 by the American College of Nurse-Midwives.

New Method for Producing Significant Amounts of RNA Labeled at Specific Sites | Center for Cancer Research

Cancer.gov

Among biomacromolecules, RNA is the most versatile, and it plays indispensable roles in almost all aspects of biology. For example, in addition to serving as mRNAs coding for proteins, RNAs regulate gene expression, such as controlling where, when, and how efficiently a gene gets expressed, participate in RNA processing, encode the genetic information of some viruses, serve as scaffolds, and even possess enzymatic activity. To study these RNAs and their biological functions and to make use of those RNA activities for biomedical applications, researchers first need to make various types of RNA. For structural biologists incorporating modified or labeled nucleotides at specific sites in RNA molecules of interest is critical to gain structural insight into RNA functions. However, placing labeled or modified residue(s) in desired positions in a large RNA has not been possible until now.

Amesos2 and Belos: Direct and Iterative Solvers for Large Sparse Linear Systems

DOE PAGES

Bavier, Eric; Hoemmen, Mark; Rajamanickam, Sivasankaran; ...

2012-01-01

Solvers for large sparse linear systems come in two categories: direct and iterative. Amesos2, a package in the Trilinos software project, provides direct methods, and Belos, another Trilinos package, provides iterative methods. Amesos2 offers a common interface to many different sparse matrix factorization codes, and can handle any implementation of sparse matrices and vectors, via an easy-to-extend C++ traits interface. It can also factor matrices whose entries have arbitrary “Scalar” type, enabling extended-precision and mixed-precision algorithms. Belos includes many different iterative methods for solving large sparse linear systems and least-squares problems. Unlike competing iterative solver libraries, Belos completely decouples themore » algorithms from the implementations of the underlying linear algebra objects. This lets Belos exploit the latest hardware without changes to the code. Belos favors algorithms that solve higher-level problems, such as multiple simultaneous linear systems and sequences of related linear systems, faster than standard algorithms. The package also supports extended-precision and mixed-precision algorithms. Together, Amesos2 and Belos form a complete suite of sparse linear solvers.« less

An illustrated catalogue of the types of Stratiomyidae (Diptera: Brachycera) in the collection of Museu Nacional, Rio de Janeiro, Brazil.

PubMed

Fachin, Diego Aguilar; Couri, Márcia Souto; De Mello-Patiu, Cátia Antunes

2016-02-26

A catalogue of the type specimens of Stratiomyidae (Diptera: Brachycera) held in the collection of Museu Nacional, Rio de Janeiro, Brazil (MNRJ) is presented. A total number of 50 type specimens of 18 valid Neotropical species were recognized and are listed in alphabetical order of subfamily, genus and specific epithet. Photos of 12 primary types of the species and bibliographical data of the original descriptions, labels and condition of all type specimens are also provided.

Heterogeneous transgene expression in the retinas of the TH-RFP, TH-Cre, TH-BAC-Cre and DAT-Cre mouse lines

PubMed Central

Vuong, Helen E.; de Sevilla Müller, Luis Pérez; Hardi, Claudia N.; McMahon, Douglas G.; Brecha, Nicholas C.

2015-01-01

Transgenic mouse lines are essential tools for understanding the connectivity, physiology and function of neuronal circuits, including those in the retina. This report compares transgene expression in the retina of a tyrosine hydroxylase (TH)-red fluorescent protein (RFP) line with three catecholamine-related Cre recombinase lines [TH-bacterial artificial chromosome (BAC)-, TH-, and dopamine transporter (DAT)-Cre] that were crossed with a ROSA26-tdTomato reporter line. Retinas were evaluated and immunostained with commonly used antibodies including those directed to TH, GABA and glycine to characterize the RFP or tdTomato fluorescent-labeled amacrine cells, and an antibody directed to RNA-binding protein with multiple splicing to identify ganglion cells. In TH-RFP retinas, types 1 and 2 dopamine (DA) amacrine cells were identified by their characteristic cellular morphology and type 1 DA cells by their expression of TH immunoreactivity. In the TH-BAC-, TH-, and DAT-tdTomato retinas, less than 1%, ~6%, and 0%, respectively, of the fluorescent cells were the expected type 1 DA amacrine cells. Instead, in the TH-BAC-tdTomato retinas, fluorescently labeled AII amacrine cells were predominant, with some medium somal diameter ganglion cells. In TH-tdTomato retinas, fluorescence was in multiple neurochemical amacrine cell types, including four types of polyaxonal amacrine cells. In DAT-tdTomato retinas, fluorescence was in GABA immunoreactive amacrine cells, including two types of bistratified and two types of monostratified amacrine cells. Although each of the Cre lines were generated with the intent to specifically label DA cells, our findings show a cellular diversity in Cre expression in the adult retina and indicate the importance of careful characterization of transgene labeling patterns. These mouse lines with their distinctive cellular labeling patterns will be useful tools for future studies of retinal function and visual processing. PMID:26335381

Heterogeneous transgene expression in the retinas of the TH-RFP, TH-Cre, TH-BAC-Cre and DAT-Cre mouse lines.

PubMed

Vuong, H E; Pérez de Sevilla Müller, L; Hardi, C N; McMahon, D G; Brecha, N C

2015-10-29

Transgenic mouse lines are essential tools for understanding the connectivity, physiology and function of neuronal circuits, including those in the retina. This report compares transgene expression in the retina of a tyrosine hydroxylase (TH)-red fluorescent protein (RFP) mouse line with three catecholamine-related Cre recombinase mouse lines [TH-bacterial artificial chromosome (BAC)-, TH-, and dopamine transporter (DAT)-Cre] that were crossed with a ROSA26-tdTomato reporter line. Retinas were evaluated and immunostained with commonly used antibodies including those directed to TH, GABA and glycine to characterize the RFP or tdTomato fluorescent-labeled amacrine cells, and an antibody directed to RNA-binding protein with multiple splicing to identify ganglion cells. In TH-RFP retinas, types 1 and 2 dopamine (DA) amacrine cells were identified by their characteristic cellular morphology and type 1 DA cells by their expression of TH immunoreactivity. In the TH-BAC-, TH-, and DAT-tdTomato retinas, less than 1%, ∼ 6%, and 0%, respectively, of the fluorescent cells were the expected type 1 DA amacrine cells. Instead, in the TH-BAC-tdTomato retinas, fluorescently labeled AII amacrine cells were predominant, with some medium diameter ganglion cells. In TH-tdTomato retinas, fluorescence was in multiple neurochemical amacrine cell types, including four types of polyaxonal amacrine cells. In DAT-tdTomato retinas, fluorescence was in GABA immunoreactive amacrine cells, including two types of bistratified and two types of monostratified amacrine cells. Although each of the Cre lines was generated with the intent to specifically label DA cells, our findings show a cellular diversity in Cre expression in the adult retina and indicate the importance of careful characterization of transgene labeling patterns. These mouse lines with their distinctive cellular labeling patterns will be useful tools for future studies of retinal function and visual processing. Published by Elsevier Ltd.

Immunogenicity is preferentially induced in sparse dendritic cell cultures.

PubMed

Nasi, Aikaterini; Bollampalli, Vishnu Priya; Sun, Meng; Chen, Yang; Amu, Sylvie; Nylén, Susanne; Eidsmo, Liv; Rothfuchs, Antonio Gigliotti; Réthi, Bence

2017-03-09

We have previously shown that human monocyte-derived dendritic cells (DCs) acquired different characteristics in dense or sparse cell cultures. Sparsity promoted the development of IL-12 producing migratory DCs, whereas dense cultures increased IL-10 production. Here we analysed whether the density-dependent endogenous breaks could modulate DC-based vaccines. Using murine bone marrow-derived DC models we show that sparse cultures were essential to achieve several key functions required for immunogenic DC vaccines, including mobility to draining lymph nodes, recruitment and massive proliferation of antigen-specific CD4+ T cells, in addition to their TH1 polarization. Transcription analyses confirmed higher commitment in sparse cultures towards T cell activation, whereas DCs obtained from dense cultures up-regulated immunosuppressive pathway components and genes suggesting higher differentiation plasticity towards osteoclasts. Interestingly, we detected a striking up-regulation of fatty acid and cholesterol biosynthesis pathways in sparse cultures, suggesting an important link between DC immunogenicity and lipid homeostasis regulation.

A Thousand Frames in Just a Few Words: Lingual Description of Videos through Latent Topics and Sparse Object Stitching (Open Access)

DTIC Science & Technology

2013-10-03

the Stanford NLP Suite∗ to create an- notated dictionaries based on word morphologies ; the human descriptions provide the input. The predicted...keywords from the low level topic models are labeled through these dictionaries. For more than two POS for the same morphology , we prefer verbs, but other...redundancy particularly retaining subjects like “man,” “woman” etc. and verb morphologies (which otherwise stem to the same prefix) as proxies for ten

Methods of Sparse Modeling and Dimensionality Reduction to Deal with Big Data

DTIC Science & Technology

2015-04-01

supervised learning (c). Our framework consists of two separate phases: (a) first find an initial space in an unsupervised manner; then (b) utilize label...model that can learn thousands of topics from a large set of documents and infer the topic mixture of each document, 2) a supervised dimension reduction...model that can learn thousands of topics from a large set of documents and infer the topic mixture of each document, (i) a method of supervised

Visual Tracking Based on Extreme Learning Machine and Sparse Representation

PubMed Central

Wang, Baoxian; Tang, Linbo; Yang, Jinglin; Zhao, Baojun; Wang, Shuigen

2015-01-01

The existing sparse representation-based visual trackers mostly suffer from both being time consuming and having poor robustness problems. To address these issues, a novel tracking method is presented via combining sparse representation and an emerging learning technique, namely extreme learning machine (ELM). Specifically, visual tracking can be divided into two consecutive processes. Firstly, ELM is utilized to find the optimal separate hyperplane between the target observations and background ones. Thus, the trained ELM classification function is able to remove most of the candidate samples related to background contents efficiently, thereby reducing the total computational cost of the following sparse representation. Secondly, to further combine ELM and sparse representation, the resultant confidence values (i.e., probabilities to be a target) of samples on the ELM classification function are used to construct a new manifold learning constraint term of the sparse representation framework, which tends to achieve robuster results. Moreover, the accelerated proximal gradient method is used for deriving the optimal solution (in matrix form) of the constrained sparse tracking model. Additionally, the matrix form solution allows the candidate samples to be calculated in parallel, thereby leading to a higher efficiency. Experiments demonstrate the effectiveness of the proposed tracker. PMID:26506359

Incorporating biological information in sparse principal component analysis with application to genomic data.

PubMed

Li, Ziyi; Safo, Sandra E; Long, Qi

2017-07-11

Sparse principal component analysis (PCA) is a popular tool for dimensionality reduction, pattern recognition, and visualization of high dimensional data. It has been recognized that complex biological mechanisms occur through concerted relationships of multiple genes working in networks that are often represented by graphs. Recent work has shown that incorporating such biological information improves feature selection and prediction performance in regression analysis, but there has been limited work on extending this approach to PCA. In this article, we propose two new sparse PCA methods called Fused and Grouped sparse PCA that enable incorporation of prior biological information in variable selection. Our simulation studies suggest that, compared to existing sparse PCA methods, the proposed methods achieve higher sensitivity and specificity when the graph structure is correctly specified, and are fairly robust to misspecified graph structures. Application to a glioblastoma gene expression dataset identified pathways that are suggested in the literature to be related with glioblastoma. The proposed sparse PCA methods Fused and Grouped sparse PCA can effectively incorporate prior biological information in variable selection, leading to improved feature selection and more interpretable principal component loadings and potentially providing insights on molecular underpinnings of complex diseases.

Efficient methods for attaching non-radioactive labels to the 5' ends of synthetic oligodeoxyribonucleotides.

PubMed Central

Agrawal, S; Christodoulou, C; Gait, M J

1986-01-01

The syntheses are described of two types of linker molecule useful for the specific attachment of non-radioactive labels such as biotin and fluorophores to the 5' terminus of synthetic oligodeoxyribonucleotides. The linkers are designed such that they can be coupled to the oligonucleotide as a final step in solid-phase synthesis using commercial DNA synthesis machines. Increased sensitivity of biotin detection was possible using an anti-biotin hybridoma/peroxidase detection system. PMID:3748808

Reactions of Chinese adults to warning labels on cigarette packages: A survey in Jiangsu Province

PubMed Central

2011-01-01

Background To compare reactions to warning labels presented on cigarette packages with a specific focus on whether the new Chinese warning labels are better than the old labels and international labels. Methods Participants aged 18 and over were recruited in two cities of Jiangsu Province in 2008, and 876 face-to-face interviews were completed. Participants were shown six types of warning labels found on cigarette packages. They comprised one old Chinese label, one new label used within the Chinese market, and one Chinese overseas label and three foreign brand labels. Participants were asked about the impact of the warning labels on: their knowledge of harm from smoking, giving cigarettes as a gift, and quitting smoking. Results Compared with the old Chinese label, a higher proportion of participants said the new label provided clear information on harm caused by smoking (31.2% vs 18.3%). Participants were less likely to give cigarettes with the new label on the package compared with the old label (25.2% vs 20.8%). These proportions were higher when compared to the international labels. Overall, 26.8% of participants would quit smoking based on information from the old label and 31.5% from the new label. When comparing the Chinese overseas label and other foreign labels to the new Chinese label with regard to providing knowledge of harm warning, impact of quitting smoking and giving cigarettes as a gift, the overseas labels were more effective. Conclusion Both the old and the new Chinese warning label are not effective in this target population. PMID:21349205

Synthesizing spatiotemporally sparse smartphone sensor data for bridge modal identification

NASA Astrophysics Data System (ADS)

Ozer, Ekin; Feng, Maria Q.

2016-08-01

Smartphones as vibration measurement instruments form a large-scale, citizen-induced, and mobile wireless sensor network (WSN) for system identification and structural health monitoring (SHM) applications. Crowdsourcing-based SHM is possible with a decentralized system granting citizens with operational responsibility and control. Yet, citizen initiatives introduce device mobility, drastically changing SHM results due to uncertainties in the time and the space domains. This paper proposes a modal identification strategy that fuses spatiotemporally sparse SHM data collected by smartphone-based WSNs. Multichannel data sampled with the time and the space independence is used to compose the modal identification parameters such as frequencies and mode shapes. Structural response time history can be gathered by smartphone accelerometers and converted into Fourier spectra by the processor units. Timestamp, data length, energy to power conversion address temporal variation, whereas spatial uncertainties are reduced by geolocation services or determining node identity via QR code labels. Then, parameters collected from each distributed network component can be extended to global behavior to deduce modal parameters without the need of a centralized and synchronous data acquisition system. The proposed method is tested on a pedestrian bridge and compared with a conventional reference monitoring system. The results show that the spatiotemporally sparse mobile WSN data can be used to infer modal parameters despite non-overlapping sensor operation schedule.

Estimating multivariate similarity between neuroimaging datasets with sparse canonical correlation analysis: an application to perfusion imaging.

PubMed

Rosa, Maria J; Mehta, Mitul A; Pich, Emilio M; Risterucci, Celine; Zelaya, Fernando; Reinders, Antje A T S; Williams, Steve C R; Dazzan, Paola; Doyle, Orla M; Marquand, Andre F

2015-01-01

An increasing number of neuroimaging studies are based on either combining more than one data modality (inter-modal) or combining more than one measurement from the same modality (intra-modal). To date, most intra-modal studies using multivariate statistics have focused on differences between datasets, for instance relying on classifiers to differentiate between effects in the data. However, to fully characterize these effects, multivariate methods able to measure similarities between datasets are needed. One classical technique for estimating the relationship between two datasets is canonical correlation analysis (CCA). However, in the context of high-dimensional data the application of CCA is extremely challenging. A recent extension of CCA, sparse CCA (SCCA), overcomes this limitation, by regularizing the model parameters while yielding a sparse solution. In this work, we modify SCCA with the aim of facilitating its application to high-dimensional neuroimaging data and finding meaningful multivariate image-to-image correspondences in intra-modal studies. In particular, we show how the optimal subset of variables can be estimated independently and we look at the information encoded in more than one set of SCCA transformations. We illustrate our framework using Arterial Spin Labeling data to investigate multivariate similarities between the effects of two antipsychotic drugs on cerebral blood flow.

Co-Labeling for Multi-View Weakly Labeled Learning.

PubMed

Xu, Xinxing; Li, Wen; Xu, Dong; Tsang, Ivor W

2016-06-01

It is often expensive and time consuming to collect labeled training samples in many real-world applications. To reduce human effort on annotating training samples, many machine learning techniques (e.g., semi-supervised learning (SSL), multi-instance learning (MIL), etc.) have been studied to exploit weakly labeled training samples. Meanwhile, when the training data is represented with multiple types of features, many multi-view learning methods have shown that classifiers trained on different views can help each other to better utilize the unlabeled training samples for the SSL task. In this paper, we study a new learning problem called multi-view weakly labeled learning, in which we aim to develop a unified approach to learn robust classifiers by effectively utilizing different types of weakly labeled multi-view data from a broad range of tasks including SSL, MIL and relative outlier detection (ROD). We propose an effective approach called co-labeling to solve the multi-view weakly labeled learning problem. Specifically, we model the learning problem on each view as a weakly labeled learning problem, which aims to learn an optimal classifier from a set of pseudo-label vectors generated by using the classifiers trained from other views. Unlike traditional co-training approaches using a single pseudo-label vector for training each classifier, our co-labeling approach explores different strategies to utilize the predictions from different views, biases and iterations for generating the pseudo-label vectors, making our approach more robust for real-world applications. Moreover, to further improve the weakly labeled learning on each view, we also exploit the inherent group structure in the pseudo-label vectors generated from different strategies, which leads to a new multi-layer multiple kernel learning problem. Promising results for text-based image retrieval on the NUS-WIDE dataset as well as news classification and text categorization on several real-world multi-view datasets clearly demonstrate that our proposed co-labeling approach achieves state-of-the-art performance for various multi-view weakly labeled learning problems including multi-view SSL, multi-view MIL and multi-view ROD.

Crystallization of bFGF-DNA Aptamer Complexes Using a Sparse Matrix Designed for Protein-Nucleic Acid Complexes

NASA Technical Reports Server (NTRS)

Cannone, Jaime J.; Barnes, Cindy L.; Achari, Aniruddha; Kundrot, Craig E.; Whitaker, Ann F. (Technical Monitor)

2001-01-01

The Sparse Matrix approach for obtaining lead crystallization conditions has proven to be very fruitful for the crystallization of proteins and nucleic acids. Here we report a Sparse Matrix developed specifically for the crystallization of protein-DNA complexes. This method is rapid and economical, typically requiring 2.5 mg of complex to test 48 conditions. The method was originally developed to crystallize basic fibroblast growth factor (bFGF) complexed with DNA sequences identified through in vitro selection, or SELEX, methods. Two DNA aptamers that bind with approximately nanomolar affinity and inhibit the angiogenic properties of bFGF were selected for co-crystallization. The Sparse Matrix produced lead crystallization conditions for both bFGF-DNA complexes.

Working with Sparse Data in Rated Language Tests: Generalizability Theory Applications

ERIC Educational Resources Information Center

Lin, Chih-Kai

2017-01-01

Sparse-rated data are common in operational performance-based language tests, as an inevitable result of assigning examinee responses to a fraction of available raters. The current study investigates the precision of two generalizability-theory methods (i.e., the rating method and the subdividing method) specifically designed to accommodate the…

Assessing the effects of cocaine dependence and pathological gambling using group-wise sparse representation of natural stimulus FMRI data.

PubMed

Ren, Yudan; Fang, Jun; Lv, Jinglei; Hu, Xintao; Guo, Cong Christine; Guo, Lei; Xu, Jiansong; Potenza, Marc N; Liu, Tianming

2017-08-01

Assessing functional brain activation patterns in neuropsychiatric disorders such as cocaine dependence (CD) or pathological gambling (PG) under naturalistic stimuli has received rising interest in recent years. In this paper, we propose and apply a novel group-wise sparse representation framework to assess differences in neural responses to naturalistic stimuli across multiple groups of participants (healthy control, cocaine dependence, pathological gambling). Specifically, natural stimulus fMRI (N-fMRI) signals from all three groups of subjects are aggregated into a big data matrix, which is then decomposed into a common signal basis dictionary and associated weight coefficient matrices via an effective online dictionary learning and sparse coding method. The coefficient matrices associated with each common dictionary atom are statistically assessed for each group separately. With the inter-group comparisons based on the group-wise correspondence established by the common dictionary, our experimental results demonstrated that the group-wise sparse coding and representation strategy can effectively and specifically detect brain networks/regions affected by different pathological conditions of the brain under naturalistic stimuli.

A multiple hold-out framework for Sparse Partial Least Squares.

PubMed

Monteiro, João M; Rao, Anil; Shawe-Taylor, John; Mourão-Miranda, Janaina

2016-09-15

Supervised classification machine learning algorithms may have limitations when studying brain diseases with heterogeneous populations, as the labels might be unreliable. More exploratory approaches, such as Sparse Partial Least Squares (SPLS), may provide insights into the brain's mechanisms by finding relationships between neuroimaging and clinical/demographic data. The identification of these relationships has the potential to improve the current understanding of disease mechanisms, refine clinical assessment tools, and stratify patients. SPLS finds multivariate associative effects in the data by computing pairs of sparse weight vectors, where each pair is used to remove its corresponding associative effect from the data by matrix deflation, before computing additional pairs. We propose a novel SPLS framework which selects the adequate number of voxels and clinical variables to describe each associative effect, and tests their reliability by fitting the model to different splits of the data. As a proof of concept, the approach was applied to find associations between grey matter probability maps and individual items of the Mini-Mental State Examination (MMSE) in a clinical sample with various degrees of dementia. The framework found two statistically significant associative effects between subsets of brain voxels and subsets of the questions/tasks. SPLS was compared with its non-sparse version (PLS). The use of projection deflation versus a classical PLS deflation was also tested in both PLS and SPLS. SPLS outperformed PLS, finding statistically significant effects and providing higher correlation values in hold-out data. Moreover, projection deflation provided better results. Copyright © 2016 The Author(s). Published by Elsevier B.V. All rights reserved.

Single molecule optical measurements of orientation and rotations of biological macromolecules

PubMed Central

Shroder, Deborah Y; Lippert, Lisa G; Goldman, Yale E

2016-01-01

The subdomains of macromolecules often undergo large orientation changes during their catalytic cycles that are essential for their activity. Tracking these rearrangements in real time opens a powerful window into the link between protein structure and functional output. Site-specific labeling of individual molecules with polarized optical probes and measuring their spatial orientation can give insight into the crucial conformational changes, dynamics, and fluctuations of macromolecules. Here we describe the range of single molecule optical technologies that can extract orientation information from these probes, we review the relevant types of probes and labeling techniques, and we highlight the advantages and disadvantages of these technologies for addressing specific inquiries. PMID:28192292

Regional differences in lectin binding patterns of vestibular hair cells

NASA Technical Reports Server (NTRS)

Baird, R. A.; Schuff, N. R.; Bancroft, J.

1993-01-01

Surface glycoconjugates of hair cells and supporting cells in the vestibular endorgans of the bullfrog were identified using biotinylated lectins with different carbohydrate specificities. Lectin binding in hair cells was consistent with the presence of glucose and mannose (CON A), galactose (RCA-I), N-acetylglucosamine (WGA), N-acetylgalactosamine (VVA), but not fucose (UEA-I) residues. Hair cells in the bullfrog sacculus, unlike those in the utriculus and semicircular canals, did not strain for N-acetylglucosamine (WGA) or N-acetylgalactosamine (VVA). By contrast, WGA and, to a lesser extent, VVA, differentially stained utricular and semicircular canal hair cells, labeling hair cells located in peripheral, but not central, regions. In mammals, WGA uniformly labeled Type I hair cells while labeling, as in the bullfrog, Type II hair cells only in peripheral regions. These regional variations were retained after enzymatic digestion. We conclude that vestibular hair cells differ in their surface glycoconjugates and that differences in lectin binding patterns can be used to identify hair cell types and to infer the epithelial origin of isolated vestibular hair cells.

Localization of P-type calcium channels in the central nervous system.

PubMed Central

Hillman, D; Chen, S; Aung, T T; Cherksey, B; Sugimori, M; Llinás, R R

1991-01-01

The distribution of the P-type calcium channel in the mammalian central nervous system has been demonstrated immunohistochemically by using a polyclonal specific antibody. This antibody was generated after P-channel isolation via a fraction from funnel-web spider toxin (FTX) that blocks the voltage-gated P channels in cerebellar Purkinje cells. In the cerebellar cortex, immunolabeling to the antibody appeared throughout the molecular layer, while all the other regions were negative. Intensely labeled patches of reactivity were seen on Purkinje cell dendrites, especially at bifurcations; much weaker reactivity was present in the soma and stem segment. Electron microscopic localization revealed labeled patches of plasma membrane on the soma, main dendrites, spiny branchlets, and spines; portions of the smooth endoplasmic reticulum were also labeled. Strong labeling was present in the periglomerular cells of the olfactory bulb and scattered neurons in the deep layer of the entorhinal and pyriform cortices. Neurons in the brainstem, habenula, nucleus of the trapezoid body and inferior olive and along the floor of the fourth ventricle were also labeled intensely. Medium-intensity reactions were observed in layer II pyramidal cells of the frontal cortex, the CA1 cells of the hippocampus, the lateral nucleus of the substantia nigra, lateral reticular nucleus, and spinal fifth nucleus. Light labeling was seen in the neocortex, striatum, and in some brainstem neurons. Images PMID:1651493

Localization of P-type calcium channels in the central nervous system.

PubMed

Hillman, D; Chen, S; Aung, T T; Cherksey, B; Sugimori, M; Llinás, R R

1991-08-15

The distribution of the P-type calcium channel in the mammalian central nervous system has been demonstrated immunohistochemically by using a polyclonal specific antibody. This antibody was generated after P-channel isolation via a fraction from funnel-web spider toxin (FTX) that blocks the voltage-gated P channels in cerebellar Purkinje cells. In the cerebellar cortex, immunolabeling to the antibody appeared throughout the molecular layer, while all the other regions were negative. Intensely labeled patches of reactivity were seen on Purkinje cell dendrites, especially at bifurcations; much weaker reactivity was present in the soma and stem segment. Electron microscopic localization revealed labeled patches of plasma membrane on the soma, main dendrites, spiny branchlets, and spines; portions of the smooth endoplasmic reticulum were also labeled. Strong labeling was present in the periglomerular cells of the olfactory bulb and scattered neurons in the deep layer of the entorhinal and pyriform cortices. Neurons in the brainstem, habenula, nucleus of the trapezoid body and inferior olive and along the floor of the fourth ventricle were also labeled intensely. Medium-intensity reactions were observed in layer II pyramidal cells of the frontal cortex, the CA1 cells of the hippocampus, the lateral nucleus of the substantia nigra, lateral reticular nucleus, and spinal fifth nucleus. Light labeling was seen in the neocortex, striatum, and in some brainstem neurons.

Physicians prefer greater detail in the biosimilar label (SmPC) - Results of a survey across seven European countries.

PubMed

Hallersten, Anna; Fürst, Walter; Mezzasalma, Riccardo

2016-06-01

In the European Union, labels (Summaries of Product Characteristics, SmPCs) of biosimilars and their reference products are in many instances almost identical (following a generic approach) despite different data requirements for the authorization of biosimilars and generics. To understand physicians' preferences on type and detail of information in the biosimilar label and their use of information sources when prescribing biologics including biosimilars, EuropaBio surveyed 210 physicians across seven European countries. Among surveyed physicians, 90.5% use the label frequently or occasionally as an information source and 87.2% deemed a clear statement on the origin of data helpful or very helpful. When comparing excerpts from the label of an authorized biosimilar and modified texts with additional information, 78.1-82.9% preferred the samples with additional information. This survey shows that the label is an appropriate vehicle for providing physicians with information about biologics and that physicians prefer more product-specific information in the biosimilar label. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Arabinogalactan proteins and pectin distribution during female gametogenesis in Quercus suber L.

PubMed Central

Lopes, Ana Lúcia; Costa, Mário Luís; Sobral, Rómulo; Costa, Maria Manuela; Amorim, Maria Isabel; Coimbra, Sílvia

2016-01-01

Background and Aims Quercus suber L. (cork oak) is one of the most important monoecious tree species in semi-arid regions of Southern Europe, with a high ecological value and economic potential. However, as a result of its long reproductive cycle, complex reproductive biology and recalcitrant seeds, conventional breeding is demanding. In its complex reproductive biology, little is known about the most important changes that occur during female gametogenesis. Arabinogalactan proteins (AGPs) and pectins are the main components of plant cell walls and have been reported to perform common functions in cell differentiation and organogenesis of reproductive plant structures. AGPs have been shown to serve as important molecules in several steps of the reproductive process in plants, working as signalling molecules, associated with the sporophyte–gametophyte transition, and pectins have been implicated in pollen–pistil interactions before double fertilization. In this study, the distribution of AGP and pectin epitopes was assessed during female gametogenesis. Methods Immunofluorescence labelling of female flower cells was performed with a set of monoclonal antibodies (mAbs) directed to the carbohydrate moiety of AGPs (JIM8 and JIM13) and pectic homogalacturonans (HGs) (mAbs JIM5 and JIM7). Key Results The selective labelling obtained with AGP and pectin mAbs JIM8, JIM13, JIM5 and JIM7 during Q. suber female gametogenesis shows that AGPs and pectic HG can work as markers for mapping gametophytic cell differentiation in this species. Pectic HG showed different distribution patterns, depending on their levels of methyl esterification. Methyl-esterified HGs showed a uniform distribution in the overall female flower cells before fertilization and a more specific pattern after fertilization. A low methyl-ester pectin distribution pattern during the different developmental stages appears to be related to the pathway that pollen tubes follow to reach the embryo sac. AGPs showed a more sparse distribution in early stages of development, but specific labelling is shown in the synergids and their filiform apparatus. Conclusions The labelling obtained with anti-AGP and anti-pectin mAbs in Q. suber female flower cells showed a dynamic distribution of AGPs and pectic HGs, which may render these molecules useful molecular markers during female gametogenesis. Changes occurring during development will be determined in order to help describe cork oak ovule structural properties before and after fertilization, providing new insight to better understand Q. suber female gametogenesis. PMID:26994101

40 CFR 1068.105 - What other provisions apply to me specifically if I manufacture equipment needing certified engines?

Code of Federal Regulations, 2010 CFR

2010-07-01

... inventory practice is to keep on hand a one-month supply of engines based on your upcoming production...) Send a request for duplicate labels in writing on your company's letterhead to the engine manufacturer. Include the following information in your request: (i) Identify the type of equipment and the specific...

Ligand-free palladium-mediated site-specific protein labeling inside gram-negative bacterial pathogens.

PubMed

Li, Jie; Lin, Shixian; Wang, Jie; Jia, Shang; Yang, Maiyun; Hao, Ziyang; Zhang, Xiaoyu; Chen, Peng R

2013-05-15

Palladium, a key transition metal in advancing modern organic synthesis, mediates diverse chemical conversions including many carbon-carbon bond formation reactions between organic compounds. However, expanding palladium chemistry for conjugation of biomolecules such as proteins, particularly within their native cellular context, is still in its infancy. Here we report the site-specific protein labeling inside pathogenic Gram-negative bacterial cells via a ligand-free palladium-mediated cross-coupling reaction. Two rationally designed pyrrolysine analogues bearing an aliphatic alkyne or an iodophenyl handle were first encoded in different enteric bacteria, which offered two facial handles for palladium-mediated Sonogashira coupling reaction on proteins within these pathogens. A GFP-based bioorthogonal reaction screening system was then developed, allowing evaluation of both the efficiency and the biocompatibilty of various palladium reagents in promoting protein-small molecule conjugation. The identified simple compound-Pd(NO3)2 exhibited high efficiency and biocompatibility for site-specific labeling of proteins in vitro and inside living E. coli cells. This Pd-mediated protein coupling method was further utilized to label and visualize a Type-III Secretion (T3S) toxin-OspF in Shigella cells. Our strategy may be generally applicable for imaging and tracking various virulence proteins within Gram-negative bacterial pathogens.

Quality evaluation of LC-MS/MS-based E. coli H antigen typing (MS-H) through label-free quantitative data analysis in a clinical sample setup.

PubMed

Cheng, Keding; Sloan, Angela; McCorrister, Stuart; Peterson, Lorea; Chui, Huixia; Drebot, Mike; Nadon, Celine; Knox, J David; Wang, Gehua

2014-12-01

The need for rapid and accurate H typing is evident during Escherichia coli outbreak situations. This study explores the transition of MS-H, a method originally developed for rapid H antigen typing of E. coli using LC-MS/MS of flagella digest of reference strains and some clinical strains, to E. coli isolates in clinical scenario through quantitative analysis and method validation. Motile and nonmotile strains were examined in batches to simulate clinical sample scenario. Various LC-MS/MS batch run procedures and MS-H typing rules were compared and summarized through quantitative analysis of MS-H data output for a standard method development. Label-free quantitative data analysis of MS-H typing was proven very useful for examining the quality of MS-H result and the effects of some sample carryovers from motile E. coli isolates. Based on this, a refined procedure and protein identification rule specific for clinical MS-H typing was established and validated. With LC-MS/MS batch run procedure and database search parameter unique for E. coli MS-H typing, the standard procedure maintained high accuracy and specificity in clinical situations, and its potential to be used in a clinical setting was clearly established. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Synthesis of empagliflozin, a novel and selective sodium-glucose co-transporter-2 inhibitor, labeled with carbon-14 and carbon-13.

PubMed

Hrapchak, Matt; Latli, Bachir; Wang, Xiao-Jun; Lee, Heewon; Campbell, Scot; Song, Jinhua J; Senanayake, Chris H

2014-10-01

Empagliflozin, (2S,3R,4R,5S,6R)-2-[4-chloro-3-[[4-[(3S)-oxolan-3-yl]oxyphenyl]methyl]phenyl]-6-(hydroxymethyl)oxane-3,4,5-triol was recently approved by the FDA for the treatment of chronic type 2 diabetes mellitus. Herein, we report the synthesis of carbon-13 and carbon-14 labeled empagliflozin. Carbon-13 labeled empagliflozin was prepared in five steps and in 34% overall chemical yield starting from the commercially available α-D-glucose-[(13)C6]. For the radiosynthesis, the carbon-14 atom was introduced in three different positions of the molecule. In the first synthesis, Carbon-14 D-(+)-gluconic acid δ-lactone was used to prepare specifically labeled empagliflozin in carbon-1 of the sugar moiety in four steps and in 19% overall radiochemical yield. Carbon-14 labeled empagliflozin with the radioactive atom in the benzylic position was obtained in eight steps and in 7% overall radiochemical yield. In the last synthesis carbon-14 uniformly labeled phenol was used to give [(14)C]empagliflozin in eight steps and in 18% overall radiochemical yield. In all these radiosyntheses, the specific activities of the final compounds were higher than 53 mCi/mmol, and the radiochemical purities were above 98.5%. Copyright © 2014 John Wiley & Sons, Ltd.

Alzheimer's disease detection via automatic 3D caudate nucleus segmentation using coupled dictionary learning with level set formulation.

PubMed

Al-Shaikhli, Saif Dawood Salman; Yang, Michael Ying; Rosenhahn, Bodo

2016-12-01

This paper presents a novel method for Alzheimer's disease classification via an automatic 3D caudate nucleus segmentation. The proposed method consists of segmentation and classification steps. In the segmentation step, we propose a novel level set cost function. The proposed cost function is constrained by a sparse representation of local image features using a dictionary learning method. We present coupled dictionaries: a feature dictionary of a grayscale brain image and a label dictionary of a caudate nucleus label image. Using online dictionary learning, the coupled dictionaries are learned from the training data. The learned coupled dictionaries are embedded into a level set function. In the classification step, a region-based feature dictionary is built. The region-based feature dictionary is learned from shape features of the caudate nucleus in the training data. The classification is based on the measure of the similarity between the sparse representation of region-based shape features of the segmented caudate in the test image and the region-based feature dictionary. The experimental results demonstrate the superiority of our method over the state-of-the-art methods by achieving a high segmentation (91.5%) and classification (92.5%) accuracy. In this paper, we find that the study of the caudate nucleus atrophy gives an advantage over the study of whole brain structure atrophy to detect Alzheimer's disease. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Sparse SPM: Group Sparse-dictionary learning in SPM framework for resting-state functional connectivity MRI analysis.

PubMed

Lee, Young-Beom; Lee, Jeonghyeon; Tak, Sungho; Lee, Kangjoo; Na, Duk L; Seo, Sang Won; Jeong, Yong; Ye, Jong Chul

2016-01-15

Recent studies of functional connectivity MR imaging have revealed that the default-mode network activity is disrupted in diseases such as Alzheimer's disease (AD). However, there is not yet a consensus on the preferred method for resting-state analysis. Because the brain is reported to have complex interconnected networks according to graph theoretical analysis, the independency assumption, as in the popular independent component analysis (ICA) approach, often does not hold. Here, rather than using the independency assumption, we present a new statistical parameter mapping (SPM)-type analysis method based on a sparse graph model where temporal dynamics at each voxel position are described as a sparse combination of global brain dynamics. In particular, a new concept of a spatially adaptive design matrix has been proposed to represent local connectivity that shares the same temporal dynamics. If we further assume that local network structures within a group are similar, the estimation problem of global and local dynamics can be solved using sparse dictionary learning for the concatenated temporal data across subjects. Moreover, under the homoscedasticity variance assumption across subjects and groups that is often used in SPM analysis, the aforementioned individual and group analyses using sparse dictionary learning can be accurately modeled by a mixed-effect model, which also facilitates a standard SPM-type group-level inference using summary statistics. Using an extensive resting fMRI data set obtained from normal, mild cognitive impairment (MCI), and Alzheimer's disease patient groups, we demonstrated that the changes in the default mode network extracted by the proposed method are more closely correlated with the progression of Alzheimer's disease. Copyright © 2015 Elsevier Inc. All rights reserved.

An empirical investigation of sparse distributed memory using discrete speech recognition

NASA Technical Reports Server (NTRS)

Danforth, Douglas G.

1990-01-01

Presented here is a step by step analysis of how the basic Sparse Distributed Memory (SDM) model can be modified to enhance its generalization capabilities for classification tasks. Data is taken from speech generated by a single talker. Experiments are used to investigate the theory of associative memories and the question of generalization from specific instances.

An Improved Sparse Representation over Learned Dictionary Method for Seizure Detection.

PubMed

Li, Junhui; Zhou, Weidong; Yuan, Shasha; Zhang, Yanli; Li, Chengcheng; Wu, Qi

2016-02-01

Automatic seizure detection has played an important role in the monitoring, diagnosis and treatment of epilepsy. In this paper, a patient specific method is proposed for seizure detection in the long-term intracranial electroencephalogram (EEG) recordings. This seizure detection method is based on sparse representation with online dictionary learning and elastic net constraint. The online learned dictionary could sparsely represent the testing samples more accurately, and the elastic net constraint which combines the 11-norm and 12-norm not only makes the coefficients sparse but also avoids over-fitting problem. First, the EEG signals are preprocessed using wavelet filtering and differential filtering, and the kernel function is applied to make the samples closer to linearly separable. Then the dictionaries of seizure and nonseizure are respectively learned from original ictal and interictal training samples with online dictionary optimization algorithm to compose the training dictionary. After that, the test samples are sparsely coded over the learned dictionary and the residuals associated with ictal and interictal sub-dictionary are calculated, respectively. Eventually, the test samples are classified as two distinct categories, seizure or nonseizure, by comparing the reconstructed residuals. The average segment-based sensitivity of 95.45%, specificity of 99.08%, and event-based sensitivity of 94.44% with false detection rate of 0.23/h and average latency of -5.14 s have been achieved with our proposed method.

Site-specific crosslinking of 4-thiouridine-modified human tRNA(3Lys) to reverse transcriptase from human immunodeficiency virus type I.

PubMed Central

Mishima, Y; Steitz, J A

1995-01-01

We have mapped specific RNA-protein contacts between human immunodeficiency virus (HIV) type I reverse transcriptase (RT) and its natural primer, human tRNA(3Lys), using a site-specific crosslinking strategy. Four different tRNA(3Lys) constructs with a single 32P-labeled 4-thiouridine (4-thioU) residue at positions -1, 16, 36 or 41 were synthesized. After incubation with RT followed by irradiation, crosslinks were localized to either the p66 or p51 subunit of RT by digestion with nuclease and SDS gel fractionation. 4-thioU at position -1 or 16 transferred label to the p66 subunit almost exclusively (> 90%), whereas position 36 labeled both p66 and p51 (3:1). Position 41 yielded no detectable crosslinks. The region of p66 contacted by position -1 of tRNA(3Lys) was localized to the 203 C-terminal amino acids of RT by CNBr cleavage, whereas a 127 amino acid-CNBr peptide (residues 230-357) from both p66 and p51 was labeled by position 36. Functionality of the 4-thioU-modified tRNA(3Lys)(-1) crosslinked to RT in the presence of an RNA but not a DNA template was demonstrated by the ability of the tRNA to be extended. These results localize the 5' half of the tRNA on the interface between the two RT subunits, closer to the RNase H domain than to the polymerase active site, in accord with previous suggestions. They argue further that a specific binding site for the 5' end of the primer tRNA(3Lys) may exist within the C-terminal portion of the p66 subunit, which could be important for the initiation of reverse transcription. Images PMID:7540137

Rapid optical imaging of EGF receptor expression with a single-chain antibody SNAP-tag fusion protein.

PubMed

Kampmeier, Florian; Niesen, Judith; Koers, Alexander; Ribbert, Markus; Brecht, Andreas; Fischer, Rainer; Kiessling, Fabian; Barth, Stefan; Thepen, Theo

2010-10-01

The epidermal growth factor receptor (EGFR) is overexpressed in several types of cancer and its inhibition can effectively inhibit tumour progression. The purpose of this study was to design an EGFR-specific imaging probe that combines efficient tumour targeting with rapid systemic clearance to facilitate non-invasive assessment of EGFR expression. Genetic fusion of a single-chain antibody fragment with the SNAP-tag produced a 48-kDa antibody derivative that can be covalently and site-specifically labelled with substrates containing 0 (6)-benzylguanine. The EGFR-specific single-chain variable fragment (scFv) fusion protein 425(scFv)SNAP was labelled with the near infrared (NIR) dye BG-747, and its accumulation, specificity and kinetics were monitored using NIR fluorescence imaging in a subcutaneous pancreatic carcinoma xenograft model. The 425(scFv)SNAP fusion protein accumulates rapidly and specifically at the tumour site. Its small size allows efficient renal clearance and a high tumour to background ratio (TBR) of 33.2 +/- 6.3 (n = 4) 10 h after injection. Binding of the labelled antibody was efficiently competed with a 20-fold excess of unlabelled probe, resulting in an average TBR of 6 +/- 1.35 (n = 4), which is similar to that obtained with a non-tumour-specific probe (5.44 +/- 1.92, n = 4). When compared with a full-length antibody against EGFR (cetuximab), 425(scFv)SNAP-747 showed significantly higher TBRs and complete clearance 72 h post-injection. The 425(scFv)SNAP fusion protein combines rapid and specific targeting of EGFR-positive tumours with a versatile and robust labelling technique that facilitates the attachment of fluorophores for use in optical imaging. The same approach could be used to couple a chelating agent for use in nuclear imaging.

Neutron-encoded Signatures Enable Product Ion Annotation From Tandem Mass Spectra*

PubMed Central

Richards, Alicia L.; Vincent, Catherine E.; Guthals, Adrian; Rose, Christopher M.; Westphall, Michael S.; Bandeira, Nuno; Coon, Joshua J.

2013-01-01

We report the use of neutron-encoded (NeuCode) stable isotope labeling of amino acids in cell culture for the purpose of C-terminal product ion annotation. Two NeuCode labeling isotopologues of lysine, 13C615N2 and 2H8, which differ by 36 mDa, were metabolically embedded in a sample proteome, and the resultant labeled proteins were combined, digested, and analyzed via liquid chromatography and mass spectrometry. With MS/MS scan resolving powers of ∼50,000 or higher, product ions containing the C terminus (i.e. lysine) appear as a doublet spaced by exactly 36 mDa, whereas N-terminal fragments exist as a single m/z peak. Through theory and experiment, we demonstrate that over 90% of all y-type product ions have detectable doublets. We report on an algorithm that can extract these neutron signatures with high sensitivity and specificity. In other words, of 15,503 y-type product ion peaks, the y-type ion identification algorithm correctly identified 14,552 (93.2%) based on detection of the NeuCode doublet; 6.8% were misclassified (i.e. other ion types that were assigned as y-type products). Searching NeuCode labeled yeast with PepNovo+ resulted in a 34% increase in correct de novo identifications relative to searching through MS/MS only. We use this tool to simplify spectra prior to database searching, to sort unmatched tandem mass spectra for spectral richness, for correlation of co-fragmented ions to their parent precursor, and for de novo sequence identification. PMID:24043425

Joint analysis of multiple high-dimensional data types using sparse matrix approximations of rank-1 with applications to ovarian and liver cancer.

PubMed

Okimoto, Gordon; Zeinalzadeh, Ashkan; Wenska, Tom; Loomis, Michael; Nation, James B; Fabre, Tiphaine; Tiirikainen, Maarit; Hernandez, Brenda; Chan, Owen; Wong, Linda; Kwee, Sandi

2016-01-01

Technological advances enable the cost-effective acquisition of Multi-Modal Data Sets (MMDS) composed of measurements for multiple, high-dimensional data types obtained from a common set of bio-samples. The joint analysis of the data matrices associated with the different data types of a MMDS should provide a more focused view of the biology underlying complex diseases such as cancer that would not be apparent from the analysis of a single data type alone. As multi-modal data rapidly accumulate in research laboratories and public databases such as The Cancer Genome Atlas (TCGA), the translation of such data into clinically actionable knowledge has been slowed by the lack of computational tools capable of analyzing MMDSs. Here, we describe the Joint Analysis of Many Matrices by ITeration (JAMMIT) algorithm that jointly analyzes the data matrices of a MMDS using sparse matrix approximations of rank-1. The JAMMIT algorithm jointly approximates an arbitrary number of data matrices by rank-1 outer-products composed of "sparse" left-singular vectors (eigen-arrays) that are unique to each matrix and a right-singular vector (eigen-signal) that is common to all the matrices. The non-zero coefficients of the eigen-arrays identify small subsets of variables for each data type (i.e., signatures) that in aggregate, or individually, best explain a dominant eigen-signal defined on the columns of the data matrices. The approximation is specified by a single "sparsity" parameter that is selected based on false discovery rate estimated by permutation testing. Multiple signals of interest in a given MDDS are sequentially detected and modeled by iterating JAMMIT on "residual" data matrices that result from a given sparse approximation. We show that JAMMIT outperforms other joint analysis algorithms in the detection of multiple signatures embedded in simulated MDDS. On real multimodal data for ovarian and liver cancer we show that JAMMIT identified multi-modal signatures that were clinically informative and enriched for cancer-related biology. Sparse matrix approximations of rank-1 provide a simple yet effective means of jointly reducing multiple, big data types to a small subset of variables that characterize important clinical and/or biological attributes of the bio-samples from which the data were acquired.

Group-sparse representation with dictionary learning for medical image denoising and fusion.

PubMed

Li, Shutao; Yin, Haitao; Fang, Leyuan

2012-12-01

Recently, sparse representation has attracted a lot of interest in various areas. However, the standard sparse representation does not consider the intrinsic structure, i.e., the nonzero elements occur in clusters, called group sparsity. Furthermore, there is no dictionary learning method for group sparse representation considering the geometrical structure of space spanned by atoms. In this paper, we propose a novel dictionary learning method, called Dictionary Learning with Group Sparsity and Graph Regularization (DL-GSGR). First, the geometrical structure of atoms is modeled as the graph regularization. Then, combining group sparsity and graph regularization, the DL-GSGR is presented, which is solved by alternating the group sparse coding and dictionary updating. In this way, the group coherence of learned dictionary can be enforced small enough such that any signal can be group sparse coded effectively. Finally, group sparse representation with DL-GSGR is applied to 3-D medical image denoising and image fusion. Specifically, in 3-D medical image denoising, a 3-D processing mechanism (using the similarity among nearby slices) and temporal regularization (to perverse the correlations across nearby slices) are exploited. The experimental results on 3-D image denoising and image fusion demonstrate the superiority of our proposed denoising and fusion approaches.

Fluorescent TEM-1 β-lactamase with wild-type activity as a rapid drug sensor for in vitro drug screening

PubMed Central

Cheong, Wing-Lam; Tsang, Ming-San; So, Pui-Kin; Chung, Wai-Hong; Leung, Yun-Chung; Chan, Pak-Ho

2014-01-01

We report the development of a novel fluorescent drug sensor from the bacterial drug target TEM-1 β-lactamase through the combined strategy of Val216→Cys216 mutation and fluorophore labelling for in vitro drug screening. The Val216 residue in TEM-1 is replaced with a cysteine residue, and the environment-sensitive fluorophore fluorescein-5-maleimide is specifically attached to the Cys216 residue in the V216C mutant for sensing drug binding at the active site. The labelled V216C mutant has wild-type catalytic activity and gives stronger fluorescence when β-lactam antibiotics bind to the active site. The labelled V216C mutant can differentiate between potent and impotent β-lactam antibiotics and can distinguish active-site binders from non-binders (including aggregates formed by small molecules in aqueous solution) by giving characteristic time-course fluorescence profiles. Mass spectrometric, molecular modelling and trypsin digestion results indicate that drug binding at the active site is likely to cause the fluorescein label to stay away from the active site and experience weaker fluorescence quenching by the residues around the active site, thus making the labelled V216C mutant to give stronger fluorescence in the drug-bound state. Given the ancestor's role of TEM-1 in the TEM family, the fluorescent TEM-1 drug sensor represents a good model to demonstrate the general combined strategy of Val216→Cys216 mutation and fluorophore labelling for fabricating tailor-made fluorescent drug sensors from other clinically significant TEM-type β-lactamase variants for in vitro drug screening. PMID:25074398

Joint detection and tracking of size-varying infrared targets based on block-wise sparse decomposition

NASA Astrophysics Data System (ADS)

Li, Miao; Lin, Zaiping; Long, Yunli; An, Wei; Zhou, Yiyu

2016-05-01

The high variability of target size makes small target detection in Infrared Search and Track (IRST) a challenging task. A joint detection and tracking method based on block-wise sparse decomposition is proposed to address this problem. For detection, the infrared image is divided into overlapped blocks, and each block is weighted on the local image complexity and target existence probabilities. Target-background decomposition is solved by block-wise inexact augmented Lagrange multipliers. For tracking, label multi-Bernoulli (LMB) tracker tracks multiple targets taking the result of single-frame detection as input, and provides corresponding target existence probabilities for detection. Unlike fixed-size methods, the proposed method can accommodate size-varying targets, due to no special assumption for the size and shape of small targets. Because of exact decomposition, classical target measurements are extended and additional direction information is provided to improve tracking performance. The experimental results show that the proposed method can effectively suppress background clutters, detect and track size-varying targets in infrared images.

Recording 13C-15N HMQC 2D sparse spectra in solids in 30 s

NASA Astrophysics Data System (ADS)

Kupče, Ēriks; Trébosc, Julien; Perrone, Barbara; Lafon, Olivier; Amoureux, Jean-Paul

2018-03-01

We propose a dipolar HMQC Hadamard-encoded (D-HMQC-Hn) experiment for fast 2D correlations of abundant nuclei in solids. The main limitation of the Hadamard methods resides in the length of the encoding pulses, which results from a compromise between the selectivity and the sensitivity due to losses. For this reason, these methods should mainly be used with sparse spectra, and they profit from the increased separation of the resonances at high magnetic fields. In the case of the D-HMQC-Hn experiments, we give a simple rule that allows directly setting the optimum length of the selective pulses, versus the minimum separation of the resonances in the indirect dimension. The demonstration has been performed on a fully 13C,15N labelled f-MLF sample, and it allowed recording the build-up curves of the 13C-15N cross-peaks within 10 min. However, the method could also be used in the case of less sensitive samples, but with more accumulations.

Immunogenicity is preferentially induced in sparse dendritic cell cultures

PubMed Central

Nasi, Aikaterini; Bollampalli, Vishnu Priya; Sun, Meng; Chen, Yang; Amu, Sylvie; Nylén, Susanne; Eidsmo, Liv; Rothfuchs, Antonio Gigliotti; Réthi, Bence

2017-01-01

We have previously shown that human monocyte-derived dendritic cells (DCs) acquired different characteristics in dense or sparse cell cultures. Sparsity promoted the development of IL-12 producing migratory DCs, whereas dense cultures increased IL-10 production. Here we analysed whether the density-dependent endogenous breaks could modulate DC-based vaccines. Using murine bone marrow-derived DC models we show that sparse cultures were essential to achieve several key functions required for immunogenic DC vaccines, including mobility to draining lymph nodes, recruitment and massive proliferation of antigen-specific CD4+ T cells, in addition to their TH1 polarization. Transcription analyses confirmed higher commitment in sparse cultures towards T cell activation, whereas DCs obtained from dense cultures up-regulated immunosuppressive pathway components and genes suggesting higher differentiation plasticity towards osteoclasts. Interestingly, we detected a striking up-regulation of fatty acid and cholesterol biosynthesis pathways in sparse cultures, suggesting an important link between DC immunogenicity and lipid homeostasis regulation. PMID:28276533

Synaptic and Network Mechanisms of Sparse and Reliable Visual Cortical Activity during Nonclassical Receptive Field Stimulation

PubMed Central

Haider, Bilal; Krause, Matthew R.; Duque, Alvaro; Yu, Yuguo; Touryan, Jonathan; Mazer, James A.; McCormick, David A.

2011-01-01

SUMMARY During natural vision, the entire visual field is stimulated by images rich in spatiotemporal structure. Although many visual system studies restrict stimuli to the classical receptive field (CRF), it is known that costimulation of the CRF and the surrounding nonclassical receptive field (nCRF) increases neuronal response sparseness. The cellular and network mechanisms underlying increased response sparseness remain largely unexplored. Here we show that combined CRF + nCRF stimulation increases the sparseness, reliability, and precision of spiking and membrane potential responses in classical regular spiking (RSC) pyramidal neurons of cat primary visual cortex. Conversely, fast-spiking interneurons exhibit increased activity and decreased selectivity during CRF + nCRF stimulation. The increased sparseness and reliability of RSC neuron spiking is associated with increased inhibitory barrages and narrower visually evoked synaptic potentials. Our experimental observations were replicated with a simple computational model, suggesting that network interactions among neuronal subtypes ultimately sharpen recurrent excitation, producing specific and reliable visual responses. PMID:20152117

Characterization of TLX expression in neural stem cells and progenitor cells in adult brains.

PubMed

Li, Shengxiu; Sun, Guoqiang; Murai, Kiyohito; Ye, Peng; Shi, Yanhong

2012-01-01

TLX has been shown to play an important role in regulating the self-renewal and proliferation of neural stem cells in adult brains. However, the cellular distribution of endogenous TLX protein in adult brains remains to be elucidated. In this study, we used immunostaining with a TLX-specific antibody to show that TLX is expressed in both neural stem cells and transit-amplifying neural progenitor cells in the subventricular zone (SVZ) of adult mouse brains. Then, using a double thymidine analog labeling approach, we showed that almost all of the self-renewing neural stem cells expressed TLX. Interestingly, most of the TLX-positive cells in the SVZ represented the thymidine analog-negative, relatively quiescent neural stem cell population. Using cell type markers and short-term BrdU labeling, we demonstrated that TLX was also expressed in the Mash1+ rapidly dividing type C cells. Furthermore, loss of TLX expression dramatically reduced BrdU label-retaining neural stem cells and the actively dividing neural progenitor cells in the SVZ, but substantially increased GFAP staining and extended GFAP processes. These results suggest that TLX is essential to maintain the self-renewing neural stem cells in the SVZ and that the GFAP+ cells in the SVZ lose neural stem cell property upon loss of TLX expression. Understanding the cellular distribution of TLX and its function in specific cell types may provide insights into the development of therapeutic tools for neurodegenerative diseases by targeting TLX in neural stem/progenitors cells.

Characterization of TLX Expression in Neural Stem Cells and Progenitor Cells in Adult Brains

PubMed Central

Li, Shengxiu; Sun, Guoqiang; Murai, Kiyohito; Ye, Peng; Shi, Yanhong

2012-01-01

TLX has been shown to play an important role in regulating the self-renewal and proliferation of neural stem cells in adult brains. However, the cellular distribution of endogenous TLX protein in adult brains remains to be elucidated. In this study, we used immunostaining with a TLX-specific antibody to show that TLX is expressed in both neural stem cells and transit-amplifying neural progenitor cells in the subventricular zone (SVZ) of adult mouse brains. Then, using a double thymidine analog labeling approach, we showed that almost all of the self-renewing neural stem cells expressed TLX. Interestingly, most of the TLX-positive cells in the SVZ represented the thymidine analog-negative, relatively quiescent neural stem cell population. Using cell type markers and short-term BrdU labeling, we demonstrated that TLX was also expressed in the Mash1+ rapidly dividing type C cells. Furthermore, loss of TLX expression dramatically reduced BrdU label-retaining neural stem cells and the actively dividing neural progenitor cells in the SVZ, but substantially increased GFAP staining and extended GFAP processes. These results suggest that TLX is essential to maintain the self-renewing neural stem cells in the SVZ and that the GFAP+ cells in the SVZ lose neural stem cell property upon loss of TLX expression.Understanding the cellular distribution of TLX and its function in specific cell types may provide insights into the development of therapeutic tools for neurodegenerative diseases by targeting TLX in neural stem/progenitors cells. PMID:22952666

Computational phenotype discovery using unsupervised feature learning over noisy, sparse, and irregular clinical data.

PubMed

Lasko, Thomas A; Denny, Joshua C; Levy, Mia A

2013-01-01

Inferring precise phenotypic patterns from population-scale clinical data is a core computational task in the development of precision, personalized medicine. The traditional approach uses supervised learning, in which an expert designates which patterns to look for (by specifying the learning task and the class labels), and where to look for them (by specifying the input variables). While appropriate for individual tasks, this approach scales poorly and misses the patterns that we don't think to look for. Unsupervised feature learning overcomes these limitations by identifying patterns (or features) that collectively form a compact and expressive representation of the source data, with no need for expert input or labeled examples. Its rising popularity is driven by new deep learning methods, which have produced high-profile successes on difficult standardized problems of object recognition in images. Here we introduce its use for phenotype discovery in clinical data. This use is challenging because the largest source of clinical data - Electronic Medical Records - typically contains noisy, sparse, and irregularly timed observations, rendering them poor substrates for deep learning methods. Our approach couples dirty clinical data to deep learning architecture via longitudinal probability densities inferred using Gaussian process regression. From episodic, longitudinal sequences of serum uric acid measurements in 4368 individuals we produced continuous phenotypic features that suggest multiple population subtypes, and that accurately distinguished (0.97 AUC) the uric-acid signatures of gout vs. acute leukemia despite not being optimized for the task. The unsupervised features were as accurate as gold-standard features engineered by an expert with complete knowledge of the domain, the classification task, and the class labels. Our findings demonstrate the potential for achieving computational phenotype discovery at population scale. We expect such data-driven phenotypes to expose unknown disease variants and subtypes and to provide rich targets for genetic association studies.

Computational Phenotype Discovery Using Unsupervised Feature Learning over Noisy, Sparse, and Irregular Clinical Data

PubMed Central

Lasko, Thomas A.; Denny, Joshua C.; Levy, Mia A.

2013-01-01

Inferring precise phenotypic patterns from population-scale clinical data is a core computational task in the development of precision, personalized medicine. The traditional approach uses supervised learning, in which an expert designates which patterns to look for (by specifying the learning task and the class labels), and where to look for them (by specifying the input variables). While appropriate for individual tasks, this approach scales poorly and misses the patterns that we don’t think to look for. Unsupervised feature learning overcomes these limitations by identifying patterns (or features) that collectively form a compact and expressive representation of the source data, with no need for expert input or labeled examples. Its rising popularity is driven by new deep learning methods, which have produced high-profile successes on difficult standardized problems of object recognition in images. Here we introduce its use for phenotype discovery in clinical data. This use is challenging because the largest source of clinical data – Electronic Medical Records – typically contains noisy, sparse, and irregularly timed observations, rendering them poor substrates for deep learning methods. Our approach couples dirty clinical data to deep learning architecture via longitudinal probability densities inferred using Gaussian process regression. From episodic, longitudinal sequences of serum uric acid measurements in 4368 individuals we produced continuous phenotypic features that suggest multiple population subtypes, and that accurately distinguished (0.97 AUC) the uric-acid signatures of gout vs. acute leukemia despite not being optimized for the task. The unsupervised features were as accurate as gold-standard features engineered by an expert with complete knowledge of the domain, the classification task, and the class labels. Our findings demonstrate the potential for achieving computational phenotype discovery at population scale. We expect such data-driven phenotypes to expose unknown disease variants and subtypes and to provide rich targets for genetic association studies. PMID:23826094

Modeling an in-register, parallel "iowa" aβ fibril structure using solid-state NMR data from labeled samples with rosetta.

PubMed

Sgourakis, Nikolaos G; Yau, Wai-Ming; Qiang, Wei

2015-01-06

Determining the structures of amyloid fibrils is an important first step toward understanding the molecular basis of neurodegenerative diseases. For β-amyloid (Aβ) fibrils, conventional solid-state NMR structure determination using uniform labeling is limited by extensive peak overlap. We describe the characterization of a distinct structural polymorph of Aβ using solid-state NMR, transmission electron microscopy (TEM), and Rosetta model building. First, the overall fibril arrangement is established using mass-per-length measurements from TEM. Then, the fibril backbone arrangement, stacking registry, and "steric zipper" core interactions are determined using a number of solid-state NMR techniques on sparsely (13)C-labeled samples. Finally, we perform Rosetta structure calculations with an explicitly symmetric representation of the system. We demonstrate the power of the hybrid Rosetta/NMR approach by modeling the in-register, parallel "Iowa" mutant (D23N) at high resolution (1.2Å backbone rmsd). The final models are validated using an independent set of NMR experiments that confirm key features. Copyright © 2015 Elsevier Ltd. All rights reserved.

Learning Low-Rank Class-Specific Dictionary and Sparse Intra-Class Variant Dictionary for Face Recognition.

PubMed

Tang, Xin; Feng, Guo-Can; Li, Xiao-Xin; Cai, Jia-Xin

2015-01-01

Face recognition is challenging especially when the images from different persons are similar to each other due to variations in illumination, expression, and occlusion. If we have sufficient training images of each person which can span the facial variations of that person under testing conditions, sparse representation based classification (SRC) achieves very promising results. However, in many applications, face recognition often encounters the small sample size problem arising from the small number of available training images for each person. In this paper, we present a novel face recognition framework by utilizing low-rank and sparse error matrix decomposition, and sparse coding techniques (LRSE+SC). Firstly, the low-rank matrix recovery technique is applied to decompose the face images per class into a low-rank matrix and a sparse error matrix. The low-rank matrix of each individual is a class-specific dictionary and it captures the discriminative feature of this individual. The sparse error matrix represents the intra-class variations, such as illumination, expression changes. Secondly, we combine the low-rank part (representative basis) of each person into a supervised dictionary and integrate all the sparse error matrix of each individual into a within-individual variant dictionary which can be applied to represent the possible variations between the testing and training images. Then these two dictionaries are used to code the query image. The within-individual variant dictionary can be shared by all the subjects and only contribute to explain the lighting conditions, expressions, and occlusions of the query image rather than discrimination. At last, a reconstruction-based scheme is adopted for face recognition. Since the within-individual dictionary is introduced, LRSE+SC can handle the problem of the corrupted training data and the situation that not all subjects have enough samples for training. Experimental results show that our method achieves the state-of-the-art results on AR, FERET, FRGC and LFW databases.

Learning Low-Rank Class-Specific Dictionary and Sparse Intra-Class Variant Dictionary for Face Recognition

PubMed Central

Tang, Xin; Feng, Guo-can; Li, Xiao-xin; Cai, Jia-xin

2015-01-01

Face recognition is challenging especially when the images from different persons are similar to each other due to variations in illumination, expression, and occlusion. If we have sufficient training images of each person which can span the facial variations of that person under testing conditions, sparse representation based classification (SRC) achieves very promising results. However, in many applications, face recognition often encounters the small sample size problem arising from the small number of available training images for each person. In this paper, we present a novel face recognition framework by utilizing low-rank and sparse error matrix decomposition, and sparse coding techniques (LRSE+SC). Firstly, the low-rank matrix recovery technique is applied to decompose the face images per class into a low-rank matrix and a sparse error matrix. The low-rank matrix of each individual is a class-specific dictionary and it captures the discriminative feature of this individual. The sparse error matrix represents the intra-class variations, such as illumination, expression changes. Secondly, we combine the low-rank part (representative basis) of each person into a supervised dictionary and integrate all the sparse error matrix of each individual into a within-individual variant dictionary which can be applied to represent the possible variations between the testing and training images. Then these two dictionaries are used to code the query image. The within-individual variant dictionary can be shared by all the subjects and only contribute to explain the lighting conditions, expressions, and occlusions of the query image rather than discrimination. At last, a reconstruction-based scheme is adopted for face recognition. Since the within-individual dictionary is introduced, LRSE+SC can handle the problem of the corrupted training data and the situation that not all subjects have enough samples for training. Experimental results show that our method achieves the state-of-the-art results on AR, FERET, FRGC and LFW databases. PMID:26571112

Sparse representation based biomarker selection for schizophrenia with integrated analysis of fMRI and SNPs.

PubMed

Cao, Hongbao; Duan, Junbo; Lin, Dongdong; Shugart, Yin Yao; Calhoun, Vince; Wang, Yu-Ping

2014-11-15

Integrative analysis of multiple data types can take advantage of their complementary information and therefore may provide higher power to identify potential biomarkers that would be missed using individual data analysis. Due to different natures of diverse data modality, data integration is challenging. Here we address the data integration problem by developing a generalized sparse model (GSM) using weighting factors to integrate multi-modality data for biomarker selection. As an example, we applied the GSM model to a joint analysis of two types of schizophrenia data sets: 759,075 SNPs and 153,594 functional magnetic resonance imaging (fMRI) voxels in 208 subjects (92 cases/116 controls). To solve this small-sample-large-variable problem, we developed a novel sparse representation based variable selection (SRVS) algorithm, with the primary aim to identify biomarkers associated with schizophrenia. To validate the effectiveness of the selected variables, we performed multivariate classification followed by a ten-fold cross validation. We compared our proposed SRVS algorithm with an earlier sparse model based variable selection algorithm for integrated analysis. In addition, we compared with the traditional statistics method for uni-variant data analysis (Chi-squared test for SNP data and ANOVA for fMRI data). Results showed that our proposed SRVS method can identify novel biomarkers that show stronger capability in distinguishing schizophrenia patients from healthy controls. Moreover, better classification ratios were achieved using biomarkers from both types of data, suggesting the importance of integrative analysis. Copyright © 2014 Elsevier Inc. All rights reserved.

Specific identification of human papillomavirus type in cervical smears and paraffin sections by in situ hybridization with radioactive probes: a preliminary communication

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gupta, J.; Gendelman, H.E.; Naghashfar, Z.

1985-01-01

Cervical Papanicolaou smears and paraffin sections of biopsy specimens obtained from women attending dysplasia clinics were examined for viral DNA sequences by in situ hybridization technique using TVS-labeled cloned recombinant DNA probes of human papillomavirus (HPV) types 6, 11, and 16. These and one unrelated DNA probe complementary to measles virus RNA were labeled by nick translation using either one or two TVS-labeled nucleotides. Paraffin sections and cervical smears were collected on pretreated slides, hybridized with the probes under stringent or nonstringent conditions for 50 h, and autoradiographed. Additional cervical specimens from the same women were examined for the presencemore » of genus-specific papillomavirus capsid antigen by the immunoperoxidase technique. Preliminary results may be summarized as follows. The infecting virus could be identified in smears as well as in sections. Viral DNA sequences were detected only when there were condylomatous cells in the specimen and in only a proportion of the condylomatous cells. Even under stringent conditions, some specimens reacted with both HPV-6 and HPV-11. In some instances, the cells did not hybridize with any of the three probes even when duplicate specimens contained frankly condylomatous, capsid antigen-positive cells. In situ hybridization of Papanicolaou smears or of tissue sections is a practical method for diagnosis and follow-up of specific papillomavirus infection using routinely collected material.« less

Risk management strategies in the Physicians' Desk Reference product labels for pregnancy category X drugs.

PubMed

Uhl, Kathleen; Kennedy, Dianne L; Kweder, Sandra L

2002-01-01

Drugs that carry a concern for teratogenicity are often classified as pregnancy category X in the drug label and contraindicated for use during pregnancy. Many drug labels can be found in the Physicians' Desk Reference (PDR), a widely used source of drug information by American clinicians and patients. To review product labelling in the electronic PDR for the pregnancy category X products for pregnancy prevention risk management components in labelling. The electronic version of the 2001 and 2002 PDR was searched for 'pregnancy category X' products using the full text search feature. All product labels identified were retrieved and reviewed for trade name, generic name, manufacturer and indication. Product labels were manually searched for any pregnancy prevention risk management strategies included in labelling. Those labels that had specific pregnancy prevention risk management strategies were further evaluated. One hundred and seventeen pregnancy category X products were obtained from 2249 products searched in the 2001 PDR database and 124 pregnancy category X products were obtained from the 2150 products in the 2002 PDR database. All pregnancy category X products identified were drug products. The label/package insert for each drug was reviewed to identify risk management strategies for pregnancy prevention. The majority of the labels include as the sole risk management strategy either a black box warning and/or a contraindication for use in women who are or may become pregnant. Only 13 drugs contained specific pregnancy prevention risk management strategies in the label directing the clinician and/or patient, e.g. frequency of pregnancy testing, number and type of contraception methods. Two drugs, bexarotene capsules and gel, were only included in the 2001 PDR. Three drugs, isotretinoin, acitretin, and thalidomide, have formal pregnancy prevention risk management programmes. This study demonstrates the varied risk management approaches in labelling for pregnancy prevention for pregnancy category X drugs. There is a need for consistency in the classification of pregnancy category X products and the pregnancy prevention risk management strategies utilised in the labelling for them.

Dual-mode fluorophore-doped nickel nitrilotriacetic acid-modified silica nanoparticles combine histidine-tagged protein purification with site-specific fluorophore labeling.

PubMed

Kim, Sung Hoon; Jeyakumar, M; Katzenellenbogen, John A

2007-10-31

We present the first example of a fluorophore-doped nickel chelate surface-modified silica nanoparticle that functions in a dual mode, combining histidine-tagged protein purification with site-specific fluorophore labeling. Tetramethylrhodamine (TMR)-doped silica nanoparticles, estimated to contain 700-900 TMRs per ca. 23 nm particle, were surface modified with nitrilotriacetic acid (NTA), producing TMR-SiO2-NTA-Ni2+. Silica-embedded TMR retains very high quantum yield, is resistant to quenching by buffer components, and is modestly quenched and only to a certain depth (ca. 2 nm) by surface-attached Ni2+. When exposed to a bacterial lysate containing estrogen receptor alpha ligand binding domain (ERalpha) as a minor component, these beads showed very high specificity binding, enabling protein purification in one step. The capacity and specificity of these beads for binding a his-tagged protein were characterized by electrophoresis, radiometric counting, and MALDI-TOF MS. ERalpha, bound to TMR-SiO2-NTA-Ni++ beads in a site-specific manner, exhibited good activity for ligand binding and for ligand-induced binding to coactivators in solution FRET experiments and protein microarray fluorometric and FRET assays. This dual-mode type TMR-SiO2-NTA-Ni2+ system represents a powerful combination of one-step histidine-tagged protein purification and site-specific labeling with multiple fluorophore species.

Toddler drinks, formulas, and milks: Labeling practices and policy implications.

PubMed

Pomeranz, Jennifer L; Romo Palafox, Maria J; Harris, Jennifer L

2018-04-01

Toddler drinks are a growing category of drinks marketed for young children 9-36 months old. Medical experts do not recommend them, and public health experts raise concerns about misleading labeling practices. In the U.S., the toddler drink category includes two types of products: transition formulas, marketed for infants and toddlers 9-24 months; and toddler milks, for children 12-36 months old. The objective of this study was to evaluate toddler drink labeling practices in light of U.S. food labeling policy and international labeling recommendations. In January 2017, we conducted legal research on U.S. food label laws and regulations; collected and evaluated toddler drink packages, including nutrition labels and claims; and compared toddler drink labels with the same brand's infant formula labels. We found that the U.S. has a regulatory structure for food labels and distinct policies for infant formula, but no laws specific to toddler drinks. Toddler drink labels utilized various terms and images to identify products and intended users; made multiple health and nutrition claims; and some stated there was scientific or expert support for the product. Compared to the same manufacturer's infant formula labels, most toddler drink labels utilized similar colors, branding, logos, and graphics. Toddler drink labels may confuse consumers about their nutrition and health benefits and the appropriateness of these products for young children. To support healthy toddler diets and well-informed decision-making by caregivers, the FDA can provide guidance or propose regulations clarifying permissible toddler drink labels and manufacturers should end inappropriate labeling practices. Copyright © 2018 Elsevier Inc. All rights reserved.

Improved FastICA algorithm in fMRI data analysis using the sparsity property of the sources.

PubMed

Ge, Ruiyang; Wang, Yubao; Zhang, Jipeng; Yao, Li; Zhang, Hang; Long, Zhiying

2016-04-01

As a blind source separation technique, independent component analysis (ICA) has many applications in functional magnetic resonance imaging (fMRI). Although either temporal or spatial prior information has been introduced into the constrained ICA and semi-blind ICA methods to improve the performance of ICA in fMRI data analysis, certain types of additional prior information, such as the sparsity, has seldom been added to the ICA algorithms as constraints. In this study, we proposed a SparseFastICA method by adding the source sparsity as a constraint to the FastICA algorithm to improve the performance of the widely used FastICA. The source sparsity is estimated through a smoothed ℓ0 norm method. We performed experimental tests on both simulated data and real fMRI data to investigate the feasibility and robustness of SparseFastICA and made a performance comparison between SparseFastICA, FastICA and Infomax ICA. Results of the simulated and real fMRI data demonstrated the feasibility and robustness of SparseFastICA for the source separation in fMRI data. Both the simulated and real fMRI experimental results showed that SparseFastICA has better robustness to noise and better spatial detection power than FastICA. Although the spatial detection power of SparseFastICA and Infomax did not show significant difference, SparseFastICA had faster computation speed than Infomax. SparseFastICA was comparable to the Infomax algorithm with a faster computation speed. More importantly, SparseFastICA outperformed FastICA in robustness and spatial detection power and can be used to identify more accurate brain networks than FastICA algorithm. Copyright © 2016 Elsevier B.V. All rights reserved.

Superposition and alignment of labeled point clouds.

PubMed

Fober, Thomas; Glinca, Serghei; Klebe, Gerhard; Hüllermeier, Eyke

2011-01-01

Geometric objects are often represented approximately in terms of a finite set of points in three-dimensional euclidean space. In this paper, we extend this representation to what we call labeled point clouds. A labeled point cloud is a finite set of points, where each point is not only associated with a position in three-dimensional space, but also with a discrete class label that represents a specific property. This type of model is especially suitable for modeling biomolecules such as proteins and protein binding sites, where a label may represent an atom type or a physico-chemical property. Proceeding from this representation, we address the question of how to compare two labeled points clouds in terms of their similarity. Using fuzzy modeling techniques, we develop a suitable similarity measure as well as an efficient evolutionary algorithm to compute it. Moreover, we consider the problem of establishing an alignment of the structures in the sense of a one-to-one correspondence between their basic constituents. From a biological point of view, alignments of this kind are of great interest, since mutually corresponding molecular constituents offer important information about evolution and heredity, and can also serve as a means to explain a degree of similarity. In this paper, we therefore develop a method for computing pairwise or multiple alignments of labeled point clouds. To this end, we proceed from an optimal superposition of the corresponding point clouds and construct an alignment which is as much as possible in agreement with the neighborhood structure established by this superposition. We apply our methods to the structural analysis of protein binding sites.

X-ray computed tomography using curvelet sparse regularization.

PubMed

Wieczorek, Matthias; Frikel, Jürgen; Vogel, Jakob; Eggl, Elena; Kopp, Felix; Noël, Peter B; Pfeiffer, Franz; Demaret, Laurent; Lasser, Tobias

2015-04-01

Reconstruction of x-ray computed tomography (CT) data remains a mathematically challenging problem in medical imaging. Complementing the standard analytical reconstruction methods, sparse regularization is growing in importance, as it allows inclusion of prior knowledge. The paper presents a method for sparse regularization based on the curvelet frame for the application to iterative reconstruction in x-ray computed tomography. In this work, the authors present an iterative reconstruction approach based on the alternating direction method of multipliers using curvelet sparse regularization. Evaluation of the method is performed on a specifically crafted numerical phantom dataset to highlight the method's strengths. Additional evaluation is performed on two real datasets from commercial scanners with different noise characteristics, a clinical bone sample acquired in a micro-CT and a human abdomen scanned in a diagnostic CT. The results clearly illustrate that curvelet sparse regularization has characteristic strengths. In particular, it improves the restoration and resolution of highly directional, high contrast features with smooth contrast variations. The authors also compare this approach to the popular technique of total variation and to traditional filtered backprojection. The authors conclude that curvelet sparse regularization is able to improve reconstruction quality by reducing noise while preserving highly directional features.

Melatonin Decreases Glucose Metabolism in Prostate Cancer Cells: A 13C Stable Isotope-Resolved Metabolomic Study.

PubMed

Hevia, David; Gonzalez-Menendez, Pedro; Fernandez-Fernandez, Mario; Cueto, Sergio; Rodriguez-Gonzalez, Pablo; Garcia-Alonso, Jose I; Mayo, Juan C; Sainz, Rosa M

2017-07-26

The pineal neuroindole melatonin exerts an exceptional variety of systemic functions. Some of them are exerted through its specific membrane receptors type 1 and type 2 (MT1 and MT2) while others are mediated by receptor-independent mechanisms. A potential transport of melatonin through facilitative glucose transporters (GLUT/ SLC2A ) was proposed in prostate cancer cells. The prostate cells have a particular metabolism that changes during tumor progression. During the first steps of carcinogenesis, oxidative phosphorylation is reactivated while the switch to the "Warburg effect" only occurs in advanced tumors and in the metastatic stage. Here, we investigated whether melatonin might change prostate cancer cell metabolism. To do so, 13 C stable isotope-resolved metabolomics in androgen sensitive LNCaP and insensitive PC-3 prostate cancer cells were employed. In addition to metabolite 13 C-labeling, ATP/AMP levels, and lactate dehydrogenase or pentose phosphate pathway activity were measured. Melatonin reduces lactate labeling in androgen-sensitive cells and it also lowers 13 C-labeling of tricarboxylic acid cycle metabolites and ATP production. In addition, melatonin reduces lactate 13 C-labeling in androgen insensitive prostate cancer cells. Results demonstrated that melatonin limits glycolysis as well as the tricarboxylic acid cycle and pentose phosphate pathway in prostate cancer cells, suggesting that the reduction of glucose uptake is a major target of the indole in this tumor type.

38 CFR 41.520 - Major program determination.

Code of Federal Regulations, 2011 CFR

2011-07-01

... auditor shall identify the larger Federal programs, which shall be labeled Type A programs. Type A... programs not labeled Type A under paragraph (b)(1) of this section shall be labeled Type B programs. (3... programs as Type A programs. When a Federal program providing loans significantly affects the number or...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jomary, C.; Beaudet, A.; Gairin, J.E.

Distribution of {kappa} opioid receptors was examined by EM radioautography in sections of guinea pig neostriatum with the selective {sup 125}I-labeled dynorphin analog (D-Pro{sup 10})dynorphin-(1-11). Most specifically labeled binding sites were found by probability circle analysis to be associated with neuronal membrane appositions. Because of limitations in resolution of the method, the radioactive sources could not be ascribed directly to either one of the apposed plasma membranes. Nevertheless, three lines of evidence favored a predominant association of ligand with dendrites of intrinsic striatal neurons: (1) the high frequency with which labeled interfaces implicated a dendrite, (2) the enrichment of dendrodendriticmore » interfaces, and (3) the occurrence of dendritic profiles labeled at several contact points along their plasma membranes. A small proportion of labeled sites was associated with axo-axonic interfaces, which may subserve the {kappa} opioid-induced regulation of presynaptic dopamine and acetylcholine release documented in guinea pig neostriatum. These results support the hypothesis that in mammalian brain {kappa} opioid receptors are conformationally and functionally distinct from {mu} and {delta} types.« less

Preparation of ⁶⁸Ga-labelled DOTA-peptides using a manual labelling approach for small-animal PET imaging.

PubMed

Romero, Eduardo; Martínez, Alfonso; Oteo, Marta; García, Angel; Morcillo, Miguel Angel

2016-01-01

(68)Ga-DOTA-peptides are a promising PET radiotracers used in the detection of different tumours types due to their ability for binding specifically receptors overexpressed in these. Furthermore, (68)Ga can be produced by a (68)Ge/(68)Ga generator on site which is a very good alternative to cyclotron-based PET isotopes. Here, we describe a manual labelling approach for the synthesis of (68)Ga-labelled DOTA-peptides based on concentration and purification of the commercial (68)Ga/(68)Ga generator eluate using an anion exchange-cartridge. (68)Ga-DOTA-TATE was used to image a pheochromocytoma xenograft mouse model by a microPET/CT scanner. The method described provides satisfactory results, allowing the subsequent (68)Ga use to label DOTA-peptides. The simplicity of the method along with its implementation reduced cost, makes it useful in preclinical PET studies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Bioorthogonal Metabolic Labeling of Nascent RNA in Neurons Improves the Sensitivity of Transcriptome-Wide Profiling.

PubMed

Zajaczkowski, Esmi L; Zhao, Qiong-Yi; Zhang, Zong Hong; Li, Xiang; Wei, Wei; Marshall, Paul R; Leighton, Laura J; Nainar, Sarah; Feng, Chao; Spitale, Robert C; Bredy, Timothy W

2018-06-15

Transcriptome-wide expression profiling of neurons has provided important insights into the underlying molecular mechanisms and gene expression patterns that transpire during learning and memory formation. However, there is a paucity of tools for profiling stimulus-induced RNA within specific neuronal cell populations. A bioorthogonal method to chemically label nascent (i.e., newly transcribed) RNA in a cell-type-specific and temporally controlled manner, which is also amenable to bioconjugation via click chemistry, was recently developed and optimized within conventional immortalized cell lines. However, its value within a more fragile and complicated cellular system such as neurons, as well as for transcriptome-wide expression profiling, has yet to be demonstrated. Here, we report the visualization and sequencing of activity-dependent nascent RNA derived from neurons using this labeling method. This work has important implications for improving transcriptome-wide expression profiling and visualization of nascent RNA in neurons, which has the potential to provide valuable insights into the mechanisms underlying neural plasticity, learning, and memory.

7 CFR 201.31a - Labeling treated seed.

Code of Federal Regulations, 2011 CFR

2011-01-01

... been treated shall be labeled in type no smaller than 8 point to indicate that the seed has been... labeling all types of mercurials. Examples of commonly accepted abbreviated chemical names are: BHC (1, 2... the size of the type used for information required to be on the label under paragraph (a) and shall...

Chemical biology-based approaches on fluorescent labeling of proteins in live cells.

PubMed

Jung, Deokho; Min, Kyoungmi; Jung, Juyeon; Jang, Wonhee; Kwon, Youngeun

2013-05-01

Recently, significant advances have been made in live cell imaging owing to the rapid development of selective labeling of proteins in vivo. Green fluorescent protein (GFP) was the first example of fluorescent reporters genetically introduced to protein of interest (POI). While GFP and various types of engineered fluorescent proteins (FPs) have been actively used for live cell imaging for many years, the size and the limited windows of fluorescent spectra of GFP and its variants set limits on possible applications. In order to complement FP-based labeling methods, alternative approaches that allow incorporation of synthetic fluorescent probes to target POIs were developed. Synthetic fluorescent probes are smaller than fluorescent proteins, often have improved photochemical properties, and offer a larger variety of colors. These synthetic probes can be introduced to POIs selectively by numerous approaches that can be largely categorized into chemical recognition-based labeling, which utilizes metal-chelating peptide tags and fluorophore-carrying metal complexes, and biological recognition-based labeling, such as (1) specific non-covalent binding between an enzyme tag and its fluorophore-carrying substrate, (2) self-modification of protein tags using substrate variants conjugated to fluorophores, (3) enzymatic reaction to generate a covalent binding between a small molecule substrate and a peptide tag, and (4) split-intein-based C-terminal labeling of target proteins. The chemical recognition-based labeling reaction often suffers from compromised selectivity of metal-ligand interaction in the cytosolic environment, consequently producing high background signals. Use of protein-substrate interactions or enzyme-mediated reactions generally shows improved specificity but each method has its limitations. Some examples are the presence of large linker protein, restriction on the choice of introducible probes due to the substrate specificity of enzymes, and competitive reaction mediated by an endogenous analogue of the introduced protein tag. These limitations have been addressed, in part, by the split-intein-based labeling approach, which introduces fluorescent probes with a minimal size (~4 amino acids) peptide tag. In this review, the advantages and the limitations of each labeling method are discussed.

Efficient convolutional sparse coding

DOEpatents

Wohlberg, Brendt

2017-06-20

Computationally efficient algorithms may be applied for fast dictionary learning solving the convolutional sparse coding problem in the Fourier domain. More specifically, efficient convolutional sparse coding may be derived within an alternating direction method of multipliers (ADMM) framework that utilizes fast Fourier transforms (FFT) to solve the main linear system in the frequency domain. Such algorithms may enable a significant reduction in computational cost over conventional approaches by implementing a linear solver for the most critical and computationally expensive component of the conventional iterative algorithm. The theoretical computational cost of the algorithm may be reduced from O(M.sup.3N) to O(MN log N), where N is the dimensionality of the data and M is the number of elements in the dictionary. This significant improvement in efficiency may greatly increase the range of problems that can practically be addressed via convolutional sparse representations.

Ultrastructural localization of hair keratins, high sulfur keratin-associated proteins and sulfhydryl oxidase in the human hair.

PubMed

Alibardi, Lorenzo

2017-03-01

Hardening of the human hair shaft during cornification results from the bonding of keratins and keratin-associated proteins. In situ hybridization and light immunocytochemical studies have shown the general distribution of different keratins and some associated proteins but not determined their ultrastructural localization. I report here the localization of hair keratins, two high-sulfur keratin-associated proteins and sulfhydryl oxidase has been studied under the transmission electron microscope in the cornification zone of the human hair. The ultrastructural study on keratin distribution in general confirms previous light microscopic studies. Sulfur-rich KAP1 is mainly cortical but the labeling disappears in fully cornified cortical cells while a diffuse labeling is also present in differentiating cuticle cells. Sulfur-rich K26 immunolocalization is only detected in the exocuticle and endocuticle. Sparse labeling for sulfhydryl oxidase occurs in differentiating cortical cells but is weak and uneven in cuticle cells and absent in medulla and inner root sheath. Labeling disappears in the upper fully cornified cortex and cuticle. The observations indicate that sulfhydryl oxidase and keratin associated proteins are initially produced in the cytoplasm among keratin bundles accumulating in cortical and cuticle cells but these proteins undergo changes during the following cornification that alter the epitopes tagged by the antibodies.

A comparative study of dietary curcumin, nanocurcumin, and other classical amyloid-binding dyes for labeling and imaging of amyloid plaques in brain tissue of 5×-familial Alzheimer's disease mice.

PubMed

Maiti, Panchanan; Hall, Tia C; Paladugu, Leela; Kolli, Nivya; Learman, Cameron; Rossignol, Julien; Dunbar, Gary L

2016-11-01

Deposition of amyloid beta protein (Aβ) is a key component in the pathogenesis of Alzheimer's disease (AD). As an anti-amyloid natural polyphenol, curcumin (Cur) has been used as a therapy for AD. Its fluorescent activity, preferential binding to Aβ, as well as structural similarities with other traditional amyloid-binding dyes, make it a promising candidate for labeling and imaging of Aβ plaques in vivo. The present study was designed to test whether dietary Cur and nanocurcumin (NC) provide more sensitivity for labeling and imaging of Aβ plaques in brain tissues from the 5×-familial AD (5×FAD) mice than the classical Aβ-binding dyes, such as Congo red and Thioflavin-S. These comparisons were made in postmortem brain tissues from the 5×FAD mice. We observed that Cur and NC labeled Aβ plaques to the same degree as Aβ-specific antibody and to a greater extent than those of the classical amyloid-binding dyes. Cur and NC also labeled Aβ plaques in 5×FAD brain tissues when injected intraperitoneally. Nanomolar concentrations of Cur or NC are sufficient for labeling and imaging of Aβ plaques in 5×FAD brain tissue. Cur and NC also labeled different types of Aβ plaques, including core, neuritic, diffuse, and burned-out, to a greater degree than other amyloid-binding dyes. Therefore, Cur and or NC can be used as an alternative to Aβ-specific antibody for labeling and imaging of Aβ plaques ex vivo and in vivo. It can provide an easy and inexpensive means of detecting Aβ-plaque load in postmortem brain tissue of animal models of AD after anti-amyloid therapy.

Joint learning of ultrasonic backscattering statistical physics and signal confidence primal for characterizing atherosclerotic plaques using intravascular ultrasound.

PubMed

Sheet, Debdoot; Karamalis, Athanasios; Eslami, Abouzar; Noël, Peter; Chatterjee, Jyotirmoy; Ray, Ajoy K; Laine, Andrew F; Carlier, Stephane G; Navab, Nassir; Katouzian, Amin

2014-01-01

Intravascular Ultrasound (IVUS) is a predominant imaging modality in interventional cardiology. It provides real-time cross-sectional images of arteries and assists clinicians to infer about atherosclerotic plaques composition. These plaques are heterogeneous in nature and constitute fibrous tissue, lipid deposits and calcifications. Each of these tissues backscatter ultrasonic pulses and are associated with a characteristic intensity in B-mode IVUS image. However, clinicians are challenged when colocated heterogeneous tissue backscatter mixed signals appearing as non-unique intensity patterns in B-mode IVUS image. Tissue characterization algorithms have been developed to assist clinicians to identify such heterogeneous tissues and assess plaque vulnerability. In this paper, we propose a novel technique coined as Stochastic Driven Histology (SDH) that is able to provide information about co-located heterogeneous tissues. It employs learning of tissue specific ultrasonic backscattering statistical physics and signal confidence primal from labeled data for predicting heterogeneous tissue composition in plaques. We employ a random forest for the purpose of learning such a primal using sparsely labeled and noisy samples. In clinical deployment, the posterior prediction of different lesions constituting the plaque is estimated. Folded cross-validation experiments have been performed with 53 plaques indicating high concurrence with traditional tissue histology. On the wider horizon, this framework enables learning of tissue-energy interaction statistical physics and can be leveraged for promising clinical applications requiring tissue characterization beyond the application demonstrated in this paper. Copyright © 2013 Elsevier B.V. All rights reserved.

Fluorescence polarization immunoassays for rapid, accurate and sensitive determination of mycotoxins

USDA-ARS?s Scientific Manuscript database

Fluorescence polarization immunoassay (FPIA) is a type of homogeneous assay. For low molecular weight antigens, such as mycotoxins, it is based on the competition between an unlabeled antigen and its fluorescent-labeled derivative (tracer) for an antigen-specific antibody. The antigen content is det...

Multi-threaded Sparse Matrix-Matrix Multiplication for Many-Core and GPU Architectures.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deveci, Mehmet; Rajamanickam, Sivasankaran; Trott, Christian Robert

Sparse Matrix-Matrix multiplication is a key kernel that has applications in several domains such as scienti c computing and graph analysis. Several algorithms have been studied in the past for this foundational kernel. In this paper, we develop parallel algorithms for sparse matrix-matrix multiplication with a focus on performance portability across different high performance computing architectures. The performance of these algorithms depend on the data structures used in them. We compare different types of accumulators in these algorithms and demonstrate the performance difference between these data structures. Furthermore, we develop a meta-algorithm, kkSpGEMM, to choose the right algorithm and datamore » structure based on the characteristics of the problem. We show performance comparisons on three architectures and demonstrate the need for the community to develop two phase sparse matrix-matrix multiplication implementations for efficient reuse of the data structures involved.« less

A mixture model with a reference-based automatic selection of components for disease classification from protein and/or gene expression levels

PubMed Central

2011-01-01

Background Bioinformatics data analysis is often using linear mixture model representing samples as additive mixture of components. Properly constrained blind matrix factorization methods extract those components using mixture samples only. However, automatic selection of extracted components to be retained for classification analysis remains an open issue. Results The method proposed here is applied to well-studied protein and genomic datasets of ovarian, prostate and colon cancers to extract components for disease prediction. It achieves average sensitivities of: 96.2 (sd = 2.7%), 97.6% (sd = 2.8%) and 90.8% (sd = 5.5%) and average specificities of: 93.6% (sd = 4.1%), 99% (sd = 2.2%) and 79.4% (sd = 9.8%) in 100 independent two-fold cross-validations. Conclusions We propose an additive mixture model of a sample for feature extraction using, in principle, sparseness constrained factorization on a sample-by-sample basis. As opposed to that, existing methods factorize complete dataset simultaneously. The sample model is composed of a reference sample representing control and/or case (disease) groups and a test sample. Each sample is decomposed into two or more components that are selected automatically (without using label information) as control specific, case specific and not differentially expressed (neutral). The number of components is determined by cross-validation. Automatic assignment of features (m/z ratios or genes) to particular component is based on thresholds estimated from each sample directly. Due to the locality of decomposition, the strength of the expression of each feature across the samples can vary. Yet, they will still be allocated to the related disease and/or control specific component. Since label information is not used in the selection process, case and control specific components can be used for classification. That is not the case with standard factorization methods. Moreover, the component selected by proposed method as disease specific can be interpreted as a sub-mode and retained for further analysis to identify potential biomarkers. As opposed to standard matrix factorization methods this can be achieved on a sample (experiment)-by-sample basis. Postulating one or more components with indifferent features enables their removal from disease and control specific components on a sample-by-sample basis. This yields selected components with reduced complexity and generally, it increases prediction accuracy. PMID:22208882

Compressive sensing for sparse time-frequency representation of nonstationary signals in the presence of impulsive noise

NASA Astrophysics Data System (ADS)

Orović, Irena; Stanković, Srdjan; Amin, Moeness

2013-05-01

A modified robust two-dimensional compressive sensing algorithm for reconstruction of sparse time-frequency representation (TFR) is proposed. The ambiguity function domain is assumed to be the domain of observations. The two-dimensional Fourier bases are used to linearly relate the observations to the sparse TFR, in lieu of the Wigner distribution. We assume that a set of available samples in the ambiguity domain is heavily corrupted by an impulsive type of noise. Consequently, the problem of sparse TFR reconstruction cannot be tackled using standard compressive sensing optimization algorithms. We introduce a two-dimensional L-statistics based modification into the transform domain representation. It provides suitable initial conditions that will produce efficient convergence of the reconstruction algorithm. This approach applies sorting and weighting operations to discard an expected amount of samples corrupted by noise. The remaining samples serve as observations used in sparse reconstruction of the time-frequency signal representation. The efficiency of the proposed approach is demonstrated on numerical examples that comprise both cases of monocomponent and multicomponent signals.

Specific 13C labeling of leucine, valine and isoleucine methyl groups for unambiguous detection of long-range restraints in protein solid-state NMR studies

NASA Astrophysics Data System (ADS)

Fasshuber, Hannes Klaus; Demers, Jean-Philippe; Chevelkov, Veniamin; Giller, Karin; Becker, Stefan; Lange, Adam

2015-03-01

Here we present an isotopic labeling strategy to easily obtain unambiguous long-range distance restraints in protein solid-state NMR studies. The method is based on the inclusion of two biosynthetic precursors in the bacterial growth medium, α-ketoisovalerate and α-ketobutyrate, leading to the production of leucine, valine and isoleucine residues that are exclusively 13C labeled on methyl groups. The resulting spectral simplification facilitates the collection of distance restraints, the verification of carbon chemical shift assignments and the measurement of methyl group dynamics. This approach is demonstrated on the type-three secretion system needle of Shigella flexneri, where 49 methyl-methyl and methyl-nitrogen distance restraints including 10 unambiguous long-range distance restraints could be collected. By combining this labeling scheme with ultra-fast MAS and proton detection, the assignment of methyl proton chemical shifts was achieved.

Pheromone lures to monitor sparse populations of spruce budworm, Choristoneura fumiferana (Lepidoptera: Tortricidae)

Treesearch

David G. Grimble

1988-01-01

Four types of spruce budworm pheromone lures were field-tested in sparse spruce budworm populations in Maine. BioLures® with constant pheromone emission rates less than 1.0, ca. 1.0-1.5, and ca. 15.0 micrograms of pheromone per day were compared to polyvinyl chloride (PVC) lures with rapidly decreasing pheromone emission rates. Mean trap catch was roughly proportional...

NELasso: Group-Sparse Modeling for Characterizing Relations Among Named Entities in News Articles.

PubMed

Tariq, Amara; Karim, Asim; Foroosh, Hassan

2017-10-01

Named entities such as people, locations, and organizations play a vital role in characterizing online content. They often reflect information of interest and are frequently used in search queries. Although named entities can be detected reliably from textual content, extracting relations among them is more challenging, yet useful in various applications (e.g., news recommending systems). In this paper, we present a novel model and system for learning semantic relations among named entities from collections of news articles. We model each named entity occurrence with sparse structured logistic regression, and consider the words (predictors) to be grouped based on background semantics. This sparse group LASSO approach forces the weights of word groups that do not influence the prediction towards zero. The resulting sparse structure is utilized for defining the type and strength of relations. Our unsupervised system yields a named entities' network where each relation is typed, quantified, and characterized in context. These relations are the key to understanding news material over time and customizing newsfeeds for readers. Extensive evaluation of our system on articles from TIME magazine and BBC News shows that the learned relations correlate with static semantic relatedness measures like WLM, and capture the evolving relationships among named entities over time.

Deep neural network-based domain adaptation for classification of remote sensing images

NASA Astrophysics Data System (ADS)

Ma, Li; Song, Jiazhen

2017-10-01

We investigate the effectiveness of deep neural network for cross-domain classification of remote sensing images in this paper. In the network, class centroid alignment is utilized as a domain adaptation strategy, making the network able to transfer knowledge from the source domain to target domain on a per-class basis. Since predicted labels of target data should be used to estimate the centroid of each class, we use overall centroid alignment as a coarse domain adaptation method to improve the estimation accuracy. In addition, rectified linear unit is used as the activation function to produce sparse features, which may improve the separation capability. The proposed network can provide both aligned features and an adaptive classifier, as well as obtain label-free classification of target domain data. The experimental results using Hyperion, NCALM, and WorldView-2 remote sensing images demonstrated the effectiveness of the proposed approach.

JiTTree: A Just-in-Time Compiled Sparse GPU Volume Data Structure.

PubMed

Labschütz, Matthias; Bruckner, Stefan; Gröller, M Eduard; Hadwiger, Markus; Rautek, Peter

2016-01-01

Sparse volume data structures enable the efficient representation of large but sparse volumes in GPU memory for computation and visualization. However, the choice of a specific data structure for a given data set depends on several factors, such as the memory budget, the sparsity of the data, and data access patterns. In general, there is no single optimal sparse data structure, but a set of several candidates with individual strengths and drawbacks. One solution to this problem are hybrid data structures which locally adapt themselves to the sparsity. However, they typically suffer from increased traversal overhead which limits their utility in many applications. This paper presents JiTTree, a novel sparse hybrid volume data structure that uses just-in-time compilation to overcome these problems. By combining multiple sparse data structures and reducing traversal overhead we leverage their individual advantages. We demonstrate that hybrid data structures adapt well to a large range of data sets. They are especially superior to other sparse data structures for data sets that locally vary in sparsity. Possible optimization criteria are memory, performance and a combination thereof. Through just-in-time (JIT) compilation, JiTTree reduces the traversal overhead of the resulting optimal data structure. As a result, our hybrid volume data structure enables efficient computations on the GPU, while being superior in terms of memory usage when compared to non-hybrid data structures.

Immunofluorescence reveals unusual patterns of labelling for connexin43 localized to calbindin-D28K-positive interstitial cells in the pineal gland.

PubMed

Tsao, D D; Wang, S G; Lynn, B D; Nagy, J I

2017-06-01

Gap junctions between cells in the pineal gland have been described ultrastructurally, but their connexin constituents have not been fully characterized. We used immunofluorescence in combination with markers of pineal cells to document the cellular localization of connexin43 (Cx43). Immunofluorescence labelling of Cx43 with several different antibodies was widely distributed throughout the pineal, whereas another connexin examined, connexin26, was not found in pineal but only in surrounding leptomeninges. Labelling apparently associated with plasma membranes was visualized either as fine Cx43-puncta (1-2 μm) or as unusually large pools of Cx43 ranging up to 4-7 μm in diameter or length. These puncta and pools were highly concentrated in perivascular spaces, where they were associated with numerous cells devoid of labelling for markers of pinealocytes (e.g. tryptophan hydroxylase and serotonin), and where they were minimally associated with blood vessels and lacked association with resident macrophages. Astrocytes labelled for glial fibrillary acidic protein were largely restricted to the anterior pole of the pineal gland, where they displayed only fine and sparse Cx43-puncta along their processes. Labelling for Cx43 was localized largely though not exclusively to the somata and long processes of a subpopulation of perivascular interstitial cells that were immunopositive for calbindin-D28K. These cells were often located among dense bundles or termination areas of sympathetic fibres labelled for tyrosine hydroxylase or serotonin. The results indicate that interstitial cells form abundant gap junctions composed of Cx43, and suggest that gap junction-mediated intracellular communication by these cells supports the activities of pinealocytes. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Automatic recognition of holistic functional brain networks using iteratively optimized convolutional neural networks (IO-CNN) with weak label initialization.

PubMed

Zhao, Yu; Ge, Fangfei; Liu, Tianming

2018-07-01

fMRI data decomposition techniques have advanced significantly from shallow models such as Independent Component Analysis (ICA) and Sparse Coding and Dictionary Learning (SCDL) to deep learning models such Deep Belief Networks (DBN) and Convolutional Autoencoder (DCAE). However, interpretations of those decomposed networks are still open questions due to the lack of functional brain atlases, no correspondence across decomposed or reconstructed networks across different subjects, and significant individual variabilities. Recent studies showed that deep learning, especially deep convolutional neural networks (CNN), has extraordinary ability of accommodating spatial object patterns, e.g., our recent works using 3D CNN for fMRI-derived network classifications achieved high accuracy with a remarkable tolerance for mistakenly labelled training brain networks. However, the training data preparation is one of the biggest obstacles in these supervised deep learning models for functional brain network map recognitions, since manual labelling requires tedious and time-consuming labours which will sometimes even introduce label mistakes. Especially for mapping functional networks in large scale datasets such as hundreds of thousands of brain networks used in this paper, the manual labelling method will become almost infeasible. In response, in this work, we tackled both the network recognition and training data labelling tasks by proposing a new iteratively optimized deep learning CNN (IO-CNN) framework with an automatic weak label initialization, which enables the functional brain networks recognition task to a fully automatic large-scale classification procedure. Our extensive experiments based on ABIDE-II 1099 brains' fMRI data showed the great promise of our IO-CNN framework. Copyright © 2018 Elsevier B.V. All rights reserved.

Sparse Coding for N-Gram Feature Extraction and Training for File Fragment Classification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Felix; Quach, Tu-Thach; Wheeler, Jason

File fragment classification is an important step in the task of file carving in digital forensics. In file carving, files must be reconstructed based on their content as a result of their fragmented storage on disk or in memory. Existing methods for classification of file fragments typically use hand-engineered features such as byte histograms or entropy measures. In this paper, we propose an approach using sparse coding that enables automated feature extraction. Sparse coding, or sparse dictionary learning, is an unsupervised learning algorithm, and is capable of extracting features based simply on how well those features can be used tomore » reconstruct the original data. With respect to file fragments, we learn sparse dictionaries for n-grams, continuous sequences of bytes, of different sizes. These dictionaries may then be used to estimate n-gram frequencies for a given file fragment, but for significantly larger n-gram sizes than are typically found in existing methods which suffer from combinatorial explosion. To demonstrate the capability of our sparse coding approach, we used the resulting features to train standard classifiers such as support vector machines (SVMs) over multiple file types. Experimentally, we achieved significantly better classification results with respect to existing methods, especially when the features were used in supplement to existing hand-engineered features.« less

Sparse Coding for N-Gram Feature Extraction and Training for File Fragment Classification

DOE PAGES

Wang, Felix; Quach, Tu-Thach; Wheeler, Jason; ...

2018-04-05

File fragment classification is an important step in the task of file carving in digital forensics. In file carving, files must be reconstructed based on their content as a result of their fragmented storage on disk or in memory. Existing methods for classification of file fragments typically use hand-engineered features such as byte histograms or entropy measures. In this paper, we propose an approach using sparse coding that enables automated feature extraction. Sparse coding, or sparse dictionary learning, is an unsupervised learning algorithm, and is capable of extracting features based simply on how well those features can be used tomore » reconstruct the original data. With respect to file fragments, we learn sparse dictionaries for n-grams, continuous sequences of bytes, of different sizes. These dictionaries may then be used to estimate n-gram frequencies for a given file fragment, but for significantly larger n-gram sizes than are typically found in existing methods which suffer from combinatorial explosion. To demonstrate the capability of our sparse coding approach, we used the resulting features to train standard classifiers such as support vector machines (SVMs) over multiple file types. Experimentally, we achieved significantly better classification results with respect to existing methods, especially when the features were used in supplement to existing hand-engineered features.« less

Pumping Iron and Silica Bodybuilding

NASA Astrophysics Data System (ADS)

Mcnair, H.; Brzezinski, M. A.; Krause, J. W.; Parker, C.; Brown, M.; Coale, T.; Bruland, K. W.

2016-02-01

The availability of dissolved iron influences the stoichiometry of nutrient uptake by diatoms. Under nutrient replete conditions diatoms consume silicic acid and nitrate in a 1:1 ratio, this ratio increases under iron stress. Using the tracers 32Si and PDMPO, the total community and group-specific silica production rates were measured along a gradient of dissolved iron in an upwelling plume off the California coast. At each station, a control (ambient silicic acid) and +20 µM silicic acid treatment were conducted with each tracer to determine whether silicic acid limitation controlled the rate of silica production. Dissolved iron was 1.3 nmol kg-1 nearshore and decreased to 0.15 nmol kg-1 offshore. Silicic acid decreased more rapidly than nitrate, it was nearly 9 µM higher in the nearshore and 7 µM lower than nitrate in the middle of the transect where the iron concentration had decreased. The rate of diatom silica production decreased in tandem with silicic acid concentration, and silica production limitation by low silicic acid was most pronounced when iron concentrations were >0.4 nmol kg-1. The composition of the diatom assemblage shifted from Chaetoceros spp. dominated nearshore to a more sparse pennate-dominated assemblage offshore. Changes in taxa-specific silica production rates will be reported based on examination of PDMPO labeled cells using confocal microscopy.

27 CFR 7.52 - Mandatory statements.

Code of Federal Regulations, 2010 CFR

2010-04-01

... OF THE TREASURY LIQUORS LABELING AND ADVERTISING OF MALT BEVERAGES Advertising of Malt Beverages § 7... broadcast. Street number and name may be omitted in the address. (b) Class. The advertisement shall contain... where only one type of malt beverage is marketed under the specific brand name advertised. (2) On...

21 CFR 870.5100 - Percutaneous Transluminal Coronary Angioplasty (PTCA) Catheter.

Code of Federal Regulations, 2013 CFR

2013-04-01

... Catheter—(1) Identification. A PTCA catheter is a device that operates on the principle of hydraulic... and length at a specific pressure as labeled, with well characterized rates of inflation and deflation and a defined burst pressure. The device generally features a type of radiographic marker to...

21 CFR 870.5100 - Percutaneous Transluminal Coronary Angioplasty (PTCA) Catheter.

Code of Federal Regulations, 2014 CFR

2014-04-01

... Catheter—(1) Identification. A PTCA catheter is a device that operates on the principle of hydraulic... and length at a specific pressure as labeled, with well characterized rates of inflation and deflation and a defined burst pressure. The device generally features a type of radiographic marker to...

21 CFR 870.5100 - Percutaneous Transluminal Coronary Angioplasty (PTCA) Catheter.

Code of Federal Regulations, 2011 CFR

2011-04-01

... Catheter—(1) Identification. A PTCA catheter is a device that operates on the principle of hydraulic... and length at a specific pressure as labeled, with well characterized rates of inflation and deflation and a defined burst pressure. The device generally features a type of radiographic marker to...

21 CFR 870.5100 - Percutaneous Transluminal Coronary Angioplasty (PTCA) Catheter.

Code of Federal Regulations, 2012 CFR

2012-04-01

... Catheter—(1) Identification. A PTCA catheter is a device that operates on the principle of hydraulic... and length at a specific pressure as labeled, with well characterized rates of inflation and deflation and a defined burst pressure. The device generally features a type of radiographic marker to...

Accuracy of a prey-specific DNA assay and a generic prey-immunomarking assay for detecting predation

USDA-ARS?s Scientific Manuscript database

1. Predator gut examinations are useful for detecting arthropod predation events. Here, the accuracy and reproducibility of two different types of gut assays are tested on various predator species that consumed an immature lacewing, Chrysoperla carnea (Stephens), that was externally labelled with ra...

Pyrylium-based dye and charge tagging in proteomics.

PubMed

Bayer, Malte; König, Simone

2016-11-01

The pyrylium group is a selective reagent for ε-amino groups in proteins. In particular, for fluorescence labeling, a number of advantages over traditional N-hydroxysuccinimidyl ester chemistry were recognized such as the rapid prestaining procedure. Here, we have investigated the labeling reaction for the fluorogenic pyrylium dye Py-1 using liquid chromatography coupled to MS with the aim of determining its specificity and possible side products. Peptides containing no, one, and two lysine residue and a choice of no or one cysteine residue were labeled with Py-1 at yields > 30%. Gas phase fragmentation proved both labeling of lysine residues as well as that of the N-terminus also in peptides that contained a lysine residue. Evidence for cysteine labeling was not found, but several other products were detected such as the results of rearrangements with adjacent acidic amino acids. Apart from the use as a fluorogenic label, Py-1 recommends itself for N-terminal charge tagging as alternative to the commonly used quaternary ammonium salts. Predominantly a- and b-type ion series were observed for N-terminally labeled peptides. Further applications include chromophore tagging since the labeled product is not only fluorescent but also colored red. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

7 CFR 3052.520 - Major program determination.

Code of Federal Regulations, 2011 CFR

2011-01-01

... shall be labeled Type A programs. Type A programs are defined as Federal programs with Federal awards... Federal awards expended exceed $10 billion. (2) Federal programs not labeled Type A under paragraph (b)(1) of this section shall be labeled Type B programs. (3) The inclusion of large loan and loan guarantees...

Joint annotation of chromatin state and chromatin conformation reveals relationships among domain types and identifies domains of cell-type-specific expression

PubMed Central

Libbrecht, Maxwell W.; Ay, Ferhat; Hoffman, Michael M.; Gilbert, David M.; Bilmes, Jeffrey A.; Noble, William Stafford

2015-01-01

The genomic neighborhood of a gene influences its activity, a behavior that is attributable in part to domain-scale regulation. Previous genomic studies have identified many types of regulatory domains. However, due to the difficulty of integrating genomics data sets, the relationships among these domain types are poorly understood. Semi-automated genome annotation (SAGA) algorithms facilitate human interpretation of heterogeneous collections of genomics data by simultaneously partitioning the human genome and assigning labels to the resulting genomic segments. However, existing SAGA methods cannot integrate inherently pairwise chromatin conformation data. We developed a new computational method, called graph-based regularization (GBR), for expressing a pairwise prior that encourages certain pairs of genomic loci to receive the same label in a genome annotation. We used GBR to exploit chromatin conformation information during genome annotation by encouraging positions that are close in 3D to occupy the same type of domain. Using this approach, we produced a model of chromatin domains in eight human cell types, thereby revealing the relationships among known domain types. Through this model, we identified clusters of tightly regulated genes expressed in only a small number of cell types, which we term “specific expression domains.” We found that domain boundaries marked by promoters and CTCF motifs are consistent between cell types even when domain activity changes. Finally, we showed that GBR can be used to transfer information from well-studied cell types to less well-characterized cell types during genome annotation, making it possible to produce high-quality annotations of the hundreds of cell types with limited available data. PMID:25677182

Joint annotation of chromatin state and chromatin conformation reveals relationships among domain types and identifies domains of cell-type-specific expression.

PubMed

Libbrecht, Maxwell W; Ay, Ferhat; Hoffman, Michael M; Gilbert, David M; Bilmes, Jeffrey A; Noble, William Stafford

2015-04-01

The genomic neighborhood of a gene influences its activity, a behavior that is attributable in part to domain-scale regulation. Previous genomic studies have identified many types of regulatory domains. However, due to the difficulty of integrating genomics data sets, the relationships among these domain types are poorly understood. Semi-automated genome annotation (SAGA) algorithms facilitate human interpretation of heterogeneous collections of genomics data by simultaneously partitioning the human genome and assigning labels to the resulting genomic segments. However, existing SAGA methods cannot integrate inherently pairwise chromatin conformation data. We developed a new computational method, called graph-based regularization (GBR), for expressing a pairwise prior that encourages certain pairs of genomic loci to receive the same label in a genome annotation. We used GBR to exploit chromatin conformation information during genome annotation by encouraging positions that are close in 3D to occupy the same type of domain. Using this approach, we produced a model of chromatin domains in eight human cell types, thereby revealing the relationships among known domain types. Through this model, we identified clusters of tightly regulated genes expressed in only a small number of cell types, which we term "specific expression domains." We found that domain boundaries marked by promoters and CTCF motifs are consistent between cell types even when domain activity changes. Finally, we showed that GBR can be used to transfer information from well-studied cell types to less well-characterized cell types during genome annotation, making it possible to produce high-quality annotations of the hundreds of cell types with limited available data. © 2015 Libbrecht et al.; Published by Cold Spring Harbor Laboratory Press.

Distribution of ELOVL4 in the Developing and Adult Mouse Brain

PubMed Central

Sherry, David M.; Hopiavuori, Blake R.; Stiles, Megan A.; Rahman, Negar S.; Ozan, Kathryn G.; Deak, Ferenc; Agbaga, Martin-Paul; Anderson, Robert E.

2017-01-01

ELOngation of Very Long chain fatty acids (ELOVL)-4 is essential for the synthesis of very long chain-fatty acids (fatty acids with chain lengths ≥ 28 carbons). The functions of ELOVL4 and its very long-chain fatty acid products are poorly understood at present. However, mutations in ELOVL4 cause neurodevelopmental or neurodegenerative diseases that vary according to the mutation and inheritance pattern. Heterozygous inheritance of different ELOVL4 mutations causes Stargardt-like Macular Dystrophy or Spinocerebellar Ataxia type 34. Homozygous inheritance of ELOVL4 mutations causes more severe disease characterized by seizures, intellectual disability, ichthyosis, and premature death. To better understand ELOVL4 and very long chain fatty acid function in the brain, we examined ELOVL4 expression in the mouse brain between embryonic day 18 and postnatal day 60 by immunolabeling using ELOVL4 and other marker antibodies. ELOVL4 was widely expressed in a region- and cell type-specific manner, and was restricted to cell bodies, consistent with its known localization to endoplasmic reticulum. ELOVL4 labeling was most prominent in gray matter, although labeling also was present in some cells located in white matter. ELOVL4 was widely expressed in the developing brain by embryonic day 18 and was especially pronounced in regions underlying the lateral ventricles and other neurogenic regions. The basal ganglia in particular showed intense ELOVL4 labeling at this stage. In the postnatal brain, cerebral cortex, hippocampus, cerebellum, thalamus, hypothalamus, midbrain, pons, and medulla all showed prominent ELOVL4 labeling, although ELOVL4 distribution was not uniform across all cells or subnuclei within these regions. In contrast, the basal ganglia showed little ELOVL4 labeling in the postnatal brain. Double labeling studies showed that ELOVL4 was primarily expressed by neurons, although presumptive oligodendrocytes located in white matter tracts also showed labeling. Little or no ELOVL4 labeling was present in astrocytes or radial glial cells. These findings suggest that ELOVL4 and its very long chain fatty acid products are important in many parts of the brain and that they are particularly associated with neuronal function. Specific roles for ELOVL4 and its products in oligodendrocytes and myelin and in cellular proliferation, especially during development, are possible. PMID:28507511

Magnetoresistive biosensors for quantitative proteomics

NASA Astrophysics Data System (ADS)

Zhou, Xiahan; Huang, Chih-Cheng; Hall, Drew A.

2017-08-01

Quantitative proteomics, as a developing method for study of proteins and identification of diseases, reveals more comprehensive and accurate information of an organism than traditional genomics. A variety of platforms, such as mass spectrometry, optical sensors, electrochemical sensors, magnetic sensors, etc., have been developed for detecting proteins quantitatively. The sandwich immunoassay is widely used as a labeled detection method due to its high specificity and flexibility allowing multiple different types of labels. While optical sensors use enzyme and fluorophore labels to detect proteins with high sensitivity, they often suffer from high background signal and challenges in miniaturization. Magnetic biosensors, including nuclear magnetic resonance sensors, oscillator-based sensors, Hall-effect sensors, and magnetoresistive sensors, use the specific binding events between magnetic nanoparticles (MNPs) and target proteins to measure the analyte concentration. Compared with other biosensing techniques, magnetic sensors take advantage of the intrinsic lack of magnetic signatures in biological samples to achieve high sensitivity and high specificity, and are compatible with semiconductor-based fabrication process to have low-cost and small-size for point-of-care (POC) applications. Although still in the development stage, magnetic biosensing is a promising technique for in-home testing and portable disease monitoring.

Embedded sparse representation of fMRI data via group-wise dictionary optimization

NASA Astrophysics Data System (ADS)

Zhu, Dajiang; Lin, Binbin; Faskowitz, Joshua; Ye, Jieping; Thompson, Paul M.

2016-03-01

Sparse learning enables dimension reduction and efficient modeling of high dimensional signals and images, but it may need to be tailored to best suit specific applications and datasets. Here we used sparse learning to efficiently represent functional magnetic resonance imaging (fMRI) data from the human brain. We propose a novel embedded sparse representation (ESR), to identify the most consistent dictionary atoms across different brain datasets via an iterative group-wise dictionary optimization procedure. In this framework, we introduced additional criteria to make the learned dictionary atoms more consistent across different subjects. We successfully identified four common dictionary atoms that follow the external task stimuli with very high accuracy. After projecting the corresponding coefficient vectors back into the 3-D brain volume space, the spatial patterns are also consistent with traditional fMRI analysis results. Our framework reveals common features of brain activation in a population, as a new, efficient fMRI analysis method.

Cell Assembly Dynamics of Sparsely-Connected Inhibitory Networks: A Simple Model for the Collective Activity of Striatal Projection Neurons.

PubMed

Angulo-Garcia, David; Berke, Joshua D; Torcini, Alessandro

2016-02-01

Striatal projection neurons form a sparsely-connected inhibitory network, and this arrangement may be essential for the appropriate temporal organization of behavior. Here we show that a simplified, sparse inhibitory network of Leaky-Integrate-and-Fire neurons can reproduce some key features of striatal population activity, as observed in brain slices. In particular we develop a new metric to determine the conditions under which sparse inhibitory networks form anti-correlated cell assemblies with time-varying activity of individual cells. We find that under these conditions the network displays an input-specific sequence of cell assembly switching, that effectively discriminates similar inputs. Our results support the proposal that GABAergic connections between striatal projection neurons allow stimulus-selective, temporally-extended sequential activation of cell assemblies. Furthermore, we help to show how altered intrastriatal GABAergic signaling may produce aberrant network-level information processing in disorders such as Parkinson's and Huntington's diseases.

Audit of manufactured products: use of allergen advisory labels and identification of labeling ambiguities.

PubMed

Pieretti, Mariah M; Chung, Danna; Pacenza, Robert; Slotkin, Todd; Sicherer, Scott H

2009-08-01

The Food Allergy Labeling and Consumer Protection Act became effective January 1, 2006, and mandates disclosure of the 8 major allergens in plain English and as a source of ingredients in the ingredient statement. It does not regulate advisory labels. We sought to determine the frequency and language used in voluntary advisory labels among commercially available products and to identify labeling ambiguities affecting consumers with allergy. Trained surveyors performed a supermarket survey of 20,241 unique manufactured food products (from an original assessment of 49,604 products) for use of advisory labels. A second detailed survey of 744 unique products evaluated additional labeling practices. Overall, 17% of 20,241 products surveyed contain advisory labels. Chocolate candy, cookies, and baking mixes were the 3 categories of 24 with the greatest frequency (> or = 40%). Categorically, advisory warnings included "may contain" (38%), "shared equipment" (33%), and "within plant" (29%). The subsurvey disclosed 25 different types of advisory terminology. Nonspecific terms, such as "natural flavors" and "spices," were found on 65% of products and were not linked to a specific ingredient for 83% of them. Additional ambiguities included unclear sources of soy (lecithin vs protein), nondisclosure of sources of gelatin and lecithin, and simultaneous disclosure of "contains" and "may contain" for the same allergen, among others. Numerous products have advisory labeling and ambiguities that present challenges to consumers with food allergy. Additional allergen labeling regulation could improve safety and quality of life for individuals with food allergy.

Limited-memory trust-region methods for sparse relaxation

NASA Astrophysics Data System (ADS)

Adhikari, Lasith; DeGuchy, Omar; Erway, Jennifer B.; Lockhart, Shelby; Marcia, Roummel F.

2017-08-01

In this paper, we solve the l2-l1 sparse recovery problem by transforming the objective function of this problem into an unconstrained differentiable function and applying a limited-memory trust-region method. Unlike gradient projection-type methods, which uses only the current gradient, our approach uses gradients from previous iterations to obtain a more accurate Hessian approximation. Numerical experiments show that our proposed approach eliminates spurious solutions more effectively while improving computational time.

The acquisition of gender labels in infancy: implications for gender-typed play.

PubMed

Zosuls, Kristina M; Ruble, Diane N; Tamis-Lemonda, Catherine S; Shrout, Patrick E; Bornstein, Marc H; Greulich, Faith K

2009-05-01

Two aspects of children's early gender development-the spontaneous production of gender labels and gender-typed play-were examined longitudinally in a sample of 82 children. Survival analysis, a statistical technique well suited to questions involving developmental transitions, was used to investigate the timing of the onset of children's gender labeling as based on mothers' biweekly telephone interviews regarding their children's language from 9 through 21 months. Videotapes of children's play both alone and with mother during home visits at 17 and 21 months were independently analyzed for play with gender-stereotyped and gender-neutral toys. Finally, the relation between gender labeling and gender-typed play was examined. Children transitioned to using gender labels at approximately 19 months, on average. Although girls and boys showed similar patterns in the development of gender labeling, girls began labeling significantly earlier than boys. Modest sex differences in play were present at 17 months and increased at 21 months. Gender labeling predicted increases in gender-typed play, suggesting that knowledge of gender categories might influence gender typing before the age of 2. Copyright 2009 APA, all rights reserved

The acquisition of gender labels in infancy: Implications for sex-typed play

PubMed Central

Zosuls, Kristina M.; Ruble, Diane N.; Tamis-LeMonda, Catherine S.; Shrout, Patrick E.; Bornstein, Marc H.; Greulich, Faith K.

2009-01-01

Two aspects of children’s early gender development - the spontaneous production of gender labels and sex-typed play - were examined longitudinally in a sample of 82 children. Survival analysis, a statistical technique well suited to questions involving developmental transitions, was used to investigate the timing of the onset of children’s gender labeling as based on mothers’ biweekly reports on their children’s language from 9 through 21 months. Videotapes of children’s play both alone and with mother at 17 and 21 months were independently analyzed for play with gender stereotyped and neutral toys. Finally, the relation between gender labeling and sex-typed play was examined. Children transitioned to using gender labels at approximately 19 months on average. Although girls and boys showed similar patterns in the development of gender labeling, girls began labeling significantly earlier than boys. Modest sex differences in play were present at 17 months and increased at 21 months. Gender labeling predicted increases in sex-typed play, suggesting that knowledge of gender categories might influence sex-typing before the age of 2. PMID:19413425

Weighted compactness function based label propagation algorithm for community detection

NASA Astrophysics Data System (ADS)

Zhang, Weitong; Zhang, Rui; Shang, Ronghua; Jiao, Licheng

2018-02-01

Community detection in complex networks, is to detect the community structure with the internal structure relatively compact and the external structure relatively sparse, according to the topological relationship among nodes in the network. In this paper, we propose a compactness function which combines the weight of nodes, and use it as the objective function to carry out the node label propagation. Firstly, according to the node degree, we find the sets of core nodes which have great influence on the network. The more the connections between the core nodes and the other nodes are, the larger the amount of the information these kernel nodes receive and transform. Then, according to the similarity of the nodes between the core nodes sets and the nodes degree, we assign weights to the nodes in the network. So the label of the nodes with great influence will be the priority in the label propagation process, which effectively improves the accuracy of the label propagation. The compactness function between nodes and communities in this paper is based on the nodes influence. It combines the connections between nodes and communities with the degree of the node belongs to its neighbor communities based on calculating the node weight. The function effectively uses the information of nodes and connections in the network. The experimental results show that the proposed algorithm can achieve good results in the artificial network and large-scale real networks compared with the 8 contrast algorithms.

Heterogeneity of transverse-axial tubule system in mouse atria: Remodeling in atrial-specific Na+-Ca2+ exchanger knockout mice.

PubMed

Yue, Xin; Zhang, Rui; Kim, Brian; Ma, Aiqun; Philipson, Kenneth D; Goldhaber, Joshua I

2017-07-01

Transverse-axial tubules (TATs) are commonly assumed to be sparse or absent in atrial myocytes from small animals. Atrial myocytes from rats, cats and rabbits lack TATs, which results in a characteristic "V"-shaped Ca release pattern in confocal line-scan recordings due to the delayed rise of Ca in the center of the cell. To examine TAT expression in isolated mouse atrial myocytes, we loaded them with the membrane dye Di-4-ANEPPS to label TATs. We found that >80% of atrial myocytes had identifiable TATs. Atria from male mice had a higher TAT density than female mice, and TAT density correlated with cell width. Using the fluorescent Ca indicator Fluo-4-AM and confocal imaging, we found that wild type (WT) mouse atrial myocytes generate near-synchronous Ca transients, in contrast to the "V"-shaped pattern typically reported in other small animals such as rat. In atrial-specific Na-Ca exchanger (NCX) knockout (KO) mice, which develop sinus node dysfunction and atrial hypertrophy with dilation, we found a substantial loss of atrial TATs in isolated atrial myocytes. There was a greater loss of transverse tubules compared to axial tubules, resulting in a dominance of axial tubules. Consistent with the overall loss of TATs, NCX KO atrial myocytes displayed a "V"-shaped Ca transient with slower and reduced central (CT) Ca release and uptake in comparison to subsarcolemmal (SS) Ca release. We compared chemically detubulated (DT) WT cells to KO, and found similar slowing of CT Ca release and uptake. However, SS Ca transients in the WT DT cells had faster uptake kinetics than KO cells, consistent with the presence of NCX and normal sarcolemmal Ca efflux in the WT DT cells. We conclude that the remodeling of NCX KO atrial myocytes is accompanied by a loss of TATs leading to abnormal Ca release and uptake that could impact atrial contractility and rhythm. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatiotemporal definition of neurite outgrowth, refinement and retraction in the developing mouse cochlea.

PubMed

Huang, Lin-Chien; Thorne, Peter R; Housley, Gary D; Montgomery, Johanna M

2007-08-01

The adult mammalian cochlea receives dual afferent innervation: the inner sensory hair cells are innervated exclusively by type I spiral ganglion neurons (SGN), whereas the sensory outer hair cells are innervated by type II SGN. We have characterized the spatiotemporal reorganization of the dual afferent innervation pattern as it is established in the developing mouse cochlea. This reorganization occurs during the first postnatal week just before the onset of hearing. Our data reveal three distinct phases in the development of the afferent innervation of the organ of Corti: (1) neurite growth and extension of both classes of afferents to all hair cells (E18-P0); (2) neurite refinement, with formation of the outer spiral bundles innervating outer hair cells (P0-P3); (3) neurite retraction and synaptic pruning to eliminate type I SGN innervation of outer hair cells, while retaining their innervation of inner hair cells (P3-P6). The characterization of this developmental innervation pattern was made possible by the finding that tetramethylrhodamine-conjugated dextran (TMRD) specifically labeled type I SGN. Peripherin and choline-acetyltransferase immunofluorescence confirmed the type II and efferent innervation patterns, respectively, and verified the specificity of the type I SGN neurites labeled by TMRD. These findings define the precise spatiotemporal neurite reorganization of the two afferent nerve fiber populations in the cochlea, which is crucial for auditory neurotransmission. This reorganization also establishes the cochlea as a model system for studying CNS synapse development, plasticity and elimination.

Histochemical evidence for the differential surface labeling, uptake, and intracellular transport of a colloidal gold-labeled insulin complex by normal human blood cells.

PubMed

Ackerman, G A; Wolken, K W

1981-10-01

A colloidal gold-labeled insulin-bovine serum albumin (GIA) reagent has been developed for the ultrastructural visualization of insulin binding sites on the cell surface and for tracing the pathway of intracellular insulin translocation. When applied to normal human blood cells, it was demonstrated by both visual inspection and quantitative analysis that the extent of surface labeling, as well as the rate and degree of internalization of the insulin complex, was directly related to cell type. Further, the pathway of insulin (GIA) transport via round vesicles and by tubulo-vesicles and saccules and its subsequent fate in the hemic cells was also related to cell variety. Monocytes followed by neutrophils bound the greatest amount of labeled insulin. The majority of lymphocytes bound and internalized little GIA, however, between 5-10% of the lymphocytes were found to bind considerable quantities of GIA. Erythrocytes rarely bound the labeled insulin complex, while platelets were noted to sequester large quantities of the GIA within their extracellular canalicular system. GIA uptake by the various types of leukocytic cells appeared to occur primarily by micropinocytosis and by the direct opening of cytoplasmic tubulo-vesicles and saccules onto the cell surface in regions directly underlying surface-bound GIA. Control procedures, viz., competitive inhibition of GIA labeling using an excess of unlabeled insulin in the incubation medium, preincubation of the GIA reagent with an antibody directed toward porcine insulin, and the incorporation of 125I-insulin into the GIA reagent, indicated the specificity and selectivity of the GIA histochemical procedure for the localization of insulin binding sites.

Neighborhood Inequalities in Retailers' Compliance With the Family Smoking Prevention and Tobacco Control Act of 2009, January 2014-July 2014.

PubMed

Lee, Joseph G L; Baker, Hannah M; Ranney, Leah M; Goldstein, Adam O

2015-10-08

Retailer noncompliance with limited US tobacco regulations on advertising and labeling was historically patterned by neighborhood in ways that promote health disparities. In 2010, the US Food and Drug Administration (FDA) began enforcing stronger tobacco retailer regulations under the Family Smoking Prevention and Tobacco Control Act of 2009. However, recent research has found no differences in compliance by neighborhood characteristics for FDA advertising and labeling inspections. We sought to investigate the neighborhood characteristics associated with retailer noncompliance with specific FDA advertising and labeling inspections (ie, violations of bans on self-service displays, selling single cigarettes, false or mislabeled products, vending machines, flavored cigarettes, and free samples). We coded FDA advertising and labeling warning letters (n = 718) for type of violations and geocoded advertising and labeling inspections from January 1 through July 31, 2014 (N = 33,543). Using multilevel models, we examined cross-sectional associations between types of violations and neighborhood characteristics previously associated with disparities (ie, percentage black, Latino, under the poverty line, and younger than 18 years). Retailer advertising and labeling violations are patterned by who lives in the neighborhood; regulated tobacco products are more likely to be stored behind the counter as the percentage of black or Latino residents increases, and single cigarettes are more often available for purchase in neighborhoods as the percentage of black, poor, or young residents increases. Contrary to previous null findings, noncompliance with FDA advertising and labeling regulations is patterned by neighborhood characteristics, sometimes in opposite directions. Given the low likelihood of self-service violations in the same neighborhoods that have high likelihood of single cigarette sales, we suggest targeted approaches to FDA retailer inspections and education campaigns.

Neighborhood Inequalities in Retailers’ Compliance With the Family Smoking Prevention and Tobacco Control Act of 2009, January 2014–July 2014

PubMed Central

Baker, Hannah M.; Ranney, Leah M.; Goldstein, Adam O.

2015-01-01

Introduction Retailer noncompliance with limited US tobacco regulations on advertising and labeling was historically patterned by neighborhood in ways that promote health disparities. In 2010, the US Food and Drug Administration (FDA) began enforcing stronger tobacco retailer regulations under the Family Smoking Prevention and Tobacco Control Act of 2009. However, recent research has found no differences in compliance by neighborhood characteristics for FDA advertising and labeling inspections. We sought to investigate the neighborhood characteristics associated with retailer noncompliance with specific FDA advertising and labeling inspections (ie, violations of bans on self-service displays, selling single cigarettes, false or mislabeled products, vending machines, flavored cigarettes, and free samples). Methods We coded FDA advertising and labeling warning letters (n = 718) for type of violations and geocoded advertising and labeling inspections from January 1 through July 31, 2014 (N = 33,543). Using multilevel models, we examined cross-sectional associations between types of violations and neighborhood characteristics previously associated with disparities (ie, percentage black, Latino, under the poverty line, and younger than 18 years). Results Retailer advertising and labeling violations are patterned by who lives in the neighborhood; regulated tobacco products are more likely to be stored behind the counter as the percentage of black or Latino residents increases, and single cigarettes are more often available for purchase in neighborhoods as the percentage of black, poor, or young residents increases. Conclusion Contrary to previous null findings, noncompliance with FDA advertising and labeling regulations is patterned by neighborhood characteristics, sometimes in opposite directions. Given the low likelihood of self-service violations in the same neighborhoods that have high likelihood of single cigarette sales, we suggest targeted approaches to FDA retailer inspections and education campaigns. PMID:26447548

Efficient spares matrix multiplication scheme for the CYBER 203

NASA Technical Reports Server (NTRS)

Lambiotte, J. J., Jr.

1984-01-01

This work has been directed toward the development of an efficient algorithm for performing this computation on the CYBER-203. The desire to provide software which gives the user the choice between the often conflicting goals of minimizing central processing (CPU) time or storage requirements has led to a diagonal-based algorithm in which one of three types of storage is selected for each diagonal. For each storage type, an initialization sub-routine estimates the CPU and storage requirements based upon results from previously performed numerical experimentation. These requirements are adjusted by weights provided by the user which reflect the relative importance the user places on the resources. The three storage types employed were chosen to be efficient on the CYBER-203 for diagonals which are sparse, moderately sparse, or dense; however, for many densities, no diagonal type is most efficient with respect to both resource requirements. The user-supplied weights dictate the choice.

A recombinant fungal lectin for labeling truncated glycans on human cancer cells.

PubMed

Audfray, Aymeric; Beldjoudi, Mona; Breiman, Adrien; Hurbin, Amandine; Boos, Irene; Unverzagt, Carlo; Bouras, Mourad; Lantuejoul, Sylvie; Coll, Jean-Luc; Varrot, Annabelle; Le Pendu, Jacques; Busser, Benoit; Imberty, Anne

2015-01-01

Cell surface glycoconjugates present alterations of their structures in chronic diseases and distinct oligosaccharide epitopes have been associated with cancer. Among them, truncated glycans present terminal non-reducing β-N-acetylglucosamine (GlcNAc) residues that are rare on healthy tissues. Lectins from unconventional sources such as fungi or algi provide novel markers that bind specifically to such epitopes, but their availability may be challenging. A GlcNAc-binding lectin from the fruiting body of the fungus Psathyrella velutina (PVL) has been produced in good yield in bacterial culture. A strong specificity for terminal GlcNAc residues was evidenced by glycan array. Affinity values obtained by microcalorimetry and surface plasmon resonance demonstrated a micromolar affinity for GlcNAcβ1-3Gal epitopes and for biantennary N-glycans with GlcNAcβ1-2Man capped branches. Crystal structure of PVL complexed with GlcNAcβ1-3Gal established the structural basis of the specificity. Labeling of several types of cancer cells and use of inhibitors of glycan metabolism indicated that rPVL binds to terminal GlcNAc but also to sialic acid (Neu5Ac). Analysis of glycosyltransferase expression confirmed the higher amount of GlcNAc present on cancer cells. rPVL binding is specific to cancer tissue and weak or no labeling is observed for healthy ones, except for stomach glands that present unique αGlcNAc-presenting mucins. In lung, breast and colon carcinomas, a clear delineation could be observed between cancer regions and surrounding healthy tissues. PVL is therefore a useful tool for labeling agalacto-glycans in cancer or other diseases.

A Recombinant Fungal Lectin for Labeling Truncated Glycans on Human Cancer Cells

PubMed Central

Hurbin, Amandine; Boos, Irene; Unverzagt, Carlo; Bouras, Mourad; Lantuejoul, Sylvie; Coll, Jean-Luc; Varrot, Annabelle; Le Pendu, Jacques; Busser, Benoit; Imberty, Anne

2015-01-01

Cell surface glycoconjugates present alterations of their structures in chronic diseases and distinct oligosaccharide epitopes have been associated with cancer. Among them, truncated glycans present terminal non-reducing β-N-acetylglucosamine (GlcNAc) residues that are rare on healthy tissues. Lectins from unconventional sources such as fungi or algi provide novel markers that bind specifically to such epitopes, but their availability may be challenging. A GlcNAc-binding lectin from the fruiting body of the fungus Psathyrella velutina (PVL) has been produced in good yield in bacterial culture. A strong specificity for terminal GlcNAc residues was evidenced by glycan array. Affinity values obtained by microcalorimetry and surface plasmon resonance demonstrated a micromolar affinity for GlcNAcβ1-3Gal epitopes and for biantennary N-glycans with GlcNAcβ1-2Man capped branches. Crystal structure of PVL complexed with GlcNAcβ1-3Gal established the structural basis of the specificity. Labeling of several types of cancer cells and use of inhibitors of glycan metabolism indicated that rPVL binds to terminal GlcNAc but also to sialic acid (Neu5Ac). Analysis of glycosyltransferase expression confirmed the higher amount of GlcNAc present on cancer cells. rPVL binding is specific to cancer tissue and weak or no labeling is observed for healthy ones, except for stomach glands that present unique αGlcNAc-presenting mucins. In lung, breast and colon carcinomas, a clear delineation could be observed between cancer regions and surrounding healthy tissues. PVL is therefore a useful tool for labeling agalacto-glycans in cancer or other diseases. PMID:26042789

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks

PubMed Central

Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic. PMID:28245222

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks.

PubMed

Wu, Jibing; Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic.

Face Aging Effect Simulation Using Hidden Factor Analysis Joint Sparse Representation.

PubMed

Yang, Hongyu; Huang, Di; Wang, Yunhong; Wang, Heng; Tang, Yuanyan

2016-06-01

Face aging simulation has received rising investigations nowadays, whereas it still remains a challenge to generate convincing and natural age-progressed face images. In this paper, we present a novel approach to such an issue using hidden factor analysis joint sparse representation. In contrast to the majority of tasks in the literature that integrally handle the facial texture, the proposed aging approach separately models the person-specific facial properties that tend to be stable in a relatively long period and the age-specific clues that gradually change over time. It then transforms the age component to a target age group via sparse reconstruction, yielding aging effects, which is finally combined with the identity component to achieve the aged face. Experiments are carried out on three face aging databases, and the results achieved clearly demonstrate the effectiveness and robustness of the proposed method in rendering a face with aging effects. In addition, a series of evaluations prove its validity with respect to identity preservation and aging effect generation.

Objective sea level pressure analysis for sparse data areas

NASA Technical Reports Server (NTRS)

Druyan, L. M.

1972-01-01

A computer procedure was used to analyze the pressure distribution over the North Pacific Ocean for eleven synoptic times in February, 1967. Independent knowledge of the central pressures of lows is shown to reduce the analysis errors for very sparse data coverage. The application of planned remote sensing of sea-level wind speeds is shown to make a significant contribution to the quality of the analysis especially in the high gradient mid-latitudes and for sparse coverage of conventional observations (such as over Southern Hemisphere oceans). Uniform distribution of the available observations of sea-level pressure and wind velocity yields results far superior to those derived from a random distribution. A generalization of the results indicates that the average lower limit for analysis errors is between 2 and 2.5 mb based on the perfect specification of the magnitude of the sea-level pressure gradient from a known verification analysis. A less than perfect specification will derive from wind-pressure relationships applied to satellite observed wind speeds.

Nonisotopic detection of human papillomavirus DNA in clinical specimens using a consensus PCR and a generic probe mix in an enzyme-linked immunosorbent assay format.

PubMed

Kornegay, J R; Shepard, A P; Hankins, C; Franco, E; Lapointe, N; Richardson, H; Coutleé, F

2001-10-01

We assessed the value of a new digoxigenin (DIG)-labeled generic probe mix in a PCR-enzyme-linked immunosorbent assay format to screen for the presence of human papillomavirus (HPV) DNA amplified from clinical specimens. After screening with this new generic assay is performed, HPV DNA-positive samples can be directly genotyped using a reverse blotting method with product from the same PCR amplification. DNA from 287 genital specimens was amplified via PCR using biotin-labeled consensus primers directed to the L1 gene. HPV amplicons were captured on a streptavidin-coated microwell plate (MWP) and detected with a DIG-labeled HPV generic probe mix consisting of nested L1 fragments from types 11, 16, 18, and 51. Coamplification and detection of human DNA with biotinylated beta-globin primers served as a control for both sample adequacy and PCR amplification. All specimens were genotyped using a reverse line blot assay (13). Results for the generic assay using MWPs and a DIG-labeled HPV generic probe mix (DIG-MWP generic probe assay) were compared with results from a previous analysis using dot blots with a radiolabeled nested generic probe mix and type-specific probes for genotyping. The DIG-MWP generic probe assay resulted in high intralaboratory concordance in genotyping results (88% versus 73% agreement using traditional methods). There were 207 HPV-positive results using the DIG-MWP method and 196 positives using the radiolabeled generic probe technique, suggesting slightly improved sensitivity. Only one sample failed to test positive with the DIG-MWP generic probe assay in spite of a positive genotyping result. Concordance between the two laboratories was nearly 87%. Approximately 6% of samples that were positive or borderline when tested with the DIG-MWP generic probe assay were not detected with the HPV type-specific panel, perhaps representing very rare or novel HPV types. This new method is easier to perform than traditional generic probe techniques and uses more objective interpretation criteria, making it useful in studies of HPV natural history.

Inconsistencies in emergency instructions on common household product labels.

PubMed

Cantrell, F Lee; Nordt, Sean Patrick; Krauss, Jamey R

2013-10-01

Human exposures to non-pharmaceutical products often results in serious injury and death annually in the United States. Studies performed more than 25 years ago described inadequate first aid advice on the majority of household products. The current study evaluates contemporary non-pharmaceutical products with respect to location, uniformity and type of their first aid and emergency contact instructions. A random, convenience sample of commercial product label information was obtained from local retail stores over an 8 month period. Twelve common non-pharmaceutical product categories, with large numbers of annual human exposures, were identified from National Poison Data Systems data. A minimum of 10 unique products for each category utilized. The following information identified: product name and manufacturer, location on container, presence and type of route-specific treatment, medical assistance referral information. A total of 259 product labels were examined. First aid/contact information was located on container: rear 162 (63 %), side 28 (11 %), front 3 (1 %), bottom 2 (0.77 %), behind label 14 (5 %), missing entirely 50 (19 %). Fifty-five products (21 %) lacked any first aid instructions. Suggested contacts for accidental poisoning: none listed 75 (29 %), physician 144 (56 %), poison control centers 102 (39 %), manufacturer 44 (17 %), "Call 911" 10 (4 %). Suggested contacts for unintentional exposure and content of first aid instructions on household products were inconsistent, frequently incomplete and at times absent. Instruction locations similarly lacked uniformity. Household product labels need to provide concise, accurate first aid and emergency contact instructions in easy-to-understand language in a universal format on product labels.

Vignettes from the field of mathematical biology: the application of mathematics to biology and medicine.

PubMed

Murray, J D

2012-08-06

The application of mathematical models in biology and medicine has a long history. From the sparse number of papers in the first half of the twentieth century with a few scientists working in the field it has become vast with thousands of active researchers. We give a brief, and far from definitive history, of how some parts of the field have developed and how the type of research has changed. We describe in more detail just two examples of specific models which are directly related to real biological problems, namely animal coat patterns and the growth and image enhancement of glioblastoma brain tumours.

Larval habitats of anopheline mosquitoes in the Upper Orinoco, Venezuela.

PubMed

Rejmánková, E; Rubio-Palis, Y; Villegas, L

1999-12-01

Survey of larval habitats of anopheline mosquitoes was conducted in Ocamo in the State of Amazonas, southern Venezuela. The sampled habitats belonged to three different hydrological types: lagoons (26 habitats), forest pools including flooded forest (16 habitats), and forest streams (4 habitats). Out of 46 habitats surveyed, 31 contained anopheline larvae. Six species were found: Anopheles darlingi, Anopheles triannulatus, Anopheles oswaldoi, Anopheles peryassui, Anopheles punctimacula, and Anopheles mediopunctatus. Anopheles triannulatus was the most abundant species. Significantly higher numbers of anopheline larvae, in general, and of An. triannulatus specifically were found in lagoons with submersed macrophytes and sparse emergent graminoids than in forest pools with detritus.

Biochemical characterization of domain-specific glycoproteins of the rat hepatocyte plasma membrane.

PubMed

Bartles, J R; Braiterman, L T; Hubbard, A L

1985-10-15

Seven integral proteins (CE 9, HA 21, HA 116, HA 16, HA 4, HA 201, and HA 301) were isolated from rat hepatocyte plasma membranes by immunoaffinity chromatography on monoclonal antibody-Sepharose. Six of the proteins (all but HA 16) exhibit domain-specific localizations (either bile canalicular or sinusoidal/lateral) about the hepatocyte surface. We identified three of these protein antigens as leucine aminopeptidase (HA 201), dipeptidyl peptidase IV (HA 301), and the asialoglycoprotein receptor (HA 116). We also developed 125I-lectin blotting procedures that, when used in conjunction with chemical and glycosidase treatments, permitted a comparison of the types of oligosaccharides present on the seven proteins. All seven are sialoglycoproteins, based upon the effects of prior neuraminidase and periodate-aniline-cyanoborohydride treatments of blots on labeling by 125I-wheat germ agglutinin. 125I-labeled Ricinus communis agglutinin I and 125I-peanut agglutinin blotting of the desialylated proteins revealed few if any conventional O-linked oligosaccharides, suggesting that the sialyl residues represent termini of N-linked complex-type oligosaccharides. Depending upon the protein, we estimated the presence of 2-26 N-linked oligosaccharides/polypeptide chain from the Mr reductions accompanying chemical or enzymatic deglycosylation. Three of these mature plasma membrane proteins (HA 21, HA 116, and HA 4) have both high mannose-type and complex-type oligosaccharides on every copy of their polypeptide chains. The labeling of these three proteins by 125I-concanavalin A was sensitive to treatment with endoglycosidase H, and each exhibited a quantitative reduction in Mr after the treatment, as assessed independently by 125I-wheat germ agglutinin blotting. At this level of analysis, we were unable to discern differences in the types of oligosaccharides present on these seven glycoproteins that correlate with their patterns of expression within the plasma membrane domains of this polarized epithelial cell.

Spatio-temporal Event Classification using Time-series Kernel based Structured Sparsity

PubMed Central

Jeni, László A.; Lőrincz, András; Szabó, Zoltán; Cohn, Jeffrey F.; Kanade, Takeo

2016-01-01

In many behavioral domains, such as facial expression and gesture, sparse structure is prevalent. This sparsity would be well suited for event detection but for one problem. Features typically are confounded by alignment error in space and time. As a consequence, high-dimensional representations such as SIFT and Gabor features have been favored despite their much greater computational cost and potential loss of information. We propose a Kernel Structured Sparsity (KSS) method that can handle both the temporal alignment problem and the structured sparse reconstruction within a common framework, and it can rely on simple features. We characterize spatio-temporal events as time-series of motion patterns and by utilizing time-series kernels we apply standard structured-sparse coding techniques to tackle this important problem. We evaluated the KSS method using both gesture and facial expression datasets that include spontaneous behavior and differ in degree of difficulty and type of ground truth coding. KSS outperformed both sparse and non-sparse methods that utilize complex image features and their temporal extensions. In the case of early facial event classification KSS had 10% higher accuracy as measured by F1 score over kernel SVM methods1. PMID:27830214

Fab fragment labeled with ICG-derivative for detecting digestive tract cancer.

PubMed

Yano, Hiromi; Muguruma, Naoki; Ito, Susumu; Aoyagi, Eriko; Kimura, Tetsuo; Imoto, Yoshitaka; Cao, Jianxin; Inoue, Shohei; Sano, Shigeki; Nagao, Yoshimitsu; Kido, Hiroshi

2006-09-01

In previous studies, we generated infrared ray fluorescence-labeled monoclonal antibodies and developed an infrared ray fluorescence endoscope capable of detecting the monoclonal antibodies to establish a novel diagnostic technique for gastrointestinal cancer. Although the whole IgG molecule has commonly been used for preparation of labeled antibodies, labeled IgG displays insufficient sensitivity and specificity, probably resulting from non-specific binding of the Fc fragment to target cells or interference between fluorochromes on the identical labeled antibody, which might be caused by molecular structure. In this in vitro study, we characterized an Fc-free fluorescence-labeled Fab fragment, which was expected to yield more specific binding to target cells than the whole IgG molecule. An anti-mucin antibody and ICG-ATT, an ICG derivative, were used as the labeled antibody and labeling compound, respectively. Paraffin sections of excised gastric cancer tissues were subjected to staining. The labeled whole IgG molecule (ICG-ATT-labeled IgG) and the labeled Fab fragment (ICG-ATT-labeled Fab) were prepared according to a previous report, and the fluorescence properties, antibody activities, and features of fluorescence microscope images obtained from paraffin sections were compared. Both ICG-ATT-labeled Fab and ICG-ATT-labeled IgG were excited by a near infrared ray of 766nm, and maximum emission occurred at 804nm. Antibody activities of ICG-ATT-labeled Fab were shown to be similar to those of unlabeled anti-MUC1 antibody. The fluorescence intensity obtained from paraffin sections of excised gastric cancer tissues revealed a tendency to be greater with ICG-ATT-labeled Fab than with ICG-ATT-labeled IgG. The infrared ray fluorescence-labeled Fab fragment was likely to be more specific than the conventionally labeled antibodies. Fragmentation of antibodies is considered to contribute to improved sensitivity and specificity of labeled antibodies for detection of micro gastrointestinal cancers.

Comparison of peroxidase-labeled DNA probes with radioactive RNA probes for detection of human papillomaviruses by in situ hybridization in paraffin sections.

PubMed

Park, J S; Kurman, R J; Kessis, T D; Shah, K V

1991-01-01

A study comparing in situ hybridization using nonradioactive DNA probes directly conjugated with horseradish peroxidase (HRP), and 35S-labeled antisense RNA probes for human papillomavirus (HPV) types 6/11, 16, and 18 was performed on formalin-fixed, paraffin-embedded tissue from 34 lesions of the cervix and vulva. These lesions included exophytic condylomas and intraepithelial and invasive neoplasms. HPV 6/11 was detected in two of four condylomata acuminata by both in situ techniques. HPV 16 was detected in 13 of 30 cases of intraepithelial and invasive neoplasms by both methods. Discordance between the two methods occurred in two instances. The radiolabeled probe but not the HRP probe detected HPV 16 in one case of cervical intraepithelial neoplasia (CIN 3), whereas the converse occurred in one case of vulvar intraepithelial neoplasia (VIN 3). HPV 18 was not detected in any of the specimens by either method. This study demonstrates that nonradioactive HRP-labeled probes for the detection of specific HPV types are as sensitive as the more laborious and potentially hazardous radioactive probes.

Image fusion via nonlocal sparse K-SVD dictionary learning.

PubMed

Li, Ying; Li, Fangyi; Bai, Bendu; Shen, Qiang

2016-03-01

Image fusion aims to merge two or more images captured via various sensors of the same scene to construct a more informative image by integrating their details. Generally, such integration is achieved through the manipulation of the representations of the images concerned. Sparse representation plays an important role in the effective description of images, offering a great potential in a variety of image processing tasks, including image fusion. Supported by sparse representation, in this paper, an approach for image fusion by the use of a novel dictionary learning scheme is proposed. The nonlocal self-similarity property of the images is exploited, not only at the stage of learning the underlying description dictionary but during the process of image fusion. In particular, the property of nonlocal self-similarity is combined with the traditional sparse dictionary. This results in an improved learned dictionary, hereafter referred to as the nonlocal sparse K-SVD dictionary (where K-SVD stands for the K times singular value decomposition that is commonly used in the literature), and abbreviated to NL_SK_SVD. The performance of the NL_SK_SVD dictionary is applied for image fusion using simultaneous orthogonal matching pursuit. The proposed approach is evaluated with different types of images, and compared with a number of alternative image fusion techniques. The resultant superior fused images using the present approach demonstrates the efficacy of the NL_SK_SVD dictionary in sparse image representation.

Apply Pesticides Correctly, A Guide for Commercial Applicators: Seed Treatment.

ERIC Educational Resources Information Center

Wamsley, Mary Ann, Ed.; Vermeire, Donna M., Ed.

This guide contains basic information to meet specific standards for pesticide applicators. The text is concerned with the types of seeds that require chemical protection against pests. Methods of treatment and labeling requirements for such seeds as rye, wheat, soybeans, peas, and grass hybrids are discussed. Safety and environmental precautions…

A mixture of sparse coding models explaining properties of face neurons related to holistic and parts-based processing

PubMed Central

2017-01-01

Experimental studies have revealed evidence of both parts-based and holistic representations of objects and faces in the primate visual system. However, it is still a mystery how such seemingly contradictory types of processing can coexist within a single system. Here, we propose a novel theory called mixture of sparse coding models, inspired by the formation of category-specific subregions in the inferotemporal (IT) cortex. We developed a hierarchical network that constructed a mixture of two sparse coding submodels on top of a simple Gabor analysis. The submodels were each trained with face or non-face object images, which resulted in separate representations of facial parts and object parts. Importantly, evoked neural activities were modeled by Bayesian inference, which had a top-down explaining-away effect that enabled recognition of an individual part to depend strongly on the category of the whole input. We show that this explaining-away effect was indeed crucial for the units in the face submodel to exhibit significant selectivity to face images over object images in a similar way to actual face-selective neurons in the macaque IT cortex. Furthermore, the model explained, qualitatively and quantitatively, several tuning properties to facial features found in the middle patch of face processing in IT as documented by Freiwald, Tsao, and Livingstone (2009). These included, in particular, tuning to only a small number of facial features that were often related to geometrically large parts like face outline and hair, preference and anti-preference of extreme facial features (e.g., very large/small inter-eye distance), and reduction of the gain of feature tuning for partial face stimuli compared to whole face stimuli. Thus, we hypothesize that the coding principle of facial features in the middle patch of face processing in the macaque IT cortex may be closely related to mixture of sparse coding models. PMID:28742816

A mixture of sparse coding models explaining properties of face neurons related to holistic and parts-based processing.

PubMed

Hosoya, Haruo; Hyvärinen, Aapo

2017-07-01

Experimental studies have revealed evidence of both parts-based and holistic representations of objects and faces in the primate visual system. However, it is still a mystery how such seemingly contradictory types of processing can coexist within a single system. Here, we propose a novel theory called mixture of sparse coding models, inspired by the formation of category-specific subregions in the inferotemporal (IT) cortex. We developed a hierarchical network that constructed a mixture of two sparse coding submodels on top of a simple Gabor analysis. The submodels were each trained with face or non-face object images, which resulted in separate representations of facial parts and object parts. Importantly, evoked neural activities were modeled by Bayesian inference, which had a top-down explaining-away effect that enabled recognition of an individual part to depend strongly on the category of the whole input. We show that this explaining-away effect was indeed crucial for the units in the face submodel to exhibit significant selectivity to face images over object images in a similar way to actual face-selective neurons in the macaque IT cortex. Furthermore, the model explained, qualitatively and quantitatively, several tuning properties to facial features found in the middle patch of face processing in IT as documented by Freiwald, Tsao, and Livingstone (2009). These included, in particular, tuning to only a small number of facial features that were often related to geometrically large parts like face outline and hair, preference and anti-preference of extreme facial features (e.g., very large/small inter-eye distance), and reduction of the gain of feature tuning for partial face stimuli compared to whole face stimuli. Thus, we hypothesize that the coding principle of facial features in the middle patch of face processing in the macaque IT cortex may be closely related to mixture of sparse coding models.

Preparation of Labeled Aflatoxins with High Specific Activities

PubMed Central

Hsieh, D. P. H.; Mateles, R. I.

1971-01-01

Resting cells of Aspergillus parasiticus ATCC 15517 were used to prepare highly labeled aflatoxins from labeled acetate. High synthetic activity in growing cells was evidenced only during 40 to 70 hr of incubation. Glucose was required for high incorporation efficiency, whereas the concentration of the labeled acetate determined the specific activity of the product. When labeled acetate was continuously added to maintain a concentration near but not exceeding 10 mm, in a culture containing 30 g of glucose per liter, 2% of its labels could be recovered in the purified aflatoxins which have a specific activity more than three times that of the labeled acetate. PMID:4329435

Open-target sparse sensing of biological agents using DNA microarray

PubMed Central

2011-01-01

Background Current biosensors are designed to target and react to specific nucleic acid sequences or structural epitopes. These 'target-specific' platforms require creation of new physical capture reagents when new organisms are targeted. An 'open-target' approach to DNA microarray biosensing is proposed and substantiated using laboratory generated data. The microarray consisted of 12,900 25 bp oligonucleotide capture probes derived from a statistical model trained on randomly selected genomic segments of pathogenic prokaryotic organisms. Open-target detection of organisms was accomplished using a reference library of hybridization patterns for three test organisms whose DNA sequences were not included in the design of the microarray probes. Results A multivariate mathematical model based on the partial least squares regression (PLSR) was developed to detect the presence of three test organisms in mixed samples. When all 12,900 probes were used, the model correctly detected the signature of three test organisms in all mixed samples (mean(R2)) = 0.76, CI = 0.95), with a 6% false positive rate. A sampling algorithm was then developed to sparsely sample the probe space for a minimal number of probes required to capture the hybridization imprints of the test organisms. The PLSR detection model was capable of correctly identifying the presence of the three test organisms in all mixed samples using only 47 probes (mean(R2)) = 0.77, CI = 0.95) with nearly 100% specificity. Conclusions We conceived an 'open-target' approach to biosensing, and hypothesized that a relatively small, non-specifically designed, DNA microarray is capable of identifying the presence of multiple organisms in mixed samples. Coupled with a mathematical model applied to laboratory generated data, and sparse sampling of capture probes, the prototype microarray platform was able to capture the signature of each organism in all mixed samples with high sensitivity and specificity. It was demonstrated that this new approach to biosensing closely follows the principles of sparse sensing. PMID:21801424

Seismic classification through sparse filter dictionaries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hickmann, Kyle Scott; Srinivasan, Gowri

We tackle a multi-label classi cation problem involving the relation between acoustic- pro le features and the measured seismogram. To isolate components of the seismo- grams unique to each class of acoustic pro le we build dictionaries of convolutional lters. The convolutional- lter dictionaries for the individual classes are then combined into a large dictionary for the entire seismogram set. A given seismogram is classi ed by computing its representation in the large dictionary and then comparing reconstruction accuracy with this representation using each of the sub-dictionaries. The sub-dictionary with the minimal reconstruction error identi es the seismogram class.

Multi-Atlas Segmentation using Partially Annotated Data: Methods and Annotation Strategies.

PubMed

Koch, Lisa M; Rajchl, Martin; Bai, Wenjia; Baumgartner, Christian F; Tong, Tong; Passerat-Palmbach, Jonathan; Aljabar, Paul; Rueckert, Daniel

2017-08-22

Multi-atlas segmentation is a widely used tool in medical image analysis, providing robust and accurate results by learning from annotated atlas datasets. However, the availability of fully annotated atlas images for training is limited due to the time required for the labelling task. Segmentation methods requiring only a proportion of each atlas image to be labelled could therefore reduce the workload on expert raters tasked with annotating atlas images. To address this issue, we first re-examine the labelling problem common in many existing approaches and formulate its solution in terms of a Markov Random Field energy minimisation problem on a graph connecting atlases and the target image. This provides a unifying framework for multi-atlas segmentation. We then show how modifications in the graph configuration of the proposed framework enable the use of partially annotated atlas images and investigate different partial annotation strategies. The proposed method was evaluated on two Magnetic Resonance Imaging (MRI) datasets for hippocampal and cardiac segmentation. Experiments were performed aimed at (1) recreating existing segmentation techniques with the proposed framework and (2) demonstrating the potential of employing sparsely annotated atlas data for multi-atlas segmentation.

SparCLeS: dynamic l₁ sparse classifiers with level sets for robust beard/moustache detection and segmentation.

PubMed

Le, T Hoang Ngan; Luu, Khoa; Savvides, Marios

2013-08-01

Robust facial hair detection and segmentation is a highly valued soft biometric attribute for carrying out forensic facial analysis. In this paper, we propose a novel and fully automatic system, called SparCLeS, for beard/moustache detection and segmentation in challenging facial images. SparCLeS uses the multiscale self-quotient (MSQ) algorithm to preprocess facial images and deal with illumination variation. Histogram of oriented gradients (HOG) features are extracted from the preprocessed images and a dynamic sparse classifier is built using these features to classify a facial region as either containing skin or facial hair. A level set based approach, which makes use of the advantages of both global and local information, is then used to segment the regions of a face containing facial hair. Experimental results demonstrate the effectiveness of our proposed system in detecting and segmenting facial hair regions in images drawn from three databases, i.e., the NIST Multiple Biometric Grand Challenge (MBGC) still face database, the NIST Color Facial Recognition Technology FERET database, and the Labeled Faces in the Wild (LFW) database.

Dimension-Factorized Range Migration Algorithm for Regularly Distributed Array Imaging

PubMed Central

Guo, Qijia; Wang, Jie; Chang, Tianying

2017-01-01

The two-dimensional planar MIMO array is a popular approach for millimeter wave imaging applications. As a promising practical alternative, sparse MIMO arrays have been devised to reduce the number of antenna elements and transmitting/receiving channels with predictable and acceptable loss in image quality. In this paper, a high precision three-dimensional imaging algorithm is proposed for MIMO arrays of the regularly distributed type, especially the sparse varieties. Termed the Dimension-Factorized Range Migration Algorithm, the new imaging approach factorizes the conventional MIMO Range Migration Algorithm into multiple operations across the sparse dimensions. The thinner the sparse dimensions of the array, the more efficient the new algorithm will be. Advantages of the proposed approach are demonstrated by comparison with the conventional MIMO Range Migration Algorithm and its non-uniform fast Fourier transform based variant in terms of all the important characteristics of the approaches, especially the anti-noise capability. The computation cost is analyzed as well to evaluate the efficiency quantitatively. PMID:29113083

Saturation Fluorescence Labeling of Proteins for Proteomic Analyses

PubMed Central

Pretzer, Elizabeth; Wiktorowicz, John E.

2008-01-01

We present here an optimized and cost-effective approach to saturation fluorescence labeling of protein thiols for proteomic analysis. We investigated a number of conditions and reagent concentrations including a disulfide reducing agent (TCEP), pH, incubation time, linearity of labeling, and saturating dye: protein thiol ratio with protein standards to gauge specific and non-specific labeling. Efficacy of labeling under these conditions was quantified using specific fluorescence estimation, defined as the ratio of fluorescence pixel intensities and Coomassie-stained pixel intensities of bands after digital imaging. Factors leading to specific vs. non-specific labeling in the presence of thiourea are also discussed. We have found that reproducible saturation of available Cys residues of the proteins used as labeling standards (human carbonic anhydrase I, enolase, α-lactalbumin) is achieved at 50-100-fold excess of the uncharged maleimide-functionalized BODIPY™ dyes over Cys. We confirm our previous findings and those of others that the maleimide dyes are not impacted by the presence of 2M thiourea. Moreover, we establish that 2 mM TCEP used as reductant is optimal. We also establish further that labeling is optimal at pH 7.5 and complete after 30 min. Low non-specific labeling was gauged by the inclusion of non-Cys containing proteins (horse myoglobin, bovine carbonic anhydrase) to the labeling mixture. We also show that the dye exhibits little to no effect on the two dimensional mobilities of labeled proteins derived from cells. PMID:18191033

High resolution labeling of cholinergic nerve terminals using a specific fully active biotinylated botulinum neurotoxin type A.

PubMed

Arribas, M; Blasi, J; Egea, G; Fariñas, I; Solsona, C; Marsal, J

1993-12-15

We report here on the synthesis and characterization of a fully active biotinylated derivative of the botulinum neurotoxin type A. Different ratios of biotin: botulinum toxin were tested to optimize derivatizing conditions and a ratio of 35:1 was selected for further experiments. The average number of biotin groups per toxin molecule was estimated to be 7.8, occurring at both heavy and light chains, and almost all externally located and easily accessible to recognition by streptavidin. The modified toxin retained its toxicity and its ability to interact with biological membranes. Apart from its suitability for detection in Western blots and in microtiter well plates, biotinylated botulinum toxin proved to be adequate for morphological labeling studies at both light and electron microscopy. Peroxidase histochemistry in cryostat sections of intoxicated rat hemidiaphragm muscles showed a distinct labeling of end-plates. Electron microscopy studies were performed on the electric organ of Torpedo marmorata using colloidal gold-conjugated streptavidin for detection. After intoxication of electric organ fragments with the modified toxin, gold labels were found associated with the presynaptic plasma membrane of nerve terminals and with the membrane of synaptic vesicles. Moreover, the distribution of biotinylated botulinum toxin binding sites over the membrane of synaptosomes isolated from the electric organ of Torpedo and their relationship with intramembrane particles were analyzed using the replica-staining label-fracture technique. It was found that the toxin is never associated with intramembrane particles.

Ectopic transgene expression in the retina of four transgenic mouse lines

PubMed Central

Gábriel, Robert; Erdélyi, Ferenc; Szabó, Gábor; Lawrence, J. Josh

2017-01-01

Retinal expression of transgenes was examined in four mouse lines. Two constructs were driven by the choline acetyltransferase (ChAT) promoter: green fluorescent protein conjugated to tau protein (tau-GFP) or cytosolic yellow fluorescent protein (YFP) generated through CRE recombinase-induced expression of Rosa26 (ChAT-CRE/ Rosa26YFP). Two other constructs targeted inhibitory interneurons: GABAergic horizontal and amacrine cells identified by glutamic acid decarboxylase (GAD65-GFP) or parvalbumin (PV) cells (PV-CRE/Rosa26YFP). Animals were transcardially perfused and retinal sections prepared. Antibodies against PV, calretinin (CALR), calbindin (CALB), and tyrosine hydroxylase (TH) were used to counterstain transgene-expressing cells. In PVxRosa and ChAT-tauGFP constructs, staining appeared in vertically oriented row of processes resembling Müller cells. In the ChATxRosa construct, populations of amacrine cells and neurons in the ganglion cell layer were labeled. Some cones also exhibited GFP fluorescence. CALR, PV and TH were found in none of these cells. Occasionally, we found GFP/ CALR and GFP/PV double-stained cells in the ganglion cell layer (GCL). In the GAD65-GFP construct, all layers of the neuroretina were labeled, except photoreceptors. Not all horizontal cells expressed GFP. We did not find GFP/TH double-labeled cells and GFP was rarely present in CALR-and CALB-containing cells. Many PV-positive neurons were also labeled for GFP, including small diameter amacrines. In the GCL, single labeling for GFP and PV was ascertained, as well as several CALR/PV double-stained neurons. In the GCL, cells triple labeled with GFP/CALR/ CALB were sparse. In conclusion, only one of the four transgenic constructs exhibited an expression pattern consistent with endogenous retinal protein expression, while the others strongly suggested ectopic gene expression. PMID:26563404

The emotion seen in a face can be a methodological artifact: The process of elimination hypothesis.

PubMed

DiGirolamo, Marissa A; Russell, James A

2017-04-01

The claim that certain facial expressions signal certain specific emotions has been supported by high observer agreement in labeling the emotion predicted for that expression. Our hypothesis was that, with a method common to the field, high observer agreement can be achieved through a process of elimination: As participants move from trial to trial and they encounter a type of expression not previously encountered in the experiment, they tend to eliminate labels they have already associated with expressions seen on previous trials; they then select among labels not previously used. Seven experiments (total N = 1,068) here showed that the amount of agreement can be altered through a process of elimination. One facial expression not previously theorized to signal any emotion was consensually labeled as disgusted (76%), annoyed (85%), playful (89%), and mischievous (96%). Three quite different facial expressions were labeled nonplussed (82%, 93%, and 82%). A prototypical sad expression was labeled disgusted (55%), and a prototypical fear expression was labeled surprised (55%). A facial expression was labeled with a made-up word ( tolen ; 53%). Similar results were obtained both in a context focused on demonstrating a process of elimination and in one similar to a commonly used method, with 4 target expressions embedded with other expressions in 24 randomly ordered trials. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

In vivo modification of retroviral gag gene-encoded polyproteins by myristic acid.

PubMed Central

Schultz, A M; Oroszlan, S

1983-01-01

It has recently been shown by mass spectral analysis (Henderson et al., Proc. Natl. Acad. Sci. U.S.A. 80:339-343, 1983) that the p15gag protein of murine leukemia viruses contains a novel post-translational modification, an amino-terminal myristyl (tetradecanoyl) amide. In this report we show that p15gag is the only structural protein to contain this fatty acid. In addition, the gag precursor polyproteins of type B, C, and D retroviruses have been examined for the presence of myristic acid by metabolic labeling and immunoprecipitation studies. In a panel of mammalian type C retroviruses we found that the precursor polyprotein Pr65gag homologs, but not the glycosylated forms (gPr80gag homologs), were specifically labeled after a 5-min incubation of infected cells with [3H]myristic acid. The gag precursor polyprotein was also labeled in mouse mammary tumor virus and in Mason-Pfizer monkey virus, but Pr76gag of Rous sarcoma virus failed to incorporate [3H]myristate. Under similar conditions, [3H]palmitate was not found to be incorporated into any viral gag proteins. Thus, myristylation appears to be a common feature of mammalian type B, C, and D retroviruses but not of avian retroviruses. Images PMID:6302307

The localization of antigen in lymph nodes and its relation to specific antibody-producing cells

PubMed Central

Humphrey, J. H.; Askonas, Brigitte A.; Auzins, Ieva; Schechter, I.; Sela, M.

1967-01-01

A branched multichain polypeptide of the type p(Tyr,Glu)-pAla--pLys was synthesized from L-lysine, L-tyrosine, L-glutamic acid and tritium labelled DL-alanine; the final product, [3H](T,G)-A--L, had a specific radioactivity about 3 mc/mg. Its immunological behaviour in mice was compared with that of another preparation of (T,G)-A--L trace labelled with 125I at a specific radioactivity of 2 mc/mg. The [3H](T,G)-A--L proved to be only very weakly immunogenic compared with [125I](T,G)-A--L. This was not attributable to its radioactivity, but probably to its relatively low tyrosine content. However, detailed autoradiographical studies of the localization of the two materials in the draining lymph nodes after injection into the footpads of previously primed and of unprimed mice revealed no qualitative differences between their behaviour, which resembled that previously described for [125I](T,G)-A--L in similar experiments. When a preparation of (T,G)-A--L, labelled on the same molecules with both 3H and 125I, was studied in respect of gross retention of each label in lymph nodes, selective retention of 3H relative to 125I was observed. This was explained by greater susceptibility to peptidase activity of L-tyrosine residues at the ends of the side chains compared with that of the underlying polymeric DL-alanine. It is concluded that in studies of the fate of iodine-labelled peptides or proteins detection of the radioactive label is likely to indicate the presence of intact molecules or of large portions of them, but that failure to detect iodine cannot be taken to denote their absence. The autoradiographs suggested the existence of fine channels containing antigen penetrating through the cortical and intermediate zones of lymph nodes. ImagesFIG. 1-4 PMID:5338919

All-organic microelectromechanical systems integrating specific molecular recognition--a new generation of chemical sensors.

PubMed

Ayela, Cédric; Dubourg, Georges; Pellet, Claude; Haupt, Karsten

2014-09-03

Cantilever-type all-organic microelectromechanical systems based on molecularly imprinted polymers for specific analyte recognition are used as chemical sensors. They are produced by a simple spray-coating-shadow-masking process. Analyte binding to the cantilever generates a measurable change in its resonance frequency. This allows label-free detection by direct mass sensing of low-molecular-weight analytes at nanomolar concentrations. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Specific 13C labeling of leucine, valine and isoleucine methyl groups for unambiguous detection of long-range restraints in protein solid-state NMR studies.

PubMed

Fasshuber, Hannes Klaus; Demers, Jean-Philippe; Chevelkov, Veniamin; Giller, Karin; Becker, Stefan; Lange, Adam

2015-03-01

Here we present an isotopic labeling strategy to easily obtain unambiguous long-range distance restraints in protein solid-state NMR studies. The method is based on the inclusion of two biosynthetic precursors in the bacterial growth medium, α-ketoisovalerate and α-ketobutyrate, leading to the production of leucine, valine and isoleucine residues that are exclusively (13)C labeled on methyl groups. The resulting spectral simplification facilitates the collection of distance restraints, the verification of carbon chemical shift assignments and the measurement of methyl group dynamics. This approach is demonstrated on the type-three secretion system needle of Shigella flexneri, where 49 methyl-methyl and methyl-nitrogen distance restraints including 10 unambiguous long-range distance restraints could be collected. By combining this labeling scheme with ultra-fast MAS and proton detection, the assignment of methyl proton chemical shifts was achieved. Copyright © 2015 Elsevier Inc. All rights reserved.

Dense encoding of natural odorants by ensembles of sparsely activated neurons in the olfactory bulb

PubMed Central

Gschwend, Olivier; Beroud, Jonathan; Vincis, Roberto; Rodriguez, Ivan; Carleton, Alan

2016-01-01

Sensory information undergoes substantial transformation along sensory pathways, usually encompassing sparsening of activity. In the olfactory bulb, though natural odorants evoke dense glomerular input maps, mitral and tufted (M/T) cells tuning is considered to be sparse because of highly odor-specific firing rate change. However, experiments used to draw this conclusion were either based on recordings performed in anesthetized preparations or used monomolecular odorants presented at arbitrary concentrations. In this study, we evaluated the lifetime and population sparseness evoked by natural odorants by capturing spike temporal patterning of neuronal assemblies instead of individual M/T tonic activity. Using functional imaging and tetrode recordings in awake mice, we show that natural odorants at their native concentrations are encoded by broad assemblies of M/T cells. While reducing odorant concentrations, we observed a reduced number of activated glomeruli representations and consequently a narrowing of M/T tuning curves. We conclude that natural odorants at their native concentrations recruit M/T cells with phasic rather than tonic activity. When encoding odorants in assemblies, M/T cells carry information about a vast number of odorants (lifetime sparseness). In addition, each natural odorant activates a broad M/T cell assembly (population sparseness). PMID:27824096

Emerging applications of label-free optical biosensors

NASA Astrophysics Data System (ADS)

Zanchetta, Giuliano; Lanfranco, Roberta; Giavazzi, Fabio; Bellini, Tommaso; Buscaglia, Marco

2017-01-01

Innovative technical solutions to realize optical biosensors with improved performance are continuously proposed. Progress in material fabrication enables developing novel substrates with enhanced optical responses. At the same time, the increased spectrum of available biomolecular tools, ranging from highly specific receptors to engineered bioconjugated polymers, facilitates the preparation of sensing surfaces with controlled functionality. What remains often unclear is to which extent this continuous innovation provides effective breakthroughs for specific applications. In this review, we address this challenging question for the class of label-free optical biosensors, which can provide a direct signal upon molecular binding without using secondary probes. Label-free biosensors have become a consolidated approach for the characterization and screening of molecular interactions in research laboratories. However, in the last decade, several examples of other applications with high potential impact have been proposed. We review the recent advances in label-free optical biosensing technology by focusing on the potential competitive advantage provided in selected emerging applications, grouped on the basis of the target type. In particular, direct and real-time detection allows the development of simpler, compact, and rapid analytical methods for different kinds of targets, from proteins to DNA and viruses. The lack of secondary interactions facilitates the binding of small-molecule targets and minimizes the perturbation in single-molecule detection. Moreover, the intrinsic versatility of label-free sensing makes it an ideal platform to be integrated with biomolecular machinery with innovative functionality, as in case of the molecular tools provided by DNA nanotechnology.

Response of selected binomial coefficients to varying degrees of matrix sparseness and to matrices with known data interrelationships

USGS Publications Warehouse

Archer, A.W.; Maples, C.G.

1989-01-01

Numerous departures from ideal relationships are revealed by Monte Carlo simulations of widely accepted binomial coefficients. For example, simulations incorporating varying levels of matrix sparseness (presence of zeros indicating lack of data) and computation of expected values reveal that not only are all common coefficients influenced by zero data, but also that some coefficients do not discriminate between sparse or dense matrices (few zero data). Such coefficients computationally merge mutually shared and mutually absent information and do not exploit all the information incorporated within the standard 2 ?? 2 contingency table; therefore, the commonly used formulae for such coefficients are more complicated than the actual range of values produced. Other coefficients do differentiate between mutual presences and absences; however, a number of these coefficients do not demonstrate a linear relationship to matrix sparseness. Finally, simulations using nonrandom matrices with known degrees of row-by-row similarities signify that several coefficients either do not display a reasonable range of values or are nonlinear with respect to known relationships within the data. Analyses with nonrandom matrices yield clues as to the utility of certain coefficients for specific applications. For example, coefficients such as Jaccard, Dice, and Baroni-Urbani and Buser are useful if correction of sparseness is desired, whereas the Russell-Rao coefficient is useful when sparseness correction is not desired. ?? 1989 International Association for Mathematical Geology.

Functional brain networks reconstruction using group sparsity-regularized learning.

PubMed

Zhao, Qinghua; Li, Will X Y; Jiang, Xi; Lv, Jinglei; Lu, Jianfeng; Liu, Tianming

2018-06-01

Investigating functional brain networks and patterns using sparse representation of fMRI data has received significant interests in the neuroimaging community. It has been reported that sparse representation is effective in reconstructing concurrent and interactive functional brain networks. To date, most of data-driven network reconstruction approaches rarely take consideration of anatomical structures, which are the substrate of brain function. Furthermore, it has been rarely explored whether structured sparse representation with anatomical guidance could facilitate functional networks reconstruction. To address this problem, in this paper, we propose to reconstruct brain networks utilizing the structure guided group sparse regression (S2GSR) in which 116 anatomical regions from the AAL template, as prior knowledge, are employed to guide the network reconstruction when performing sparse representation of whole-brain fMRI data. Specifically, we extract fMRI signals from standard space aligned with the AAL template. Then by learning a global over-complete dictionary, with the learned dictionary as a set of features (regressors), the group structured regression employs anatomical structures as group information to regress whole brain signals. Finally, the decomposition coefficients matrix is mapped back to the brain volume to represent functional brain networks and patterns. We use the publicly available Human Connectome Project (HCP) Q1 dataset as the test bed, and the experimental results indicate that the proposed anatomically guided structure sparse representation is effective in reconstructing concurrent functional brain networks.

Protocol for the specialist supervised individualised multifactorial treatment of new clinically diagnosed type 2 diabetes in general practice (IDA): a prospective controlled multicentre open-label intervention study

PubMed Central

Stidsen, Jacob Volmer; Nielsen, Jens Steen; Henriksen, Jan Erik; Friborg, Søren Gunnar; Olesen, Thomas Bastholm; Olsen, Michael Hecht; Beck-Nielsen, Henning

2017-01-01

Introduction We present the protocol for a multifactorial intervention study designed to test whether individualised treatment, based on pathophysiological phenotyping and individualised treatment goals, improves type 2 diabetes (T2D) outcomes. Methods and analysis We will conduct a prospective controlled multicentre open-label intervention study, drawing on the longitudinal cohort of the Danish Centre for Strategic Research in Type 2 Diabetes (DD2). New clinically diagnosed patients with T2D in the intervention group will be assigned to receive individualised treatment by their general practitioner. Intervention patients will be compared with a matched control cohort of DD2 patients receiving routine clinical care. Among intervention patients, we will first do pathophysiological phenotyping to classify patients into WHO-defined T2D or other specific types of diabetes (monogenic diabetes, secondary diabetes etc). Patients with WHO-defined T2D will then be further subcharacterised by their beta-cell function (BCF) and insulin sensitivity (IS), using the revised homeostatic assessment model, as having either insulinopaenic T2D (high IS and low BCF), classical T2D (low IS and low BCF) or hyperinsulinaemic T2D (low IS and high BCF). For each subtype, a specific treatment algorithm will target the primary pathophysiological defect. Similarly, antihypertensive treatment will be targeted at the specific underlying pathophysiology, characterised by impedance cardiography (relative importance of vascular resistance, intravascular volume and cardiac inotropy). All treatment goals will be based on individual patient assessment of expected positive versus adverse effects. Web-based and face-to-face individualised lifestyle intervention will also be implemented to empower patients to make a sustainable improvement in daily physical activity and to change to a low-carbohydrate diet. Ethics and dissemination The study will use well-known pharmacological agents according to their labels; patient safety is therefore considered high. Study results will be published in international peer-reviewed journals. Trial registration number NCT02015130; Pre-results. PMID:29229652

Development of a Multiplexed Microsphere PCR for Culture-Free Detection and Gram-Typing of Bacteria in Human Blood Samples.

PubMed

Liang, Fang; Browne, Daniel J; Gray, Megan J; Gartlan, Kate H; Smith, David D; Barnard, Ross T; Hill, Geoffrey R; Corrie, Simon R; Markey, Kate A

2018-05-11

Bloodstream infection is a significant clinical problem, particularly in vulnerable patient groups such as those undergoing chemotherapy and bone marrow transplantation. Clinical diagnostics for suspected bloodstream infection remain centered around blood culture (highly variable timing, in the order of hours to days to become positive), and empiric use of broad-spectrum antibiotics is therefore employed for patients presenting with febrile neutropenia. Gram-typing provides the first opportunity to target therapy (e.g., combinations containing vancomycin or teicoplanin for Gram-positives; piperacillin-tazobactam or a carbapenem for Gram-negatives); however, current approaches require blood culture. In this study, we describe a multiplexed microsphere-PCR assay with flow cytometry readout, which can distinguish Gram-positive from Gram-negative bacterial DNA in a 3.5 h time period. The combination of a simple assay design (amplicon-dependent release of Gram-type specific Cy3-labeled oligonucleotides) and the Luminex-based readout (for quantifying each specific Cy3-labeled sequence) opens opportunities for further multiplexing. We demonstrate the feasibility of detecting common Gram-positive and Gram-negative organisms after spiking whole bacteria into healthy human blood prior to DNA extraction. Further development of DNA extraction methods is required to reach detection limits comparable to blood culture.

Tactical 3D Model Generation using Structure-From-Motion on Video from Unmanned Systems

DTIC Science & Technology

2015-04-01

available SfM application known as VisualSFM .6,7 VisualSFM is an end-user, “off-the-shelf” implementation of SfM that is easy to configure and used for...most 3D model generation applications from imagery. While the usual interface with VisualSFM is through their graphical user interface (GUI), we will be...of our system.5 There are two types of 3D model generation available within VisualSFM ; sparse and dense reconstruction. Sparse reconstruction begins

Fast sparsely synchronized brain rhythms in a scale-free neural network

NASA Astrophysics Data System (ADS)

Kim, Sang-Yoon; Lim, Woochang

2015-08-01

We consider a directed version of the Barabási-Albert scale-free network model with symmetric preferential attachment with the same in- and out-degrees and study the emergence of sparsely synchronized rhythms for a fixed attachment degree in an inhibitory population of fast-spiking Izhikevich interneurons. Fast sparsely synchronized rhythms with stochastic and intermittent neuronal discharges are found to appear for large values of J (synaptic inhibition strength) and D (noise intensity). For an intensive study we fix J at a sufficiently large value and investigate the population states by increasing D . For small D , full synchronization with the same population-rhythm frequency fp and mean firing rate (MFR) fi of individual neurons occurs, while for large D partial synchronization with fp> ( : ensemble-averaged MFR) appears due to intermittent discharge of individual neurons; in particular, the case of fp>4 is referred to as sparse synchronization. For the case of partial and sparse synchronization, MFRs of individual neurons vary depending on their degrees. As D passes a critical value D* (which is determined by employing an order parameter), a transition to unsynchronization occurs due to the destructive role of noise to spoil the pacing between sparse spikes. For D

27 CFR 4.23 - Varietal (grape type) labeling.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Varietal (grape type) labeling. 4.23 Section 4.23 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX AND TRADE BUREAU... Varietal (grape type) labeling. (a) General. The names of one or more grape varieties may be used as the...

Deep transfer learning for automatic target classification: MWIR to LWIR

NASA Astrophysics Data System (ADS)

Ding, Zhengming; Nasrabadi, Nasser; Fu, Yun

2016-05-01

Publisher's Note: This paper, originally published on 5/12/2016, was replaced with a corrected/revised version on 5/18/2016. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. When dealing with sparse or no labeled data in the target domain, transfer learning shows its appealing performance by borrowing the supervised knowledge from external domains. Recently deep structure learning has been exploited in transfer learning due to its attractive power in extracting effective knowledge through multi-layer strategy, so that deep transfer learning is promising to address the cross-domain mismatch. In general, cross-domain disparity can be resulted from the difference between source and target distributions or different modalities, e.g., Midwave IR (MWIR) and Longwave IR (LWIR). In this paper, we propose a Weighted Deep Transfer Learning framework for automatic target classification through a task-driven fashion. Specifically, deep features and classifier parameters are obtained simultaneously for optimal classification performance. In this way, the proposed deep structures can extract more effective features with the guidance of the classifier performance; on the other hand, the classifier performance is further improved since it is optimized on more discriminative features. Furthermore, we build a weighted scheme to couple source and target output by assigning pseudo labels to target data, therefore we can transfer knowledge from source (i.e., MWIR) to target (i.e., LWIR). Experimental results on real databases demonstrate the superiority of the proposed algorithm by comparing with others.

Circular dichroism and site-directed spin labeling reveal structural and dynamical features of high-pressure states of myoglobin

PubMed Central

Lerch, Michael T.; Horwitz, Joseph; McCoy, John; Hubbell, Wayne L.

2013-01-01

Excited states of proteins may play important roles in function, yet are difficult to study spectroscopically because of their sparse population. High hydrostatic pressure increases the equilibrium population of excited states, enabling their characterization [Akasaka K (2003) Biochemistry 42:10875–85]. High-pressure site-directed spin-labeling EPR (SDSL-EPR) was developed recently to map the site-specific structure and dynamics of excited states populated by pressure. To monitor global secondary structure content by circular dichroism (CD) at high pressure, a modified optical cell using a custom MgF2 window with a reduced aperture is introduced. Here, a combination of SDSL-EPR and CD is used to map reversible structural transitions in holomyoglobin and apomyoglobin (apoMb) as a function of applied pressure up to 2 kbar. CD shows that the high-pressure excited state of apoMb at pH 6 has helical content identical to that of native apoMb, but reversible changes reflecting the appearance of a conformational ensemble are observed by SDSL-EPR, suggesting a helical topology that fluctuates slowly on the EPR time scale. Although the high-pressure state of apoMb at pH 6 has been referred to as a molten globule, the data presented here reveal significant differences from the well-characterized pH 4.1 molten globule of apoMb. Pressure-populated states of both holomyoglobin and apoMb at pH 4.1 have significantly less helical structure, and for the latter, that may correspond to a transient folding intermediate. PMID:24248390

Label Review Training: Module 1: Label Basics, Page 21

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review. Learn about types of labels.

Cellulose and pectin localization in roots of mycorrhizalAllium porrum: labelling continuity between host cell wall and interfacial material.

PubMed

Bonfante-Fasolo, P; Vian, B; Perotto, S; Faccio, A; Knox, J P

1990-03-01

Two different types of contacts (or interfaces) exist between the plant host and the fungus during the vesicular-arbuscular mycorrhizal symbiosis, depending on whether the fungus is intercellular or intracellular. In the first case, the walls of the partners are in contact, while in the second case the fungal wall is separated from the host cytoplasm by the invaginated host plasmamembrane and by an interfacial material. In order to verify the origin of the interfacial material, affinity techniques which allow identification in situ of cell-wall components, were used. Cellobiohydrolase (CBH I) that binds to cellulose and a monoclonal antibody (JIM 5) that reacts with pectic components were tested on roots ofAllium porrum L. (leek) colonized byGlomus versiforme (Karst.) Berch. Both probes gave a labelling specific for the host cell wall, but each probe labelled over specific and distinct areas. The CBH I-colloidal gold complex heavily labelled the thick epidermal cell walls, whereas JIM 5 only labelled this area weakly. Labelling of the hypodermis was mostly on intercellular material after treatment with JIM 5 and only on the wall when CBH I was used. Suberin bands found on the radial walls were never labelled. Cortical cells were mostly labelled on the middle lamella with JIM 5 and on the wall with CBH I. Gold granules from the two probes were found in interfacial material both near the point where the fungus enters the cell and around the thin hyphae penetrating deep into the cell. The ultrastructural observations demonstrate that cellulose and pectic components have different but complementary distributions in the walls of root cells involved in the mycorrhizal symbiosis. These components show a similar distribution in the interfacial material laid down around the vesicular-arbuscular mycorrhizal fungus indicating that the interfacial material is of host origin.

Recombinant anti-tenascin antibody constructs

DOE Office of Scientific and Technical Information (OSTI.GOV)

ZALUTSKY, MICHAEL R

2006-08-29

The general objective of this research is to combine genetically derived molecular constructs reactive with tenascin, with appropriate radionuclides and labeling methods in order to generate more effective diagnostic and therapeutic reagents for oncologic nuclear medicine. Tenascin, a polymorphic extracellular matrix glycoprotein, is of interest because of its high expression on glioma, melanoma, as well as prostate and breast carcinoma. Recently, we have also documented high levels of tenascin in lymphomas, particularly those of higher grade, making the potential clinical impact of tenascin-specific radiodiagnostics and therapeutics even greater. An essential feature of our work plan is the ability to exploitmore » our extensive clinical experience in order to design second-generation constructs with properties which could improve clinical efficacy. To date, we have treated over 150 brain tumor patients with 131I-labeled murine 81C6, an antibody which binds specifically to the alternatively spliced fibronectin type III repeats CD of the tenascin molecule. During the current grant period, we have made several observations which form the basis for our proposed specific aims. First, tissue distribution and catabolism experiments in animal models have demonstrated enhanced stability for a chimeric construct composed of murine variable regions and human IgG2 constant domains. Furthermore, pharmacokinetic studies in patients with 131I-labeled chimeric 81C6 have shown significantly longer retention in glioma tumor resection cavities compared with its murine parent. Second, we have initiated the first clinical trial of an endoradiotherapeutic labeled with the 7.2-hr -particle emitter 211At. Twelve glioma patients have received 211At-labeled chimeric 81C6 directly into their brain tumor resection cavity, and very encouraging results have been obtained. Now that the feasibility of human studies with 211At, has been demonstrated, the development and evaluation of anti-tenascin constructs with optimized properties for use in tandem with short half life radionuclides such as 211At ( as well as 1.8-hr 18F for PET imaging) is warranted. Our specific aims are: 1) to construct a bivalent, anti-tenascin molecule containing murine 81C6 variable regions and the human IgG2 hinge region. Both the CH2 domain deletion construct (CH2) and F(ab’)2 will be investigated; 2) to construct a single-chain Fv dimer or multimer with adequate stability, affinity and immunoreactivity for use in tandem with 211At for therapy and 18F for imaging; 3) to generate higher affinity scFv constructs reactive with the alternatively spliced fibronectin type III repeats CD of the tenascin molecule via phage display technology and site-directed mutagenesis; 4) to label promising anti-tenascin constructs with radioiodine, 211At, and 18F and evaluate their potential as radiodiagnostic and radiotherapeutic agents. The proposed studies include: characterization of affinity and immunoreactivity after labeling; evaluation of tissue distribution and projected dosimetry in normal mice, and athymic rodents with subcutaneous, intracranial and neoplastic meningitis xenografts; investigation of the nature of low and high molecular weight labeled catabolites generated in mice; and assessment of cytotoxicity in vitro and in vivo models of human glioma, and possibly, other tenascin expressing tumors; and 5) to investigate strategies for labeling scFv monomers and dimers which will minimize retention of the radiohalogen in the kidneys through the use of negatively charged templates.« less

Calreticulin mutation-specific immunostaining in myeloproliferative neoplasms: pathogenetic insight and diagnostic value

PubMed Central

Vannucchi, A M; Rotunno, G; Bartalucci, N; Raugei, G; Carrai, V; Balliu, M; Mannarelli, C; Pacilli, A; Calabresi, L; Fjerza, R; Pieri, L; Bosi, A; Manfredini, R; Guglielmelli, P

2014-01-01

Mutations in the gene calreticulin (CALR) occur in the majority of JAK2- and MPL-unmutated patients with essential thrombocythemia (ET) and primary myelofibrosis (PMF); identifying CALR mutations contributes to the diagnostic pathway of ET and PMF. CALR mutations are heterogeneous spanning over the exon 9, but all result in a novel common protein C terminus. We developed a polyclonal antibody against a 17-amino-acid peptide derived from mutated calreticulin that was used for immunostaining of bone marrow biopsies. We show that this antibody specifically recognized patients harboring different types of CALR mutation with no staining in healthy controls and JAK2- or MPL-mutated ET and PMF. The labeling was mostly localized in megakaryocytes, whereas myeloid and erythroid cells showed faint staining, suggesting a preferential expression of calreticulin in megakaryocytes. Megakaryocytic-restricted expression of calreticulin was also demonstrated using an antibody against wild-type calreticulin and by measuring the levels of calreticulin RNA by gene expression analysis. Immunostaining using an antibody specific for mutated calreticulin may become a rapid, simple and cost-effective method for identifying CALR-mutated patients complementing molecular analysis; furthermore, the labeling pattern supports the preferential expansion of megakaryocytic cell lineage as a result of CALR mutation in an immature hematopoietic stem cell. PMID:24618731

Novel In Vivo Model for Combinatorial Fluorescence Labeling in Mouse Prostate

PubMed Central

Fang, Xiaolan; Gyabaah, Kenneth; Nickkholgh, Bita; Cline, J. Mark; Balaji, K.C.

2015-01-01

BACKGROUND The epithelial layer of prostate glands contains several types of cells, including luminal and basal cells. Yet there is paucity of animal models to study the cellular origin of normal or neoplastic development in the prostate to facilitate the treatment of heterogenous prostate diseases by targeting individual cell lineages. METHODS We developed a mouse model that expresses different types of fluorescent proteins (XFPs) specifically in prostatic cells. Using an in vivo stochastic fluorescent protein combinatorial strategy, XFP signals were expressed specifically in prostate of Protein Kinase D1 (PKD1) knock-out, K-RasG12D knock-in, and Phosphatase and tensin homolog (PTEN) and PKD1 double knock-out mice under the control of PB-Cre promoter. RESULTS In vivo XFP signals were observed in prostate of PKD1 knock-out, K-RasG12D knock-in, and PTEN PKD1 double knock-out mice, which developed normal, hyperplastic, and neoplastic prostate, respectively. The patchy expression pattern of XFPs in neoplasia tissue indicated the clonal origin of cancer cells in the prostate. CONCLUSIONS The transgenic mouse models demonstrate combinatorial fluorescent protein expression in normal and cancerous prostatic tissues. This novel prostate-specific fluorescent labeled mouse model, which we named Prorainbow, could be useful in studying benign and malignant pathology of prostate. PMID:25753731

Novel In Vivo model for combinatorial fluorescence labeling in mouse prostate.

PubMed

Fang, Xiaolan; Gyabaah, Kenneth; Nickkholgh, Bita; Cline, J Mark; Balaji, K C

2015-06-15

The epithelial layer of prostate glands contains several types of cells, including luminal and basal cells. Yet there is paucity of animal models to study the cellular origin of normal or neoplastic development in the prostate to facilitate the treatment of heterogenous prostate diseases by targeting individual cell lineages. We developed a mouse model that expresses different types of fluorescent proteins (XFPs) specifically in prostatic cells. Using an in vivo stochastic fluorescent protein combinatorial strategy, XFP signals were expressed specifically in prostate of Protein Kinase D1 (PKD1) knock-out, K-Ras(G) (12) (D) knock-in, and Phosphatase and tensin homolog (PTEN) and PKD1 double knock-out mice under the control of PB-Cre promoter. In vivo XFP signals were observed in prostate of PKD1 knock-out, K-Ras(G) (12) (D) knock-in, and PTEN PKD1 double knock-out mice, which developed normal, hyperplastic, and neoplastic prostate, respectively. The patchy expression pattern of XFPs in neoplasia tissue indicated the clonal origin of cancer cells in the prostate. The transgenic mouse models demonstrate combinatorial fluorescent protein expression in normal and cancerous prostatic tissues. This novel prostate-specific fluorescent labeled mouse model, which we named Prorainbow, could be useful in studying benign and malignant pathology of prostate. © 2015 Wiley Periodicals, Inc.

Novel contiguous gene deletion in peruvian girl with Trichothiodystrophy type 4 and glutaric aciduria type 3.

PubMed

La Serna-Infantes, Jorge; Pastor, Miguel Chávez; Trubnykova, Milana; Velásquez, Félix Chavesta; Sotomayor, Flor Vásquez; Barriga, Hugo Abarca

2018-07-01

Trichothiodystrophy type 4 is a rare autosomal recessive and ectodermal disorder, characterized by dry, brittle, sparse and sulfur-deficient hair and other features like intellectual disability, ichthyotic skin and short stature, caused by a homozygous mutation in MPLKIP gene. Glutaric aciduria type 3 is caused by a homozygous mutation in SUGCT gene with no distinctive phenotype. Both genes are localized on chromosome 7 (7p14). We report an 8-year-old female with short stature, microcephaly, development delay, intellectual disability and hair characterized for dark, short, coarse, sparse and brittle associated to classical trichorrhexis microscopy pattern. Chromosome microarray analysis showed a 125 kb homozygous pathogenic deletion, which includes genes MPLKIP and SUGCT, not described before. This is the first case described in Peru of a novel contiguous gene deletion of Trichothiodystrophy type 4 and Glutaric aciduria type 3 performed by chromosome microarray analysis, highlighting the contribution and importance of molecular technologies on diagnosis of rare genetic conditions. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Temporally-Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer’s Disease

PubMed Central

Jie, Biao; Liu, Mingxia; Liu, Jun

2016-01-01

Sparse learning has been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer’s disease (AD) and its prodromal stage, i.e., mild cognitive impairment (MCI). However, most existing sparse learning-based studies only adopt cross-sectional analysis methods, where the sparse model is learned using data from a single time-point. Actually, multiple time-points of data are often available in brain imaging applications, which can be used in some longitudinal analysis methods to better uncover the disease progression patterns. Accordingly, in this paper we propose a novel temporally-constrained group sparse learning method aiming for longitudinal analysis with multiple time-points of data. Specifically, we learn a sparse linear regression model by using the imaging data from multiple time-points, where a group regularization term is first employed to group the weights for the same brain region across different time-points together. Furthermore, to reflect the smooth changes between data derived from adjacent time-points, we incorporate two smoothness regularization terms into the objective function, i.e., one fused smoothness term which requires that the differences between two successive weight vectors from adjacent time-points should be small, and another output smoothness term which requires the differences between outputs of two successive models from adjacent time-points should also be small. We develop an efficient optimization algorithm to solve the proposed objective function. Experimental results on ADNI database demonstrate that, compared with conventional sparse learning-based methods, our proposed method can achieve improved regression performance and also help in discovering disease-related biomarkers. PMID:27093313

Label Review Training: Module 1: Label Basics, Page 18

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review. This section discusses the types of labels.

Site-Specific Bioorthogonal Labeling for Fluorescence Imaging of Intracellular Proteins in Living Cells.

PubMed

Peng, Tao; Hang, Howard C

2016-11-02

Over the past years, fluorescent proteins (e.g., green fluorescent proteins) have been widely utilized to visualize recombinant protein expression and localization in live cells. Although powerful, fluorescent protein tags are limited by their relatively large sizes and potential perturbation to protein function. Alternatively, site-specific labeling of proteins with small-molecule organic fluorophores using bioorthogonal chemistry may provide a more precise and less perturbing method. This approach involves site-specific incorporation of unnatural amino acids (UAAs) into proteins via genetic code expansion, followed by bioorthogonal chemical labeling with small organic fluorophores in living cells. While this approach has been used to label extracellular proteins for live cell imaging studies, site-specific bioorthogonal labeling and fluorescence imaging of intracellular proteins in live cells is still challenging. Herein, we systematically evaluate site-specific incorporation of diastereomerically pure bioorthogonal UAAs bearing stained alkynes or alkenes into intracellular proteins for inverse-electron-demand Diels-Alder cycloaddition reactions with tetrazine-functionalized fluorophores for live cell labeling and imaging in mammalian cells. Our studies show that site-specific incorporation of axial diastereomer of trans-cyclooct-2-ene-lysine robustly affords highly efficient and specific bioorthogonal labeling with monosubstituted tetrazine fluorophores in live mammalian cells, which enabled us to image the intracellular localization and real-time dynamic trafficking of IFITM3, a small membrane-associated protein with only 137 amino acids, for the first time. Our optimized UAA incorporation and bioorthogonal labeling conditions also enabled efficient site-specific fluorescence labeling of other intracellular proteins for live cell imaging studies in mammalian cells.

Nonconvex Sparse Logistic Regression With Weakly Convex Regularization

NASA Astrophysics Data System (ADS)

Shen, Xinyue; Gu, Yuantao

2018-06-01

In this work we propose to fit a sparse logistic regression model by a weakly convex regularized nonconvex optimization problem. The idea is based on the finding that a weakly convex function as an approximation of the $\\ell_0$ pseudo norm is able to better induce sparsity than the commonly used $\\ell_1$ norm. For a class of weakly convex sparsity inducing functions, we prove the nonconvexity of the corresponding sparse logistic regression problem, and study its local optimality conditions and the choice of the regularization parameter to exclude trivial solutions. Despite the nonconvexity, a method based on proximal gradient descent is used to solve the general weakly convex sparse logistic regression, and its convergence behavior is studied theoretically. Then the general framework is applied to a specific weakly convex function, and a necessary and sufficient local optimality condition is provided. The solution method is instantiated in this case as an iterative firm-shrinkage algorithm, and its effectiveness is demonstrated in numerical experiments by both randomly generated and real datasets.

Full-reference quality assessment of stereoscopic images by learning binocular receptive field properties.

PubMed

Shao, Feng; Li, Kemeng; Lin, Weisi; Jiang, Gangyi; Yu, Mei; Dai, Qionghai

2015-10-01

Quality assessment of 3D images encounters more challenges than its 2D counterparts. Directly applying 2D image quality metrics is not the solution. In this paper, we propose a new full-reference quality assessment for stereoscopic images by learning binocular receptive field properties to be more in line with human visual perception. To be more specific, in the training phase, we learn a multiscale dictionary from the training database, so that the latent structure of images can be represented as a set of basis vectors. In the quality estimation phase, we compute sparse feature similarity index based on the estimated sparse coefficient vectors by considering their phase difference and amplitude difference, and compute global luminance similarity index by considering luminance changes. The final quality score is obtained by incorporating binocular combination based on sparse energy and sparse complexity. Experimental results on five public 3D image quality assessment databases demonstrate that in comparison with the most related existing methods, the devised algorithm achieves high consistency with subjective assessment.

KChIPs and Kv4 alpha subunits as integral components of A-type potassium channels in mammalian brain.

PubMed

Rhodes, Kenneth J; Carroll, Karen I; Sung, M Amy; Doliveira, Lisa C; Monaghan, Michael M; Burke, Sharon L; Strassle, Brian W; Buchwalder, Lynn; Menegola, Milena; Cao, Jie; An, W Frank; Trimmer, James S

2004-09-08

Voltage-gated potassium (Kv) channels from the Kv4, or Shal-related, gene family underlie a major component of the A-type potassium current in mammalian central neurons. We recently identified a family of calcium-binding proteins, termed KChIPs (Kv channel interacting proteins), that bind to the cytoplasmic N termini of Kv4 family alpha subunits and modulate their surface density, inactivation kinetics, and rate of recovery from inactivation (An et al., 2000). Here, we used single and double-label immunohistochemistry, together with circumscribed lesions and coimmunoprecipitation analyses, to examine the regional and subcellular distribution of KChIPs1-4 and Kv4 family alpha subunits in adult rat brain. Immunohistochemical staining using KChIP-specific monoclonal antibodies revealed that the KChIP polypeptides are concentrated in neuronal somata and dendrites where their cellular and subcellular distribution overlaps, in an isoform-specific manner, with that of Kv4.2 and Kv4.3. For example, immunoreactivity for KChIP1 and Kv4.3 is concentrated in the somata and dendrites of hippocampal, striatal, and neocortical interneurons. Immunoreactivity for KChIP2, KChIP4, and Kv4.2 is concentrated in the apical and basal dendrites of hippocampal and neocortical pyramidal cells. Double-label immunofluorescence labeling revealed that throughout the forebrain, KChIP2 and KChIP4 are frequently colocalized with Kv4.2, whereas in cortical, hippocampal, and striatal interneurons, KChIP1 is frequently colocalized with Kv4.3. Coimmunoprecipitation analyses confirmed that all KChIPs coassociate with Kv4 alpha subunits in brain membranes, indicating that KChIPs 1-4 are integral components of native A-type Kv channel complexes and are likely to play a major role as modulators of somatodendritic excitability.

Segmental Versican Expression in the Trabecular Meshwork and Involvement in Outflow Facility

PubMed Central

Keller, Kate E.; Bradley, John M.; Vranka, Janice A.

2011-01-01

Purpose. Versican is a large proteoglycan with numerous chondroitin sulfate (CS) glycosaminoglycan (GAG) side chains attached. To assess versican's potential contributions to aqueous humor outflow resistance, its segmental distribution in the trabecular meshwork (TM) and the effect on outflow facility of silencing the versican gene were evaluated. Methods. Fluorescent quantum dots (Qdots) were perfused to label outflow pathways of anterior segments. Immunofluorescence with confocal microscopy and quantitative RT-PCR were used to determine versican protein and mRNA distribution relative to Qdot-labeled regions. Lentiviral delivery of shRNA-silencing cassettes to TM cells in perfused anterior segment cultures was used to evaluate the involvement of versican and CS GAG chains in outflow facility. Results. Qdot uptake by TM cells showed considerable segmental variability in both human and porcine outflow pathways. Regional levels of Qdot labeling were inversely related to versican protein and mRNA levels; versican levels were relatively high in sparsely Qdot-labeled regions and low in densely labeled regions. Versican silencing decreased outflow facility in human and increased facility in porcine anterior segments. However, RNAi silencing of ChGn, an enzyme unique to CS GAG biosynthesis, increased outflow facility in both species. The fibrillar pattern of versican immunostaining in the TM juxtacanalicular region was disrupted after versican silencing in perfusion culture. Conclusions. Versican appears to be a central component of the outflow resistance, where it may organize GAGs and other ECM components to facilitate and control open flow channels in the TM. However, the exact molecular organization of this resistance appears to differ between human and porcine eyes. PMID:21596823

Superresolution imaging in live Caulobacter crescentus cells using photoswitchable enhanced yellow fluorescent protein

NASA Astrophysics Data System (ADS)

Biteen, Julie S.; Thompson, Michael A.; Tselentis, Nicole K.; Shapiro, Lucy; Moerner, W. E.

2009-02-01

Recently, photoactivation and photoswitching were used to control single-molecule fluorescent labels and produce images of cellular structures beyond the optical diffraction limit (e.g., PALM, FPALM, and STORM). While previous live-cell studies relied on sophisticated photoactivatable fluorescent proteins, we show in the present work that superresolution imaging can be performed with fusions to the commonly used fluorescent protein EYFP. Rather than being photoactivated, however, EYFP can be reactivated with violet light after apparent photobleaching. In each cycle after initial imaging, only a sparse subset fluorophores is reactivated and localized, and the final image is then generated from the measured single-molecule positions. Because these methods are based on the imaging nanometer-sized single-molecule emitters and on the use of an active control mechanism to produce sparse sub-ensembles, we suggest the phrase "Single-Molecule Active-Control Microscopy" (SMACM) as an inclusive term for this general imaging strategy. In this paper, we address limitations arising from physiologically imposed upper boundaries on the fluorophore concentration by employing dark time-lapse periods to allow single-molecule motions to fill in filamentous structures, increasing the effective labeling concentration while localizing each emitter at most once per resolution-limited spot. We image cell-cycle-dependent superstructures of the bacterial actin protein MreB in live Caulobacter crescentus cells with sub-40-nm resolution for the first time. Furthermore, we quantify the reactivation quantum yield of EYFP, and find this to be 1.6 x 10-6, on par with conventional photoswitchable fluorescent proteins like Dronpa. These studies show that EYFP is a useful emitter for in vivo superresolution imaging of intracellular structures in bacterial cells.

VGLUT1 and VGLUT2 innervation in autonomic regions of intact and transected rat spinal cord.

PubMed

Llewellyn-Smith, Ida J; Martin, Carolyn L; Fenwick, Natalie M; Dicarlo, Stephen E; Lujan, Heidi L; Schreihofer, Ann M

2007-08-20

Fast excitatory neurotransmission to sympathetic and parasympathetic preganglionic neurons (SPN and PPN) is glutamatergic. To characterize this innervation in spinal autonomic regions, we localized immunoreactivity for vesicular glutamate transporters (VGLUTs) 1 and 2 in intact cords and after upper thoracic complete transections. Preganglionic neurons were retrogradely labeled by intraperitoneal Fluoro-Gold or with cholera toxin B (CTB) from superior cervical, celiac, or major pelvic ganglia or adrenal medulla. Glutamatergic somata were localized with in situ hybridization for VGLUT mRNA. In intact cords, all autonomic areas contained abundant VGLUT2-immunoreactive axons and synapses. CTB-immunoreactive SPN and PPN received many close appositions from VGLUT2-immunoreactive axons. VGLUT2-immunoreactive synapses occurred on Fluoro-Gold-labeled SPN. Somata with VGLUT2 mRNA occurred throughout the spinal gray matter. VGLUT2 immunoreactivity was not noticeably affected caudal to a transection. In contrast, in intact cords, VGLUT1-immunoreactive axons were sparse in the intermediolateral cell column (IML) and lumbosacral parasympathetic nucleus but moderately dense above the central canal. VGLUT1-immunoreactive close appositions were rare on SPN in the IML and the central autonomic area and on PPN. Transection reduced the density of VGLUT1-immunoreactive axons in sympathetic subnuclei but increased their density in the parasympathetic nucleus. Neuronal cell bodies with VGLUT1 mRNA occurred only in Clarke's column. These data indicate that SPN and PPN are densely innervated by VGLUT2-immunoreactive axons, some of which arise from spinal neurons. In contrast, the VGLUT1-immunoreactive innervation of spinal preganglionic neurons is sparse, and some may arise from supraspinal sources. Increased VGLUT1 immunoreactivity after transection may correlate with increased glutamatergic transmission to PPN. (c) 2007 Wiley-Liss, Inc.

21 CFR 101.65 - Implied nutrient content claims and related label statements.

Code of Federal Regulations, 2012 CFR

2012-04-01

..., physiological, pathological, or other condition, where the claim identifies the special diet of which the food... certain amount (e.g., “high in oat bran”) are implied nutrient content claims and must comply with... the ingredient or type of preparation. If a more specific level is claimed (e.g., “high in ___), that...

21 CFR 101.65 - Implied nutrient content claims and related label statements.

Code of Federal Regulations, 2013 CFR

2013-04-01

..., physiological, pathological, or other condition, where the claim identifies the special diet of which the food... certain amount (e.g., “high in oat bran”) are implied nutrient content claims and must comply with... the ingredient or type of preparation. If a more specific level is claimed (e.g., “high in ___), that...

21 CFR 101.65 - Implied nutrient content claims and related label statements.

Code of Federal Regulations, 2014 CFR

2014-04-01

..., physiological, pathological, or other condition, where the claim identifies the special diet of which the food... certain amount (e.g., “high in oat bran”) are implied nutrient content claims and must comply with... the ingredient or type of preparation. If a more specific level is claimed (e.g., “high in ___), that...

Proximity labeling of cis-ligands of CD22/Siglec-2 reveals stepwise α2,6 sialic acid-dependent and -independent interactions.

PubMed

Alborzian Deh Sheikh, Amin; Akatsu, Chizuru; Imamura, Akihiro; Abdu-Allah, Hajjaj H M; Takematsu, Hiromu; Ando, Hiromune; Ishida, Hideharu; Tsubata, Takeshi

2018-01-01

Lectins expressed on the cell surface are often bound and regulated by the membrane molecules containing the glycan ligands on the same cell (cis-ligands). However, molecular nature and function of cis-ligands are generally poorly understood partly because of weak interaction between lectins and glycan ligands. Cis-ligands are most extensively studied in CD22 (also known as Siglec-2), an inhibitory B lymphocyte receptor specifically recognizing α2,6 sialic acids. CD22, CD45 and IgM are suggested to be ligands of CD22. Here we labeled molecules in the proximity of CD22 in situ on B cell surface using biotin-tyramide. Molecules including CD22, CD45 and IgM were labeled in wild-type but not ST6GalI -/- B cells that lack α2,6 sialic acids, indicating that these molecules associate with CD22 by lectin-glycan interaction, and are therefore cis-ligands. In ST6GalI -/- B cells, these cis-ligands are located in a slightly more distance from CD22. Thus, the lectin-glycan interaction recruits cis-ligands already located in the relative proximity of CD22 through non-lectin-glycan interaction to the close proximity. Moreover, cis-ligands are labeled in Cmah -/- B cells that lack Neu5Gc preferred by mouse CD22 as efficiently as in wild-type B cells, indicating that very low affinity lectin-glycan interaction is sufficient for recruiting cis-ligands, and can be detected by proximity labeling. Thus, proximity labeling with tyramide appears to be a useful method to identify cis-ligands and to analyze their interaction with the lectins. Copyright © 2017 Elsevier Inc. All rights reserved.

Label Review Training: Module 1: Label Basics, Page 23

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review. Lists types of labels that do not require review.

Capacity for patterns and sequences in Kanerva's SDM as compared to other associative memory models. [Sparse, Distributed Memory

NASA Technical Reports Server (NTRS)

Keeler, James D.

1988-01-01

The information capacity of Kanerva's Sparse Distributed Memory (SDM) and Hopfield-type neural networks is investigated. Under the approximations used here, it is shown that the total information stored in these systems is proportional to the number connections in the network. The proportionality constant is the same for the SDM and Hopfield-type models independent of the particular model, or the order of the model. The approximations are checked numerically. This same analysis can be used to show that the SDM can store sequences of spatiotemporal patterns, and the addition of time-delayed connections allows the retrieval of context dependent temporal patterns. A minor modification of the SDM can be used to store correlated patterns.

40 CFR Appendix I to Part 60 - Removable Label and Owner's Manual

Code of Federal Regulations, 2014 CFR

2014-07-01

... various label types that may apply. 2.2 Certified Wood Heaters The design and content of certified wood... three variables listed above. Figures 1 and 2 illustrate the variations in label design. Figure 1 is a... general layout, the type font and type size illustrated in Figures 1 and 2. 2.2.1 Identification and...

40 CFR Appendix I to Part 60 - Removable Label and Owner's Manual

Code of Federal Regulations, 2012 CFR

2012-07-01

... various label types that may apply. 2.2 Certified Wood Heaters The design and content of certified wood... three variables listed above. Figures 1 and 2 illustrate the variations in label design. Figure 1 is a... general layout, the type font and type size illustrated in Figures 1 and 2. 2.2.1Identification and...

40 CFR Appendix I to Part 60 - Removable Label and Owner's Manual

Code of Federal Regulations, 2013 CFR

2013-07-01

... various label types that may apply. 2.2 Certified Wood Heaters The design and content of certified wood... three variables listed above. Figures 1 and 2 illustrate the variations in label design. Figure 1 is a... general layout, the type font and type size illustrated in Figures 1 and 2. 2.2.1Identification and...

Immunomicrospheres - Reagents for cell labeling and separation

NASA Technical Reports Server (NTRS)

Rembaum, A.; Dreyer, W. J.

1980-01-01

Immunomicrospheres are specially designed microscopic particles that have antibodies or similar molecules chemically bound to their surfaces. The antibody-coated microspheres react in a highly specific way with target cells, viruses, or other antigenic agents. Immunomicrospheres may be synthesized so that they incorporate compounds that are highly radioactive, intensely fluorescent, magnetic, electron opaque, highly colored, or pharmacologically active. These various types of microspheres may be coated with pure, highly specific monoclonal antibodies obtained by the new hybridoma cell cloning techniques or with conventional antibody preparations. Some of the many present and potential applications for these new reagents are (1) new types of radioimmune or immunofluorescent assays, (2) improved fluorescence microscopy, (3) separation of cells on the basis of the fluorescent, electrophoretic, or magnetic properties of bound immunomicrospheres, (4) markers for use in several types of electron or standard light microscopy, and (5) delivery of lethal compouds to specific undesirable living cells. The combination of the various new types of synthetic microspheres and the newly available homogeneous antibodies offers new opportunities in research, diagnosis, and therapy.

Abnormal Functional Lateralization and Activity of Language Brain Areas in Typical Specific Language Impairment (Developmental Dysphasia)

ERIC Educational Resources Information Center

de Guibert, Clement; Maumet, Camille; Jannin, Pierre; Ferre, Jean-Christophe; Treguier, Catherine; Barillot, Christian; Le Rumeur, Elisabeth; Allaire, Catherine; Biraben, Arnaud

2011-01-01

Atypical functional lateralization and specialization for language have been proposed to account for developmental language disorders, yet results from functional neuroimaging studies are sparse and inconsistent. This functional magnetic resonance imaging study compared children with a specific subtype of specific language impairment affecting…

Measurement of Single Macromolecule Orientation by Total Internal Reflection Fluorescence Polarization Microscopy

PubMed Central

Forkey, Joseph N.; Quinlan, Margot E.; Goldman, Yale E.

2005-01-01

A new approach is presented for measuring the three-dimensional orientation of individual macromolecules using single molecule fluorescence polarization (SMFP) microscopy. The technique uses the unique polarizations of evanescent waves generated by total internal reflection to excite the dipole moment of individual fluorophores. To evaluate the new SMFP technique, single molecule orientation measurements from sparsely labeled F-actin are compared to ensemble-averaged orientation data from similarly prepared densely labeled F-actin. Standard deviations of the SMFP measurements taken at 40 ms time intervals indicate that the uncertainty for individual measurements of axial and azimuthal angles is ∼10° at 40 ms time resolution. Comparison with ensemble data shows there are no substantial systematic errors associated with the single molecule measurements. In addition to evaluating the technique, the data also provide a new measurement of the torsional rigidity of F-actin. These measurements support the smaller of two values of the torsional rigidity of F-actin previously reported. PMID:15894632

High-performance sparse matrix-matrix products on Intel KNL and multicore architectures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagasaka, Y; Matsuoka, S; Azad, A

Sparse matrix-matrix multiplication (SpGEMM) is a computational primitive that is widely used in areas ranging from traditional numerical applications to recent big data analysis and machine learning. Although many SpGEMM algorithms have been proposed, hardware specific optimizations for multi- and many-core processors are lacking and a detailed analysis of their performance under various use cases and matrices is not available. We firstly identify and mitigate multiple bottlenecks with memory management and thread scheduling on Intel Xeon Phi (Knights Landing or KNL). Specifically targeting multi- and many-core processors, we develop a hash-table-based algorithm and optimize a heap-based shared-memory SpGEMM algorithm. Wemore » examine their performance together with other publicly available codes. Different from the literature, our evaluation also includes use cases that are representative of real graph algorithms, such as multi-source breadth-first search or triangle counting. Our hash-table and heap-based algorithms are showing significant speedups from libraries in the majority of the cases while different algorithms dominate the other scenarios with different matrix size, sparsity, compression factor and operation type. We wrap up in-depth evaluation results and make a recipe to give the best SpGEMM algorithm for target scenario. A critical finding is that hash-table-based SpGEMM gets a significant performance boost if the nonzeros are not required to be sorted within each row of the output matrix.« less

Piano Transcription with Convolutional Sparse Lateral Inhibition

DOE PAGES

Cogliati, Andrea; Duan, Zhiyao; Wohlberg, Brendt Egon

2017-02-08

This paper extends our prior work on contextdependent piano transcription to estimate the length of the notes in addition to their pitch and onset. This approach employs convolutional sparse coding along with lateral inhibition constraints to approximate a musical signal as the sum of piano note waveforms (dictionary elements) convolved with their temporal activations. The waveforms are pre-recorded for the specific piano to be transcribed in the specific environment. A dictionary containing multiple waveforms per pitch is generated by truncating a long waveform for each pitch to different lengths. During transcription, the dictionary elements are fixed and their temporal activationsmore » are estimated and post-processed to obtain the pitch, onset and note length estimation. A sparsity penalty promotes globally sparse activations of the dictionary elements, and a lateral inhibition term penalizes concurrent activations of different waveforms corresponding to the same pitch within a temporal neighborhood, to achieve note length estimation. Experiments on the MAPS dataset show that the proposed approach significantly outperforms a state-of-the-art music transcription method trained in the same context-dependent setting in transcription accuracy.« less

Piano Transcription with Convolutional Sparse Lateral Inhibition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cogliati, Andrea; Duan, Zhiyao; Wohlberg, Brendt Egon

This paper extends our prior work on contextdependent piano transcription to estimate the length of the notes in addition to their pitch and onset. This approach employs convolutional sparse coding along with lateral inhibition constraints to approximate a musical signal as the sum of piano note waveforms (dictionary elements) convolved with their temporal activations. The waveforms are pre-recorded for the specific piano to be transcribed in the specific environment. A dictionary containing multiple waveforms per pitch is generated by truncating a long waveform for each pitch to different lengths. During transcription, the dictionary elements are fixed and their temporal activationsmore » are estimated and post-processed to obtain the pitch, onset and note length estimation. A sparsity penalty promotes globally sparse activations of the dictionary elements, and a lateral inhibition term penalizes concurrent activations of different waveforms corresponding to the same pitch within a temporal neighborhood, to achieve note length estimation. Experiments on the MAPS dataset show that the proposed approach significantly outperforms a state-of-the-art music transcription method trained in the same context-dependent setting in transcription accuracy.« less

Beauty is in the efficient coding of the beholder.

PubMed

Renoult, Julien P; Bovet, Jeanne; Raymond, Michel

2016-03-01

Sexual ornaments are often assumed to be indicators of mate quality. Yet it remains poorly known how certain ornaments are chosen before any coevolutionary race makes them indicative. Perceptual biases have been proposed to play this role, but known biases are mostly restricted to a specific taxon, which precludes evaluating their general importance in sexual selection. Here we identify a potentially universal perceptual bias in mate choice. We used an algorithm that models the sparseness of the activity of simple cells in the primary visual cortex (or V1) of humans when coding images of female faces. Sparseness was found positively correlated with attractiveness as rated by men and explained up to 17% of variance in attractiveness. Because V1 is adapted to process signals from natural scenes, in general, not faces specifically, our results indicate that attractiveness for female faces is influenced by a visual bias. Sparseness and more generally efficient neural coding are ubiquitous, occurring in various animals and sensory modalities, suggesting that the influence of efficient coding on mate choice can be widespread in animals.

Isoform-specific PKA dynamics revealed by dye-triggered aggregation and DAKAP1alpha-mediated localization in living cells.

PubMed

Martin, Brent R; Deerinck, Thomas J; Ellisman, Mark H; Taylor, Susan S; Tsien, Roger Y

2007-09-01

The tetracysteine sequence YRECCPGCCMWR fused to the N terminus of green fluorescent protein (GFP) self-aggregates upon biarsenical labeling in living cells or in vitro. Such dye-triggered aggregates form temperature-dependent morphologies and are dispersed by photobleaching. Fusion of the biarsenical aggregating GFP to the regulatory (R) or catalytic (C) subunit of PKA traps intact holoenzyme in compact fluorescent puncta upon biarsenical labeling. Contrary to the classical model of PKA activation, elevated cAMP does not allow RIalpha and Calpha to diffuse far apart unless the pseudosubstrate inhibitor PKI or locally concentrated substrate is coexpressed. However, RIIalpha releases Calpha upon elevated cAMP alone, dependent on autophosphorylation of the RIIalpha inhibitory domain. DAKAP1alpha overexpression induced R and C outer mitochondrial colocalization and showed similar regulation. Overall, effective separation of type I PKA is substrate dependent, whereas type II PKA dissociation relies on autophosphorylation.

Introduction to Pesticide Labels

EPA Pesticide Factsheets

Pesticide product labels provide critical information about how to safely and legally handle and use pesticide products. Unlike most other types of product labels, pesticide labels are legally enforceable. Learn about pesticide product labels.

Eye guidance during real-world scene search: The role color plays in central and peripheral vision.

PubMed

Nuthmann, Antje; Malcolm, George L

2016-01-01

The visual system utilizes environmental features to direct gaze efficiently when locating objects. While previous research has isolated various features' contributions to gaze guidance, these studies generally used sparse displays and did not investigate how features facilitated search as a function of their location on the visual field. The current study investigated how features across the visual field--particularly color--facilitate gaze guidance during real-world search. A gaze-contingent window followed participants' eye movements, restricting color information to specified regions. Scene images were presented in full color, with color in the periphery and gray in central vision or gray in the periphery and color in central vision, or in grayscale. Color conditions were crossed with a search cue manipulation, with the target cued either with a word label or an exact picture. Search times increased as color information in the scene decreased. A gaze-data based decomposition of search time revealed color-mediated effects on specific subprocesses of search. Color in peripheral vision facilitated target localization, whereas color in central vision facilitated target verification. Picture cues facilitated search, with the effects of cue specificity and scene color combining additively. When available, the visual system utilizes the environment's color information to facilitate different real-world visual search behaviors based on the location within the visual field.

Parallel iterative methods for sparse linear and nonlinear equations

NASA Technical Reports Server (NTRS)

Saad, Youcef

1989-01-01

As three-dimensional models are gaining importance, iterative methods will become almost mandatory. Among these, preconditioned Krylov subspace methods have been viewed as the most efficient and reliable, when solving linear as well as nonlinear systems of equations. There has been several different approaches taken to adapt iterative methods for supercomputers. Some of these approaches are discussed and the methods that deal more specifically with general unstructured sparse matrices, such as those arising from finite element methods, are emphasized.

Use of DNA barcoding to reveal species composition of convenience seafood.

PubMed

Huxley-Jones, Elizabeth; Shaw, Jennifer L A; Fletcher, Carly; Parnell, Juliette; Watts, Phillip C

2012-04-01

Increased education of consumers can be an effective tool for conservation of commercially harvested marine species when product labeling is accurate and allows an informed choice. However, generic labeling (e.g., as white fish or surimi) and mislabeling of seafood prevents this and may erode consumer confidence in seafood product labels in general. We used DNA barcoding to identify the species composition of two types of convenience seafood (i.e., products processed for ease of consumption): fish fingers (long pieces of fish covered with bread crumbs or batter, n = 241) and seafood sticks (long pieces of cooked fish, n = 30). In products labeled as either white fish or surimi, four teleost species were present. Less than 1.5% of fish fingers with species-specific information were mislabeled. Results of other studies show substantially more mislabeling (e.g., >25%) of teleost products, which likely reflects the lower economic gains associated with mislabeling of convenience seafood compared with whole fillets. In addition to species identification, seafood product labels should be required to contain information about, for example, harvesting practices, and our data indicate that consumers can have reasonable confidence in the accuracy of the labels of convenience seafood and thus select brands on the basis of information about current fisheries practice. ©2012 Society for Conservation Biology.

The science of stem cell biobanking: investing in the future.

PubMed

Diaferia, Giuseppe R; Cardano, Marina; Cattaneo, Monica; Spinelli, Chiara C; Dessì, Sara S; DeBlasio, Pasquale; Biunno, Ida

2012-01-01

The use of human stem cells in biomedical research projects is increasing steadily and the number of cells that are being derived develops at a remarkable pace. However, stem cells around the world are vastly different in their provenance, programming, and potentials. Furthermore, knowledge on the actual number of cell types, their derivation, availability, and characteristics is rather sparse. Usually, "colleague-supply" avenues constantly furnish cells to laboratories around the world without ensuring their correct identity, characterization, and quality. These parameters are critical if the cells will be eventually used in toxicology studies and drug discovery. Here, we outline some basic principles in establishing a stem cell-specific bank. Copyright © 2011 Wiley Periodicals, Inc.

The Global Positioning System (GPS) and attitude determination: Applications and activities in the Flight Dynamics Division

NASA Technical Reports Server (NTRS)

Ketchum, Eleanor; Garrick, Joe

1995-01-01

The application of GPS to spacecraft attitude determination is a new and growing field. Although the theoretical literature is extensive, space flight testing is currently sparse and inadequate. As an operations organization, the Flight Dynamics Division (FDD) has the responsibility to investigate this new technology, and determine how best to implement the innovation to provide adequate support for future missions. This paper presents some of the current efforts within FDD with regard to GPS attitude determination. This effort specifically addresses institutional capabilities to accommodate a new type of sensor, critically evaluating the literature for recent advancements, and in examining some available -albeit crude- flight data.

Vignettes from the field of mathematical biology: the application of mathematics to biology and medicine

PubMed Central

Murray, J. D.

2012-01-01

The application of mathematical models in biology and medicine has a long history. From the sparse number of papers in the first half of the twentieth century with a few scientists working in the field it has become vast with thousands of active researchers. We give a brief, and far from definitive history, of how some parts of the field have developed and how the type of research has changed. We describe in more detail just two examples of specific models which are directly related to real biological problems, namely animal coat patterns and the growth and image enhancement of glioblastoma brain tumours. PMID:23919124

Gold Nanoparticle Labels Amplify Ellipsometric Signals

NASA Technical Reports Server (NTRS)

Venkatasubbarao, Srivatsa

2008-01-01

The ellipsometric method reported in the immediately preceding article was developed in conjunction with a method of using gold nanoparticles as labels on biomolecules that one seeks to detect. The purpose of the labeling is to exploit the optical properties of the gold nanoparticles in order to amplify the measurable ellipsometric effects and thereby to enable ultrasensitive detection of the labeled biomolecules without need to develop more-complex ellipsometric instrumentation. The colorimetric, polarization, light-scattering, and other optical properties of nanoparticles depend on their sizes and shapes. In the present method, these size-and-shape-dependent properties are used to magnify the polarization of scattered light and the diattenuation and retardance of signals derived from ellipsometry. The size-and-shape-dependent optical properties of the nanoparticles make it possible to interrogate the nanoparticles by use of light of various wavelengths, as appropriate, to optimally detect particles of a specific type at high sensitivity. Hence, by incorporating gold nanoparticles bound to biomolecules as primary or secondary labels, the performance of ellipsometry as a means of detecting the biomolecules can be improved. The use of gold nanoparticles as labels in ellipsometry has been found to afford sensitivity that equals or exceeds the sensitivity achieved by use of fluorescence-based methods. Potential applications for ellipsometric detection of gold nanoparticle-labeled biomolecules include monitoring molecules of interest in biological samples, in-vitro diagnostics, process monitoring, general environmental monitoring, and detection of biohazards.

Sparse-sampling with time-encoded (TICO) stimulated Raman scattering for fast image acquisition

NASA Astrophysics Data System (ADS)

Hakert, Hubertus; Eibl, Matthias; Karpf, Sebastian; Huber, Robert

2017-07-01

Modern biomedical imaging modalities aim to provide researchers a multimodal contrast for a deeper insight into a specimen under investigation. A very promising technique is stimulated Raman scattering (SRS) microscopy, which can unveil the chemical composition of a sample with a very high specificity. Although the signal intensities are enhanced manifold to achieve a faster acquisition of images if compared to standard Raman microscopy, there is a trade-off between specificity and acquisition speed. Commonly used SRS concepts either probe only very few Raman transitions as the tuning of the applied laser sources is complicated or record whole spectra with a spectrometer based setup. While the first approach is fast, it reduces the specificity and the spectrometer approach records whole spectra -with energy differences where no Raman information is present-, which limits the acquisition speed. Therefore, we present a new approach based on the TICO-Raman concept, which we call sparse-sampling. The TICO-sparse-sampling setup is fully electronically controllable and allows probing of only the characteristic peaks of a Raman spectrum instead of always acquiring a whole spectrum. By reducing the spectral points to the relevant peaks, the acquisition time can be greatly reduced compared to a uniformly, equidistantly sampled Raman spectrum while the specificity and the signal to noise ratio (SNR) are maintained. Furthermore, all laser sources are completely fiber based. The synchronized detection enables a full resolution of the Raman signal, whereas the analogue and digital balancing allows shot noise limited detection. First imaging results with polystyrene (PS) and polymethylmethacrylate (PMMA) beads confirm the advantages of TICO sparse-sampling. We achieved a pixel dwell time as low as 35 μs for an image differentiating both species. The mechanical properties of the applied voice coil stage for scanning the sample currently limits even faster acquisition.

Oxygen vacancies: The origin of n -type conductivity in ZnO

NASA Astrophysics Data System (ADS)

Liu, Lishu; Mei, Zengxia; Tang, Aihua; Azarov, Alexander; Kuznetsov, Andrej; Xue, Qi-Kun; Du, Xiaolong

2016-06-01

Oxygen vacancy (VO) is a common native point defect that plays crucial roles in determining the physical and chemical properties of metal oxides such as ZnO. However, fundamental understanding of VO is still very sparse. Specifically, whether VO is mainly responsible for the n -type conductivity in ZnO has been still unsettled in the past 50 years. Here, we report on a study of oxygen self-diffusion by conceiving and growing oxygen-isotope ZnO heterostructures with delicately controlled chemical potential and Fermi level. The diffusion process is found to be predominantly mediated by VO. We further demonstrate that, in contrast to the general belief of their neutral attribute, the oxygen vacancies in ZnO are actually +2 charged and thus responsible for the unintentional n -type conductivity as well as the nonstoichiometry of ZnO. The methodology can be extended to study oxygen-related point defects and their energetics in other technologically important oxide materials.

Sparse and Specific Coding during Information Transmission between Co-cultured Dentate Gyrus and CA3 Hippocampal Networks

PubMed Central

Poli, Daniele; Thiagarajan, Srikanth; DeMarse, Thomas B.; Wheeler, Bruce C.; Brewer, Gregory J.

2017-01-01

To better understand encoding and decoding of stimulus information in two specific hippocampal sub-regions, we isolated and co-cultured rat primary dentate gyrus (DG) and CA3 neurons within a two-chamber device with axonal connectivity via micro-tunnels. We tested the hypothesis that, in these engineered networks, decoding performance of stimulus site information would be more accurate when stimuli and information flow occur in anatomically correct feed-forward DG to CA3 vs. CA3 back to DG. In particular, we characterized the neural code of these sub-regions by measuring sparseness and uniqueness of the responses evoked by specific paired-pulse stimuli. We used the evoked responses in CA3 to decode the stimulation sites in DG (and vice-versa) by means of learning algorithms for classification (support vector machine, SVM). The device was placed over an 8 × 8 grid of extracellular electrodes (micro-electrode array, MEA) in order to provide a platform for monitoring development, self-organization, and improved access to stimulation and recording at multiple sites. The micro-tunnels were designed with dimensions 3 × 10 × 400 μm allowing axonal growth but not migration of cell bodies and long enough to exclude traversal by dendrites. Paired-pulse stimulation (inter-pulse interval 50 ms) was applied at 22 different sites and repeated 25 times in each chamber for each sub-region to evoke time-locked activity. DG-DG and CA3-CA3 networks were used as controls. Stimulation in DG drove signals through the axons in the tunnels to activate a relatively small set of specific electrodes in CA3 (sparse code). CA3-CA3 and DG-DG controls were less sparse in coding than CA3 in DG-CA3 networks. Using all target electrodes with the three highest spike rates (14%), the evoked responses in CA3 specified each stimulation site in DG with optimum uniqueness of 64%. Finally, by SVM learning, these evoked responses in CA3 correctly decoded the stimulation sites in DG for 43% of the trials, significantly higher than the reverse, i.e., how well-recording in DG could predict the stimulation site in CA3. In conclusion, our co-cultured model for the in vivo DG-CA3 hippocampal network showed sparse and specific responses in CA3, selectively evoked by each stimulation site in DG. PMID:28321182

Resonance Raman Probes for Organelle-Specific Labeling in Live Cells

NASA Astrophysics Data System (ADS)

Kuzmin, Andrey N.; Pliss, Artem; Lim, Chang-Keun; Heo, Jeongyun; Kim, Sehoon; Rzhevskii, Alexander; Gu, Bobo; Yong, Ken-Tye; Wen, Shangchun; Prasad, Paras N.

2016-06-01

Raman microspectroscopy provides for high-resolution non-invasive molecular analysis of biological samples and has a breakthrough potential for dissection of cellular molecular composition at a single organelle level. However, the potential of Raman microspectroscopy can be fully realized only when novel types of molecular probes distinguishable in the Raman spectroscopy modality are developed for labeling of specific cellular domains to guide spectrochemical spatial imaging. Here we report on the design of a next generation Raman probe, based on BlackBerry Quencher 650 compound, which provides unprecedentedly high signal intensity through the Resonance Raman (RR) enhancement mechanism. Remarkably, RR enhancement occurs with low-toxic red light, which is close to maximum transparency in the biological optical window. The utility of proposed RR probes was validated for targeting lysosomes in live cultured cells, which enabled identification and subsequent monitoring of dynamic changes in this organelle by Raman imaging.

Adapter reagents for protein site specific dye labeling.

PubMed

Thompson, Darren A; Evans, Eric G B; Kasza, Tomas; Millhauser, Glenn L; Dawson, Philip E

2014-05-01

Chemoselective protein labeling remains a significant challenge in chemical biology. Although many selective labeling chemistries have been reported, the practicalities of matching the reaction with appropriately functionalized proteins and labeling reagents is often a challenge. For example, we encountered the challenge of site specifically labeling the cellular form of the murine Prion protein with a fluorescent dye. To facilitate this labeling, a protein was expressed with site specific p-acetylphenylalanine. However, the utility of this acetophenone reactive group is hampered by the severe lack of commercially available aminooxy fluorophores. Here we outline a general strategy for the efficient solid phase synthesis of adapter reagents capable of converting maleimido-labels into aminooxy or azide functional groups that can be further tuned for desired length or solubility properties. The utility of the adapter strategy is demonstrated in the context of fluorescent labeling of the murine Prion protein through an adapted aminooxy-Alexa dye. © 2014 Wiley Periodicals, Inc.

Adapter Reagents for Protein Site Specific Dye Labeling

PubMed Central

Thompson, Darren A.; Evans, Eric G. B.; Kasza, Tomas; Millhauser, Glenn L.; Dawson, Philip E.

2016-01-01

Chemoselective protein labeling remains a significant challenge in chemical biology. Although many selective labeling chemistries have been reported, the practicalities of matching the reaction with appropriately functionalized proteins and labeling reagents is often a challenge. For example, we encountered the challenge of site specifically labeling the cellular form of the murine Prion protein with a fluorescent dye. To facilitate this labeling, a protein was expressed with site specific p-acetylphenylalanine. However, the utility of this aceto-phenone reactive group is hampered by the severe lack of commercially available aminooxy fluorophores. Here we outline a general strategy for the efficient solid phase synthesis of adapter reagents capable of converting maleimido-labels into aminooxy or azide functional groups that can be further tuned for desired length or solubility properties. The utility of the adapter strategy is demonstrated in the context of fluorescent labeling of the murine Prion protein through an adapted aminooxy-Alexa dye. PMID:24599728

Tree edit distance for leaf-labelled trees on free leafset and its comparison with frequent subsplit dissimilarity and popular distance measures

PubMed Central

2011-01-01

Background This paper is devoted to distance measures for leaf-labelled trees on free leafset. A leaf-labelled tree is a data structure which is a special type of a tree where only leaves (terminal) nodes are labelled. This data structure is used in bioinformatics for modelling of evolution history of genes and species and also in linguistics for modelling of languages evolution history. Many domain specific problems occur and need to be solved with help of tree postprocessing techniques such as distance measures. Results Here we introduce the tree edit distance designed for leaf labelled trees on free leafset, which occurs to be a metric. It is presented together with tree edit consensus tree notion. We provide statistical evaluation of provided measure with respect to R-F, MAST and frequent subsplit based dissimilarity measures as the reference measures. Conclusions The tree edit distance was proven to be a metric and has the advantage of using different costs for contraction and pruning, therefore their properties can be tuned depending on the needs of the user. Two of the presented methods carry the most interesting properties. E(3,1) is very discriminative (having a wide range of values) and has a very regular distance distribution which is similar to a normal distribution in its shape and is good both for similar and non-similar trees. NFC(2,1) on the other hand is proportional or nearly proportional to the number of mutation operations used, irrespective of their type. PMID:21612645

Multiple Sparse Representations Classification

PubMed Central

Plenge, Esben; Klein, Stefan S.; Niessen, Wiro J.; Meijering, Erik

2015-01-01

Sparse representations classification (SRC) is a powerful technique for pixelwise classification of images and it is increasingly being used for a wide variety of image analysis tasks. The method uses sparse representation and learned redundant dictionaries to classify image pixels. In this empirical study we propose to further leverage the redundancy of the learned dictionaries to achieve a more accurate classifier. In conventional SRC, each image pixel is associated with a small patch surrounding it. Using these patches, a dictionary is trained for each class in a supervised fashion. Commonly, redundant/overcomplete dictionaries are trained and image patches are sparsely represented by a linear combination of only a few of the dictionary elements. Given a set of trained dictionaries, a new patch is sparse coded using each of them, and subsequently assigned to the class whose dictionary yields the minimum residual energy. We propose a generalization of this scheme. The method, which we call multiple sparse representations classification (mSRC), is based on the observation that an overcomplete, class specific dictionary is capable of generating multiple accurate and independent estimates of a patch belonging to the class. So instead of finding a single sparse representation of a patch for each dictionary, we find multiple, and the corresponding residual energies provides an enhanced statistic which is used to improve classification. We demonstrate the efficacy of mSRC for three example applications: pixelwise classification of texture images, lumen segmentation in carotid artery magnetic resonance imaging (MRI), and bifurcation point detection in carotid artery MRI. We compare our method with conventional SRC, K-nearest neighbor, and support vector machine classifiers. The results show that mSRC outperforms SRC and the other reference methods. In addition, we present an extensive evaluation of the effect of the main mSRC parameters: patch size, dictionary size, and sparsity level. PMID:26177106

Quantifying risk: the role of absolute and relative measures in interpreting risk of adverse reactions from product labels of antipsychotic medications.

PubMed

Citrome, Leslie

2009-09-01

Pharmaceutical product labeling as approved by regulatory agencies include statements of adverse event risk. Product labels include descriptive statements such as whether events are uncommon or rare, as well as percentage occurrence for more common events. In addition tables are provided with the frequencies of the latter events for both product and placebo as observed in clinical trials. Competing products are not mentioned in a specific drug's product labeling but indirect comparisons can be made using the corresponding label information for the alternate product. Two types of tools are easily used for this purpose: absolute measures such as number needed to harm (NNH), and relative measures such as relative risk increase (RRI). The calculations for both of these types of quantitative measures are presented using as examples the oral first-line second-generation antipsychotic medications. Among three sample outcomes selected a priori, akathisia, weight gain, and discontinuation from a clinical trial because of an adverse reaction, there appears to be differences among the different antipsychotics versus placebo. Aripiprazole was associated with the highest risk for akathisia, particularly when used as adjunctive treatment of major depressive disorder (NNH 5, 95% CI 4-7; RRI 525%, 95% CI 267%-964%). Although insufficient information was available in product labeling to calculate the CI, olanzapine was associated with the highest risk for weight gain of at least 7% from baseline (NNH 6, RRI 640% for adults; NNH 4, RRI 314% for adolescents), and quetiapine for the indication of bipolar depression was associated with the highest risk of discontinuation from a clinical trial because of an adverse reaction (NNH 8, RRI 265% for 600 mg/d; NNH 15, RRI 137% for 300 mg/d). In conclusion, with certain limitations, it is possible for the clinician to extract information from medication product labeling regarding the frequency with which certain adverse reactions can be expected. This supplements, but does not replace, information reported directly in clinical trial reports.

Type I interferons for induction of remission in ulcerative colitis.

PubMed

Wang, Yongjun; MacDonald, John K; Benchimol, Eric I; Griffiths, Anne Marie; Steinhart, A Hillary; Panaccione, Remo; Seow, Cynthia H

2015-09-14

Interferons (IFNs) are cytokines which possess immunoregulatory properties and have been used to successfully treat a number of chronic inflammatory disorders. It has been postulated that Type I IFNs may be able to re-establish the Th1/Th2 balance in Th2 predominant diseases like ulcerative colitis. To systematically evaluate the efficacy and safety of type I IFN therapy for induction of remission in ulcerative colitis. We searched MEDLINE, EMBASE, CENTRAL, the Cochrane IBD/FBD group specialised register, and ClinicalTrials.gov from inception to August 8, 2014. Reference lists of trials and review articles, as well as recent proceedings from major gastroenterology meetings were manually searched. Randomised controlled trials of type I IFNs for induction of remission in UC were included. The study population included patients of any age with active ulcerative colitis. There were no exclusions based on type, dose or duration of IFN treatment. Two independent authors reviewed studies for eligibility, extracted the data and assessed study quality using the Cochrane risk of bias tool. The overall quality of the evidence supporting the outcomes was evaluated using the GRADE criteria. The primary outcome was induction of remission of ulcerative colitis. Secondary outcomes included: time to remission, mean change in disease activity index score, clinical, histological or endoscopic improvement, improvement in quality of life, and adverse events. We calculated the risk ratio (RR) and corresponding 95% confidence interval (CI) for dichotomous outcomes. We calculated the mean difference and corresponding 95% confidence interval for continuous outcomes. Meta-analysis was performed using RevMan 5.3.5 software. Six studies were eligible for inclusion (517 patients). Five studies compared type I IFNs to placebo injections (485 patients) and a single study compared IFNs to prednisolone enemas in patients with left-sided colitis (32 patients). The active comparator study was rated as high risk of bias due to an open-label design. Three studies were rated as unclear risk of bias for random sequence generation and allocation concealment. Two studies described as double blind were rated as unclear risk of bias for blinding. There was no significant benefit of type I IFNs over placebo for inducing clinical remission or improvement in patients with active ulcerative colitis. Thirty-six per cent (87/242) of patients in the type I IFNs group achieved clinical remission by 8 to 12 weeks compared to 30% (36/120) of placebo patients (RR 1.16, 95% CI 0.84 to 1.58; 4 studies, 362 patients). A GRADE analysis indicated that the overall quality of the evidence supporting the outcome clinical remission was moderate due to sparse data (123 events). Fifty-six per cent (149/264) of patients in the type I IFNs group improved clinically by 8 to 12 weeks compared to 48% (77/161) of placebo patients (RR 1.16, 95% CI 0.96 to 1.40; 4 studies, 425 patients). A GRADE analysis indicated that the overall quality of the evidence supporting the outcome clinical improvement was moderate due to sparse data (226 events). Patients who received type I IFNs were significantly more likely to withdraw from the studies due to adverse events than those who received placebo. Seven per cent (18/42) of type I IFNs patients withdrew due to adverse events compared to 2% (3/152) of placebo patients (RR 3.16, 95% CI 1.06 to 9.40). A GRADE analysis indicated that the overall quality of the evidence supporting the outcome withdrawal due to adverse events was low due to very sparse data (21 events). The study comparing type I IFNs to prednisolone enemas found no difference between the treatment groups in quality of life or disease activity scores. Common adverse events included headaches, arthralgias, myalgias, fatigue, back pain, nausea, application site reactions, rigors, and fevers. There were no statistically significant differences in the other secondary outcomes. Moderate quality evidence suggests that type I IFNs are not effective for the induction of remission in UC. In addition, there are concerns regarding the tolerability of this class of treatment.

Hydrocortisone Stimulation of RNA Synthesis in Induction of Hepatic Enzymes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kenney, Francis T.; Wicks, Wesley D.; Greenman, David L.

Increased synthesis of hepatic enzymes due to hydrocortisone is preceded by an increase in the rate of synthesis of nuclear RNA. Pulse-labeled RNA from liver nuclei was fractionated by a differential thermal phenol procedures, and the labeled RNA of each fraction was characterized by sucrose gradient centrifugation and base composition analysis. Hormone treatment increases the rate of synthesis of three types of RNA: (1) the nuclear precursor to ribosomal RNA, (2) a rapid turnover component with base composition similar to the tissue DNA, and (3) transfer RNA. Much of the total isotope incorporation into transfer RNA can be traced tomore » turnover of the terminal adenylate residue, but this type of labeling is insensitive to the hormone. The steroid also stimulates isotope incorporation into tissue precursor pools. The effect is abolished by actinomycin and thus is secondary to the hormonal stimulation of RNA synthesis. Growth hormone stimulates RNA synthesis in both intact and adrenalectomized rats, but induces the rapid turnover enzymes (tyrosine transaminase and tryptophan pyrrolase) only in the presence of functional adrenals. It therefore seems that glucocorticoids initiate both a generalized increase in synthesis of RNA and a selective induction of specific enzymes.« less

Evidence for label-retaining tumour-initiating cells in human glioblastoma

PubMed Central

Deleyrolle, Loic P.; Harding, Angus; Cato, Kathleen; Siebzehnrubl, Florian A.; Rahman, Maryam; Azari, Hassan; Olson, Sarah; Gabrielli, Brian; Osborne, Geoffrey; Vescovi, Angelo

2011-01-01

Individual tumour cells display diverse functional behaviours in terms of proliferation rate, cell–cell interactions, metastatic potential and sensitivity to therapy. Moreover, sequencing studies have demonstrated surprising levels of genetic diversity between individual patient tumours of the same type. Tumour heterogeneity presents a significant therapeutic challenge as diverse cell types within a tumour can respond differently to therapies, and inter-patient heterogeneity may prevent the development of general treatments for cancer. One strategy that may help overcome tumour heterogeneity is the identification of tumour sub-populations that drive specific disease pathologies for the development of therapies targeting these clinically relevant sub-populations. Here, we have identified a dye-retaining brain tumour population that displays all the hallmarks of a tumour-initiating sub-population. Using a limiting dilution transplantation assay in immunocompromised mice, label-retaining brain tumour cells display elevated tumour-initiation properties relative to the bulk population. Importantly, tumours generated from these label-retaining cells exhibit all the pathological features of the primary disease. Together, these findings confirm dye-retaining brain tumour cells exhibit tumour-initiation ability and are therefore viable targets for the development of therapeutics targeting this sub-population. PMID:21515906

Comparison of peroxidase-labeled DNA probes with radioactive RNA probes for detection of human papillomaviruses by in situ hybridization in paraffin sections

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, J.S.; Kurman, R.J.; Kessis, T.D.

1991-01-01

A study comparing in situ hybridization using nonradioactive DNA probes directly conjugated with horseradish peroxidase (HRP), and {sup 35}S-labeled antisense RNA probes for human papillomavirus (HPV) types 6/11, 16, and 18 was performed on formalin-fixed, paraffin-embedded tissue from 34 lesions of the cervix and vulva. These lesions included exophytic condylomas and intraepithelial and invasive neoplasms. HPV 6/11 was detected in two of four condylomata acuminata by both in situ techniques. HPV 16 was detected in 13 of 30 cases of intraepithelial and invasive neoplasms by both methods. Discordance between the two methods occurred in two instances. The radiolabeled probe butmore » not the HRP probe detected HPV 16 in one case of cervical intraepithelial neoplasia (CIN 3), whereas the converse occurred in one case of vulvar intraepithelial neoplasia (VIN 3). HPV 18 was not detected in any of the specimens by either method. This study demonstrates that nonradioactive HRP-labeled probes for the detection of specific HPV types are as sensitive as the more laborious and potentially hazardous radioactive probes.« less

Practices in public health finance: an investigation of jurisdiction funding patterns and performance.

PubMed

Honoré, Peggy A; Simoes, Eduardo J; Jones, Walter J; Moonesinghe, Ramal

2004-01-01

A field of study for public health finance has never been adequately developed. Consequently, very little is known about the relationships, types, and amount of finances that fund the public health system in America. This research was undertaken to build on the sparse knowledge of public health finance by examining the value of performance measurement systems to financial analysis. A correlational study was conducted to examine the associations between public health system performance of the 10 essential public health services and funding patterns of 50 local health departments in a large state. The specific objectives were to investigate if different levels and types of revenues, expenditures, and other demographic variables in a jurisdiction are correlated to performance. Pearson correlation analysis did not conclusively show strong associations; however, statistically significant positive associations primarily between higher levels of performance and jurisdiction taxes per capita were found.

Improving M-SBL for Joint Sparse Recovery Using a Subspace Penalty

NASA Astrophysics Data System (ADS)

Ye, Jong Chul; Kim, Jong Min; Bresler, Yoram

2015-12-01

The multiple measurement vector problem (MMV) is a generalization of the compressed sensing problem that addresses the recovery of a set of jointly sparse signal vectors. One of the important contributions of this paper is to reveal that the seemingly least related state-of-art MMV joint sparse recovery algorithms - M-SBL (multiple sparse Bayesian learning) and subspace-based hybrid greedy algorithms - have a very important link. More specifically, we show that replacing the $\\log\\det(\\cdot)$ term in M-SBL by a rank proxy that exploits the spark reduction property discovered in subspace-based joint sparse recovery algorithms, provides significant improvements. In particular, if we use the Schatten-$p$ quasi-norm as the corresponding rank proxy, the global minimiser of the proposed algorithm becomes identical to the true solution as $p \\rightarrow 0$. Furthermore, under the same regularity conditions, we show that the convergence to a local minimiser is guaranteed using an alternating minimization algorithm that has closed form expressions for each of the minimization steps, which are convex. Numerical simulations under a variety of scenarios in terms of SNR, and condition number of the signal amplitude matrix demonstrate that the proposed algorithm consistently outperforms M-SBL and other state-of-the art algorithms.

Probing Protein Structure by Amino Acid-Specific Covalent Labeling and Mass Spectrometry

PubMed Central

Mendoza, Vanessa Leah; Vachet, Richard W.

2009-01-01

For many years, amino acid-specific covalent labeling has been a valuable tool to study protein structure and protein interactions, especially for systems that are difficult to study by other means. These covalent labeling methods typically map protein structure and interactions by measuring the differential reactivity of amino acid side chains. The reactivity of amino acids in proteins generally depends on the accessibility of the side chain to the reagent, the inherent reactivity of the label and the reactivity of the amino acid side chain. Peptide mass mapping with ESI- or MALDI-MS and peptide sequencing with tandem MS are typically employed to identify modification sites to provide site-specific structural information. In this review, we describe the reagents that are most commonly used in these residue-specific modification reactions, details about the proper use of these covalent labeling reagents, and information about the specific biochemical problems that have been addressed with covalent labeling strategies. PMID:19016300

Living on the Edge: A Geometric Theory of Phase Transitions in Convex Optimization

DTIC Science & Technology

2013-03-24

framework for constructing a regularizer f that promotes a specified type of structure, as well as many additional examples. We say that the...Rd that promote the structures we expect to find in x0 8 D. AMELUNXEN, M. LOTZ, M. B. MCCOY, AND J. A. TROPP and y0. Then we can frame the convex...signal x0 is sparse in the standard basis, and the second signal U y0 is sparse in a known basis U . In this case, we can use `1 norms to promote

The neuron identity problem: form meets function.

PubMed

Fishell, Gord; Heintz, Nathaniel

2013-10-30

A complete understanding of nervous system function cannot be achieved without the identification of its component cell types. In this Perspective, we explore a series of related issues surrounding cell identity and how revolutionary methods for labeling and probing specific neuronal types have clarified this question. Specifically, we ask the following questions: what is the purpose of such diversity, how is it generated, how is it maintained, and, ultimately, how can one unambiguously identity one cell type from another? We suggest that each cell type can be defined by a unique and conserved molecular ground state that determines its capabilities. We believe that gaining an understanding of these molecular barcodes will advance our ability to explore brain function, enhance our understanding of the biochemical basis of CNS disorders, and aid in the development of novel therapeutic strategies. Copyright © 2013 Elsevier Inc. All rights reserved.

Chemotherapeutic Effect of CD147 Antibody-labeled Micelles Encapsulating Doxorubicin Conjugate Targeting CD147-Expressing Carcinoma Cells.

PubMed

Asakura, Tadashi; Yokoyama, Masayuki; Shiraishi, Koichi; Aoki, Katsuhiko; Ohkawa, Kiyoshi

2018-03-01

CD147 (basigin/emmprin) is expressed on the surface of carcinoma cells. For studying the efficacy of CD147-targeting medicine on CD147-expressing cells, we studied the effect of anti-CD147-labeled polymeric micelles (CD147ab micelles) that encapsulated a conjugate of doxorubicin with glutathione (GSH-DXR), with specific accumulation and cytotoxicity against CD147-expressing A431 human epidermoid carcinoma cells, Ishikawa human endometrial adenocarcinoma cells, and PC3 human prostate carcinoma cells. By treatment of each cell type with CD147ab micelles for 1 h, a specific accumulation of CD147ab micelles in CD147-expressing cells was observed. In addition, the cytotoxicity of GSH-DXR-encapsulated micelles against each cell type was measured by treatment of the micelles for 1 h. The cytotoxic effect of CD147ab micelles carrying GSH-DXR was 3- to 10-fold higher for these cells than that of micelles without GSH-DXR. These results suggest that GSH-DXR-encapsulated CD147ab micelles could serve as an effective drug delivery system to CD147-expressing carcinoma cells. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Discovering cell types in flow cytometry data with random matrix theory

NASA Astrophysics Data System (ADS)

Shen, Yang; Nussenblatt, Robert; Losert, Wolfgang

Flow cytometry is a widely used experimental technique in immunology research. During the experiments, peripheral blood mononuclear cells (PBMC) from a single patient, labeled with multiple fluorescent stains that bind to different proteins, are illuminated by a laser. The intensity of each stain on a single cell is recorded and reflects the amount of protein expressed by that cell. The data analysis focuses on identifying specific cell types related to a disease. Different cell types can be identified by the type and amount of protein they express. To date, this has most often been done manually by labelling a protein as expressed or not while ignoring the amount of expression. Using a cross correlation matrix of stain intensities, which contains both information on the proteins expressed and their amount, has been largely ignored by researchers as it suffers from measurement noise. Here we present an algorithm to identify cell types in flow cytometry data which uses random matrix theory (RMT) to reduce noise in a cross correlation matrix. We demonstrate our method using a published flow cytometry data set. Compared with previous analysis techniques, we were able to rediscover relevant cell types in an automatic way. Department of Physics, University of Maryland, College Park, MD 20742.

Fast sparsely synchronized brain rhythms in a scale-free neural network.

PubMed

Kim, Sang-Yoon; Lim, Woochang

2015-08-01

We consider a directed version of the Barabási-Albert scale-free network model with symmetric preferential attachment with the same in- and out-degrees and study the emergence of sparsely synchronized rhythms for a fixed attachment degree in an inhibitory population of fast-spiking Izhikevich interneurons. Fast sparsely synchronized rhythms with stochastic and intermittent neuronal discharges are found to appear for large values of J (synaptic inhibition strength) and D (noise intensity). For an intensive study we fix J at a sufficiently large value and investigate the population states by increasing D. For small D, full synchronization with the same population-rhythm frequency fp and mean firing rate (MFR) fi of individual neurons occurs, while for large D partial synchronization with fp>〈fi〉 (〈fi〉: ensemble-averaged MFR) appears due to intermittent discharge of individual neurons; in particular, the case of fp>4〈fi〉 is referred to as sparse synchronization. For the case of partial and sparse synchronization, MFRs of individual neurons vary depending on their degrees. As D passes a critical value D* (which is determined by employing an order parameter), a transition to unsynchronization occurs due to the destructive role of noise to spoil the pacing between sparse spikes. For D

Sparse Feature Selection Identifies H2A.Z as a Novel, Pattern-Specific Biomarker for Asymmetrically Self-Renewing Distributed Stem Cells

PubMed Central

Huh, Yang Hoon; Noh, Minsoo; Burden, Frank R.; Chen, Jennifer C.; Winkler, David A.; Sherley, James L.

2015-01-01

There is a long-standing unmet clinical need for biomarkers with high specificity for distributed stem cells (DSCs) in tissues, or for use in diagnostic and therapeutic cell preparations (e.g., bone marrow). Although DSCs are essential for tissue maintenance and repair, accurate determination of their numbers for medical applications has been problematic. Previous searches for biomarkers expressed specifically in DSCs were hampered by difficulty obtaining pure DSCs and by the challenges in mining complex molecular expression data. To identify DSC such useful and specific biomarkers, we combined a novel sparse feature selection method with combinatorial molecular expression data focused on asymmetric self-renewal, a conspicuous property of DSCs. The analysis identified reduced expression of the histone H2A variant H2A.Z as a superior molecular discriminator for DSC asymmetric self-renewal. Subsequent molecular expression studies showed H2A.Z to be a novel “pattern-specific biomarker” for asymmetrically self-renewing cells with sufficient specificity to count asymmetrically self-renewing DSCs in vitro and potentially in situ. PMID:25636161

Tandem mass spectrometry of isomeric aniline-labeled N-glycans separated on porous graphitic carbon: Revealing the attachment position of terminal sialic acids and structures of neutral glycans.

PubMed

Michael, Claudia; Rizzi, Andreas M

2015-07-15

Quantitative monitoring of changes in the N-glycome upon disease has gained significance in the context of biomarker discovery. Separation and quantification of isobaric glycan isomers can be attained by using high-performance liquid chromatography/electrospray ionization mass spectrometry (HPLC/ESI-MS). Collision-induced dissociation (CID)-based fragmentation of separated isobaric glycans is evaluated in respect to its potential of providing fragment ions specific for the linkage positions of terminal sialic acids and the presence of intersecting GlcNAc moieties, respectively. N-Glycans were labeled via reductive amination using (12)C6-aniline and (13)C6-aniline as isotope-coded labeling reagents. The differently labeled glycans were merged and separated into various species using a porous graphitic carbon (PGC) stationary phase. Identification of structural features of separated isobaric isomers was performed by CID-based tandem mass spectrometry (MS/MS) carried out in a quadrupole time-of-flight (QqTOF) or a quadrupole ion-trap (IT) mass spectrometer. Working in the negative ion mode, new diagnostic CID fragment ions could be found that are indicative for the α2,6-type linkage of sialic acids. Other diagnostic ions, identified before as being indicative for the substitution of the 6-antenna, could be confirmed as being of relevance also in the case of aniline labeling. In the positive ion mode, CID fragment ions indicative for the structure of short neutral N-glycans were identified. One new diagnostic ion specific for the linkage position of the terminal sialic acids and one for the presence of bisecting GlcNAc in N-glycans were identified. The aniline label introduced for improved relative quantitation in MS(1) was found not to significantly alter the CID fragmentation patterns that were reported previously by other authors for unlabeled/reduced glycans or for glycans with more polar labels. Copyright © 2015 John Wiley & Sons, Ltd.

Brain tumor segmentation from multimodal magnetic resonance images via sparse representation.

PubMed

Li, Yuhong; Jia, Fucang; Qin, Jing

2016-10-01

Accurately segmenting and quantifying brain gliomas from magnetic resonance (MR) images remains a challenging task because of the large spatial and structural variability among brain tumors. To develop a fully automatic and accurate brain tumor segmentation algorithm, we present a probabilistic model of multimodal MR brain tumor segmentation. This model combines sparse representation and the Markov random field (MRF) to solve the spatial and structural variability problem. We formulate the tumor segmentation problem as a multi-classification task by labeling each voxel as the maximum posterior probability. We estimate the maximum a posteriori (MAP) probability by introducing the sparse representation into a likelihood probability and a MRF into the prior probability. Considering the MAP as an NP-hard problem, we convert the maximum posterior probability estimation into a minimum energy optimization problem and employ graph cuts to find the solution to the MAP estimation. Our method is evaluated using the Brain Tumor Segmentation Challenge 2013 database (BRATS 2013) and obtained Dice coefficient metric values of 0.85, 0.75, and 0.69 on the high-grade Challenge data set, 0.73, 0.56, and 0.54 on the high-grade Challenge LeaderBoard data set, and 0.84, 0.54, and 0.57 on the low-grade Challenge data set for the complete, core, and enhancing regions. The experimental results show that the proposed algorithm is valid and ranks 2nd compared with the state-of-the-art tumor segmentation algorithms in the MICCAI BRATS 2013 challenge. Copyright © 2016 Elsevier B.V. All rights reserved.

Automated detection of feeding strikes by larval fish using continuous high-speed digital video: a novel method to extract quantitative data from fast, sparse kinematic events.

PubMed

Shamur, Eyal; Zilka, Miri; Hassner, Tal; China, Victor; Liberzon, Alex; Holzman, Roi

2016-06-01

Using videography to extract quantitative data on animal movement and kinematics constitutes a major tool in biomechanics and behavioral ecology. Advanced recording technologies now enable acquisition of long video sequences encompassing sparse and unpredictable events. Although such events may be ecologically important, analysis of sparse data can be extremely time-consuming and potentially biased; data quality is often strongly dependent on the training level of the observer and subject to contamination by observer-dependent biases. These constraints often limit our ability to study animal performance and fitness. Using long videos of foraging fish larvae, we provide a framework for the automated detection of prey acquisition strikes, a behavior that is infrequent yet critical for larval survival. We compared the performance of four video descriptors and their combinations against manually identified feeding events. For our data, the best single descriptor provided a classification accuracy of 77-95% and detection accuracy of 88-98%, depending on fish species and size. Using a combination of descriptors improved the accuracy of classification by ∼2%, but did not improve detection accuracy. Our results indicate that the effort required by an expert to manually label videos can be greatly reduced to examining only the potential feeding detections in order to filter false detections. Thus, using automated descriptors reduces the amount of manual work needed to identify events of interest from weeks to hours, enabling the assembly of an unbiased large dataset of ecologically relevant behaviors. © 2016. Published by The Company of Biologists Ltd.

EHR-based phenotyping: Bulk learning and evaluation.

PubMed

Chiu, Po-Hsiang; Hripcsak, George

2017-06-01

In data-driven phenotyping, a core computational task is to identify medical concepts and their variations from sources of electronic health records (EHR) to stratify phenotypic cohorts. A conventional analytic framework for phenotyping largely uses a manual knowledge engineering approach or a supervised learning approach where clinical cases are represented by variables encompassing diagnoses, medicinal treatments and laboratory tests, among others. In such a framework, tasks associated with feature engineering and data annotation remain a tedious and expensive exercise, resulting in poor scalability. In addition, certain clinical conditions, such as those that are rare and acute in nature, may never accumulate sufficient data over time, which poses a challenge to establishing accurate and informative statistical models. In this paper, we use infectious diseases as the domain of study to demonstrate a hierarchical learning method based on ensemble learning that attempts to address these issues through feature abstraction. We use a sparse annotation set to train and evaluate many phenotypes at once, which we call bulk learning. In this batch-phenotyping framework, disease cohort definitions can be learned from within the abstract feature space established by using multiple diseases as a substrate and diagnostic codes as surrogates. In particular, using surrogate labels for model training renders possible its subsequent evaluation using only a sparse annotated sample. Moreover, statistical models can be trained and evaluated, using the same sparse annotation, from within the abstract feature space of low dimensionality that encapsulates the shared clinical traits of these target diseases, collectively referred to as the bulk learning set. Copyright © 2017 Elsevier Inc. All rights reserved.

Using mass spectrometry to study the photo-affinity labeling of protein tyrosine phosphatase 1B

NASA Astrophysics Data System (ADS)

Leriche, Tammy; Skorey, Kathryn; Roy, Patrick; McKay, Dan; Bateman, Kevin P.

2004-11-01

Protein tyrosine phosphatase 1B (PTP1B) is a potential target for the treatment of Type II diabetes and several companies are developing small molecule inhibitors of this enzyme. Part of the characterization of these compounds as PTP1B inhibitors is the understanding of how they bind in the enzyme active site. The use of photo-activated inhibitors that target the active site can provide such insight. This paper describes the characterization of a photoprobe directed at the active site of PTP1B. Mass spectrometry revealed the specific binding of the probe to the intact protein. Digestion of the labeled protein followed by LC-MS and LC-MS/MS was used to show that the photoprobe binds to a specific active site amino acid. This was confirmed by comparison with the X-ray structure of PTP1B with a PTP1B inhibitor. The probe labels a conserved acidic residue (Asp) that is required for catalytic activity. This photoprobe may prove to be a useful tool for the development of a PTP1B inhibitor or for the study of PTPs in general.

Axon collaterals projection from nucleus reticularis tegmenti pontis onto the cerebellar paramedian lobule in the rabbit: a fluorescent double labelling study.

PubMed

Mierzejewska-Krzyzowska, B

1999-01-01

Double labelling method with retrograde transport of fluorescent tracers (Fast Blue; FB and Diamidino Yellow; DY) was employed in the rabbit to investigate whether neurones of the nucleus reticularis tegmenti pontis (NRTP) give off axon collaterals to the cerebellar paramedian lobule (PML) of both sides. Following injections to various regions of the homotopic or heterotopic sublobules of the left (FB) and right (DY) PML cortex, distribution of double labelled neurones within NRTP was analyzed. NRTP of the rabbit consists of a medial principal part (the nucleus papillioformis: PLF) and smaller lateral part (the processus tegmentosus lateralis: PTL). Within PLF three subdivisions are to be distinguished: the dorsomedial part -- zone A, the main part -- zone B and the ventrolateral part -- zone C. The present study in the rabbit indicated collateral projections from neurones in some NRTP regions to the both PML. The cells of origin of these projections were located prominently through the rostrocaudal extent of zone B. Projections from zone A were sparse and those from zone C were absent. Moreover, a weak projection arose mainly from the caudal aspect of PTL. It is concluded that the rostral (e and f) and middle (c and d) sublobules are the main targets for the NRTP-PML branching projections.

Cell-selective metabolic labeling of biomolecules with bioorthogonal functionalities.

PubMed

Xie, Ran; Hong, Senlian; Chen, Xing

2013-10-01

Metabolic labeling of biomolecules with bioorthogonal functionalities enables visualization, enrichment, and analysis of the biomolecules of interest in their physiological environments. This versatile strategy has found utility in probing various classes of biomolecules in a broad range of biological processes. On the other hand, metabolic labeling is nonselective with respect to cell type, which imposes limitations for studies performed in complex biological systems. Herein, we review the recent methodological developments aiming to endow metabolic labeling strategies with cell-type selectivity. The cell-selective metabolic labeling strategies have emerged from protein and glycan labeling. We envision that these strategies can be readily extended to labeling of other classes of biomolecules. Copyright © 2013 Elsevier Ltd. All rights reserved.

Characterizing and differentiating task-based and resting state fMRI signals via two-stage sparse representations.

PubMed

Zhang, Shu; Li, Xiang; Lv, Jinglei; Jiang, Xi; Guo, Lei; Liu, Tianming

2016-03-01

A relatively underexplored question in fMRI is whether there are intrinsic differences in terms of signal composition patterns that can effectively characterize and differentiate task-based or resting state fMRI (tfMRI or rsfMRI) signals. In this paper, we propose a novel two-stage sparse representation framework to examine the fundamental difference between tfMRI and rsfMRI signals. Specifically, in the first stage, the whole-brain tfMRI or rsfMRI signals of each subject were composed into a big data matrix, which was then factorized into a subject-specific dictionary matrix and a weight coefficient matrix for sparse representation. In the second stage, all of the dictionary matrices from both tfMRI/rsfMRI data across multiple subjects were composed into another big data-matrix, which was further sparsely represented by a cross-subjects common dictionary and a weight matrix. This framework has been applied on the recently publicly released Human Connectome Project (HCP) fMRI data and experimental results revealed that there are distinctive and descriptive atoms in the cross-subjects common dictionary that can effectively characterize and differentiate tfMRI and rsfMRI signals, achieving 100% classification accuracy. Moreover, our methods and results can be meaningfully interpreted, e.g., the well-known default mode network (DMN) activities can be recovered from the very noisy and heterogeneous aggregated big-data of tfMRI and rsfMRI signals across all subjects in HCP Q1 release.

Parents' meal choices for their children at fast food and family restaurants with different menu labeling presentations.

PubMed

Lee, Kiwon; Lee, Youngmi

2018-06-01

This study examined the effect of nutrition labeling formats on parents' food choices for their children at different restaurant types. An online survey was conducted with 1,980 parents of children aged 3-12 years. Participants were randomly assigned to fast food or family restaurant scenarios, and one of four menu stimuli conditions: no labeling, low-calorie symbol (symbol), numeric value (numeric), and both low-calorie symbol and numeric value (symbol + numeric). Participants selected menu items for their children. Menu choices and total calories were compared by nutrition labeling formats in each type of the restaurant. Low-calorie item selections were scored and a two-way analysis of variance (ANOVA) was conducted for an interaction effect between restaurant and labeling type. In the fast food restaurant group, parents presented with low-calorie symbols selected the lowest calorie items more often than those not presented with the format. Parents in the symbol + numeric condition selected significantly fewer calories (653 kcal) than those in the no labeling (677 kcal) or numeric conditions (674 kcal) ( P = 0.006). In the family restaurant group, no significant difference were observed among different labeling conditions. A significant interaction between restaurant and labeling type on low-calorie selection score (F = 6.03, P < 0.01) suggests that the effect of nutrition labeling format interplays with restaurant type to jointly affect parents' food choices for their children. The provision of easily interpretable nutritional information format at fast food restaurants may encourage healthier food choices of parents for their children; however, the effects were negligible at family restaurants.

Electrical tuning and transduction in short hair cells of the chicken auditory papilla.

PubMed

Tan, Xiaodong; Beurg, Maryline; Hackney, Carole; Mahendrasingam, Shanthini; Fettiplace, Robert

2013-04-01

The avian auditory papilla contains two classes of sensory receptor, tall hair cells (THCs) and short hair cells (SHCs), the latter analogous to mammalian outer hair cells with large efferent but sparse afferent innervation. Little is known about the tuning, transduction, or electrical properties of SHCs. To address this problem, we made patch-clamp recordings from hair cells in an isolated chicken basilar papilla preparation at 33°C. We found that SHCs are electrically tuned by a Ca(2+)-activated K(+) current, their resonant frequency varying along the papilla in tandem with that of the THCs, which also exhibit electrical tuning. The tonotopic map for THCs was similar to maps previously described from auditory nerve fiber measurements. SHCs also possess an A-type K(+) current, but electrical tuning was observed only at resting potentials positive to -45 mV, where the A current is inactivated. We predict that the resting potential in vivo is approximately -40 mV, depolarized by a standing inward current through mechanotransducer (MT) channels having a resting open probability of ∼0.26. The resting open probability stems from a low endolymphatic Ca(2+) concentration (0.24 mM) and a high intracellular mobile Ca(2+) buffer concentration, estimated from perforated-patch recordings as equivalent to 0.5 mM BAPTA. The high buffer concentration was confirmed by quantifying parvalbumin-3 and calbindin D-28K with calibrated postembedding immunogold labeling, demonstrating >1 mM calcium-binding sites. Both proteins displayed an apex-to-base gradient matching that in the MT current amplitude, which increased exponentially along the papilla. Stereociliary bundles also labeled heavily with antibodies against the Ca(2+) pump isoform PMCA2a.

Memory for product sounds: the effect of sound and label type.

PubMed

Ozcan, Elif; van Egmond, René

2007-11-01

The (mnemonic) interactions between auditory, visual, and the semantic systems have been investigated using structurally complex auditory stimuli (i.e., product sounds). Six types of product sounds (air, alarm, cyclic, impact, liquid, mechanical) that vary in spectral-temporal structure were presented in four label type conditions: self-generated text, text, image, and pictogram. A memory paradigm that incorporated free recall, recognition, and matching tasks was employed. The results for the sound type suggest that the amount of spectral-temporal structure in a sound can be indicative for memory performance. Findings related to label type suggest that 'self' creates a strong bias for the retrieval and the recognition of sounds that were self-labeled; the density and the complexity of the visual information (i.e., pictograms) hinders the memory performance ('visual' overshadowing effect); and image labeling has an additive effect on the recall and matching tasks (dual coding). Thus, the findings suggest that the memory performances for product sounds are task-dependent.

Bacterial Production of Site Specific 13C Labeled Phenylalanine and Methodology for High Level Incorporation into Bacterially Expressed Recombinant Proteins

PubMed Central

Ramaraju, Bhargavi; McFeeters, Hana; Vogler, Bernhard; McFeeters, Robert L.

2016-01-01

Nuclear magnetic resonance spectroscopy studies of ever larger systems have benefited from many different forms of isotope labeling, in particular, site specific isotopic labeling. Site specific 13C labeling of methyl groups has become an established means of probing systems not amenable to traditional methodology. However useful, methyl reporter sites can be limited in number and/or location. Therefore, new complementary site specific isotope labeling strategies are valuable. Aromatic amino acids make excellent probes since they are often found at important interaction interfaces and play significant structural roles. Aromatic side chains have many of the same advantages as methyl containing amino acids including distinct 13C chemical shifts and multiple magnetically equivalent 1H positions. Herein we report economical bacterial production and one-step purification of phenylalanine with 13C incorporation at the Cα, Cγ and Cε positions, resulting in two isolated 1H-13C spin systems. We also present methodology to maximize incorporation of phenylalanine into recombinantly overexpressed proteins in bacteria and demonstrate compatibility with ILV-methyl labeling. Inexpensive, site specific isotope labeled phenylalanine adds another dimension to biomolecular NMR, opening new avenues of study. PMID:28028744

Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries

DOE PAGES

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; ...

2014-12-09

We present results from an ongoing effort to extend neuromimetic machine vision algorithms to multispectral data using adaptive signal processing combined with compressive sensing and machine learning techniques. Our goal is to develop a robust classification methodology that will allow for automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties, and topographic/geomorphic characteristics. We use a Hebbian learning rule to build spectral-textural dictionaries that are tailored for classification. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labelsmore » are automatically generated using unsupervised clustering of sparse approximations (CoSA). We demonstrate our method on multispectral WorldView-2 data from a coastal plain ecosystem in Barrow, Alaska. We explore learning from both raw multispectral imagery and normalized band difference indices. We explore a quantitative metric to evaluate the spectral properties of the clusters in order to potentially aid in assigning land cover categories to the cluster labels. In this study, our results suggest CoSA is a promising approach to unsupervised land cover classification in high-resolution satellite imagery.« less

Automatic thoracic anatomy segmentation on CT images using hierarchical fuzzy models and registration

NASA Astrophysics Data System (ADS)

Sun, Kaioqiong; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Torigian, Drew A.

2014-03-01

This paper proposes a thoracic anatomy segmentation method based on hierarchical recognition and delineation guided by a built fuzzy model. Labeled binary samples for each organ are registered and aligned into a 3D fuzzy set representing the fuzzy shape model for the organ. The gray intensity distributions of the corresponding regions of the organ in the original image are recorded in the model. The hierarchical relation and mean location relation between different organs are also captured in the model. Following the hierarchical structure and location relation, the fuzzy shape model of different organs is registered to the given target image to achieve object recognition. A fuzzy connected delineation method is then used to obtain the final segmentation result of organs with seed points provided by recognition. The hierarchical structure and location relation integrated in the model provide the initial parameters for registration and make the recognition efficient and robust. The 3D fuzzy model combined with hierarchical affine registration ensures that accurate recognition can be obtained for both non-sparse and sparse organs. The results on real images are presented and shown to be better than a recently reported fuzzy model-based anatomy recognition strategy.

Microtiter format for simultaneous multianalyte detection and development of a PCR-chemiluminescent enzyme immunoassay for typing human papillomavirus DNAs.

PubMed

Roda, Aldo; Mirasoli, Mara; Venturoli, Simona; Cricca, Monica; Bonvicini, Francesca; Baraldini, Mario; Pasini, Patrizia; Zerbini, Marialuisa; Musiani, Monica

2002-10-01

To allow multianalyte binding assays, we have developed a novel polystyrene microtiter plate containing 24 main wells, each divided into 7 subwells. We explored its clinical potential by developing a PCR-chemiluminescent immunoassay (PCR-CLEIA) for simultaneous detection and typing of seven high oncogenic risk human papillomavirus (HPV) DNAs in one well. Seven different oligonucleotide probes, each specific for a high-risk HPV genotype, were separately immobilized in the subwells. Subsequently, a digoxigenin-labeled consensus PCR amplification product was added to the main well. The PCR product hybridized to the immobilized probe corresponding to its genotype and was subsequently detected by use of a peroxidase-labeled anti-digoxigenin antibody and chemiluminescence imaging with an ultrasensitive charge-coupled device camera. Results obtained for 50 cytologic samples were compared with those obtained with a conventional colorimetric PCR-ELISA. The method was specific and allowed detection of 50 genome copies of HPV 16, 18, 33, and 58, and 100 genome copies of HPV 31, 35, and 45. Intra- and interassay CVs for the method were 5.6% and 7.9%, respectively. All results obtained for clinical samples were confirmed by the conventional PCR-ELISA. PCR-CLEIA allows rapid, single-tube simultaneous detection and typing of seven high-risk HPV DNAs with small reagent volumes. The principle appears applicable to the development of other single-tube panels of tests.

A structured sparse regression method for estimating isoform expression level from multi-sample RNA-seq data.

PubMed

Zhang, L; Liu, X J

2016-06-03

With the rapid development of next-generation high-throughput sequencing technology, RNA-seq has become a standard and important technique for transcriptome analysis. For multi-sample RNA-seq data, the existing expression estimation methods usually deal with each single-RNA-seq sample, and ignore that the read distributions are consistent across multiple samples. In the current study, we propose a structured sparse regression method, SSRSeq, to estimate isoform expression using multi-sample RNA-seq data. SSRSeq uses a non-parameter model to capture the general tendency of non-uniformity read distribution for all genes across multiple samples. Additionally, our method adds a structured sparse regularization, which not only incorporates the sparse specificity between a gene and its corresponding isoform expression levels, but also reduces the effects of noisy reads, especially for lowly expressed genes and isoforms. Four real datasets were used to evaluate our method on isoform expression estimation. Compared with other popular methods, SSRSeq reduced the variance between multiple samples, and produced more accurate isoform expression estimations, and thus more meaningful biological interpretations.

Perceptually controlled doping for audio source separation

NASA Astrophysics Data System (ADS)

Mahé, Gaël; Nadalin, Everton Z.; Suyama, Ricardo; Romano, João MT

2014-12-01

The separation of an underdetermined audio mixture can be performed through sparse component analysis (SCA) that relies however on the strong hypothesis that source signals are sparse in some domain. To overcome this difficulty in the case where the original sources are available before the mixing process, the informed source separation (ISS) embeds in the mixture a watermark, which information can help a further separation. Though powerful, this technique is generally specific to a particular mixing setup and may be compromised by an additional bitrate compression stage. Thus, instead of watermarking, we propose a `doping' method that makes the time-frequency representation of each source more sparse, while preserving its audio quality. This method is based on an iterative decrease of the distance between the distribution of the signal and a target sparse distribution, under a perceptual constraint. We aim to show that the proposed approach is robust to audio coding and that the use of the sparsified signals improves the source separation, in comparison with the original sources. In this work, the analysis is made only in instantaneous mixtures and focused on voice sources.

Two-dimensional sparse wavenumber recovery for guided wavefields

NASA Astrophysics Data System (ADS)

Sabeti, Soroosh; Harley, Joel B.

2018-04-01

The multi-modal and dispersive behavior of guided waves is often characterized by their dispersion curves, which describe their frequency-wavenumber behavior. In prior work, compressive sensing based techniques, such as sparse wavenumber analysis (SWA), have been capable of recovering dispersion curves from limited data samples. A major limitation of SWA, however, is the assumption that the structure is isotropic. As a result, SWA fails when applied to composites and other anisotropic structures. There have been efforts to address this issue in the literature, but they either are not easily generalizable or do not sufficiently express the data. In this paper, we enhance the existing approaches by employing a two-dimensional wavenumber model to account for direction-dependent velocities in anisotropic media. We integrate this model with tools from compressive sensing to reconstruct a wavefield from incomplete data. Specifically, we create a modified two-dimensional orthogonal matching pursuit algorithm that takes an undersampled wavefield image, with specified unknown elements, and determines its sparse wavenumber characteristics. We then recover the entire wavefield from the sparse representations obtained with our small number of data samples.

On-Chip Neural Data Compression Based On Compressed Sensing With Sparse Sensing Matrices.

PubMed

Zhao, Wenfeng; Sun, Biao; Wu, Tong; Yang, Zhi

2018-02-01

On-chip neural data compression is an enabling technique for wireless neural interfaces that suffer from insufficient bandwidth and power budgets to transmit the raw data. The data compression algorithm and its implementation should be power and area efficient and functionally reliable over different datasets. Compressed sensing is an emerging technique that has been applied to compress various neurophysiological data. However, the state-of-the-art compressed sensing (CS) encoders leverage random but dense binary measurement matrices, which incur substantial implementation costs on both power and area that could offset the benefits from the reduced wireless data rate. In this paper, we propose two CS encoder designs based on sparse measurement matrices that could lead to efficient hardware implementation. Specifically, two different approaches for the construction of sparse measurement matrices, i.e., the deterministic quasi-cyclic array code (QCAC) matrix and -sparse random binary matrix [-SRBM] are exploited. We demonstrate that the proposed CS encoders lead to comparable recovery performance. And efficient VLSI architecture designs are proposed for QCAC-CS and -SRBM encoders with reduced area and total power consumption.

SPReM: Sparse Projection Regression Model For High-dimensional Linear Regression *

PubMed Central

Sun, Qiang; Zhu, Hongtu; Liu, Yufeng; Ibrahim, Joseph G.

2014-01-01

The aim of this paper is to develop a sparse projection regression modeling (SPReM) framework to perform multivariate regression modeling with a large number of responses and a multivariate covariate of interest. We propose two novel heritability ratios to simultaneously perform dimension reduction, response selection, estimation, and testing, while explicitly accounting for correlations among multivariate responses. Our SPReM is devised to specifically address the low statistical power issue of many standard statistical approaches, such as the Hotelling’s T2 test statistic or a mass univariate analysis, for high-dimensional data. We formulate the estimation problem of SPREM as a novel sparse unit rank projection (SURP) problem and propose a fast optimization algorithm for SURP. Furthermore, we extend SURP to the sparse multi-rank projection (SMURP) by adopting a sequential SURP approximation. Theoretically, we have systematically investigated the convergence properties of SURP and the convergence rate of SURP estimates. Our simulation results and real data analysis have shown that SPReM out-performs other state-of-the-art methods. PMID:26527844

Interaction of tachykinins with their receptors studied with cyclic analogues of substance P and neurokinin B

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ploux, O.; Lavielle, S.; Chassaing, G.

1987-11-01

The activities of two groups of cyclic agonists of substance P (SP) have been studied. The disulfide bridge constraints have been designed on the basis of conformational studies on SP and physalaemin indicating an ..cap alpha..-helical structure for the core of these two tachykinins (group I) and a folding of the C-terminal carboxamide towards the side chains of the glutamines 5 and 6 (group II). Only peptides simulating the ..cap alpha..-helix present substantial potencies. (Cys/sup 3,6/)SP is as active as SP in inhibiting /sup 125/I-labeled Bolton and Hunter SP-specific binding on rat brain synaptosomes and on dog carotid bioassay, twomore » assays specific for the neurokinin 1 receptor. Moreover, (Cys/sup 3,6/)SP is a potent as neurokinin B in inhibiting /sup 125/I-labeled Bolton and Hunter eledoisin-specific binding on rat cortical synaptosomes as well as in stimulating rat portal vein, two tests specific for the neurokinin 3 receptor. Interestingly, in contrast to neurokinin B, (Cys/sup 3,6/)SP is a weak agonist of the neurokinin 2 receptor subtype, as evidenced by its binding potency in inhibiting /sup 3/H-labeled neurokinin A-specific binding on rat duodenum and in inducing the contractions of the rabbit pulmonary artery, a neurokinin 2-type bioassay. To increase the specificity of the cyclic analogue (Cys/sup 3,6/)SP positions 8 and 9 were modified. Collectively, these results suggest that the neurokinin 1 and neurokinin 3 tachykinin receptors may recognize a similar three-dimensional structure of the core of the tachykinins. Different orientations of the common C-terminal tripeptide may be related to the selectivity for the different receptor subtypes.« less

Automated annotation of functional imaging experiments via multi-label classification

PubMed Central

Turner, Matthew D.; Chakrabarti, Chayan; Jones, Thomas B.; Xu, Jiawei F.; Fox, Peter T.; Luger, George F.; Laird, Angela R.; Turner, Jessica A.

2013-01-01

Identifying the experimental methods in human neuroimaging papers is important for grouping meaningfully similar experiments for meta-analyses. Currently, this can only be done by human readers. We present the performance of common machine learning (text mining) methods applied to the problem of automatically classifying or labeling this literature. Labeling terms are from the Cognitive Paradigm Ontology (CogPO), the text corpora are abstracts of published functional neuroimaging papers, and the methods use the performance of a human expert as training data. We aim to replicate the expert's annotation of multiple labels per abstract identifying the experimental stimuli, cognitive paradigms, response types, and other relevant dimensions of the experiments. We use several standard machine learning methods: naive Bayes (NB), k-nearest neighbor, and support vector machines (specifically SMO or sequential minimal optimization). Exact match performance ranged from only 15% in the worst cases to 78% in the best cases. NB methods combined with binary relevance transformations performed strongly and were robust to overfitting. This collection of results demonstrates what can be achieved with off-the-shelf software components and little to no pre-processing of raw text. PMID:24409112

Completing sparse and disconnected protein-protein network by deep learning.

PubMed

Huang, Lei; Liao, Li; Wu, Cathy H

2018-03-22

Protein-protein interaction (PPI) prediction remains a central task in systems biology to achieve a better and holistic understanding of cellular and intracellular processes. Recently, an increasing number of computational methods have shifted from pair-wise prediction to network level prediction. Many of the existing network level methods predict PPIs under the assumption that the training network should be connected. However, this assumption greatly affects the prediction power and limits the application area because the current golden standard PPI networks are usually very sparse and disconnected. Therefore, how to effectively predict PPIs based on a training network that is sparse and disconnected remains a challenge. In this work, we developed a novel PPI prediction method based on deep learning neural network and regularized Laplacian kernel. We use a neural network with an autoencoder-like architecture to implicitly simulate the evolutionary processes of a PPI network. Neurons of the output layer correspond to proteins and are labeled with values (1 for interaction and 0 for otherwise) from the adjacency matrix of a sparse disconnected training PPI network. Unlike autoencoder, neurons at the input layer are given all zero input, reflecting an assumption of no a priori knowledge about PPIs, and hidden layers of smaller sizes mimic ancient interactome at different times during evolution. After the training step, an evolved PPI network whose rows are outputs of the neural network can be obtained. We then predict PPIs by applying the regularized Laplacian kernel to the transition matrix that is built upon the evolved PPI network. The results from cross-validation experiments show that the PPI prediction accuracies for yeast data and human data measured as AUC are increased by up to 8.4 and 14.9% respectively, as compared to the baseline. Moreover, the evolved PPI network can also help us leverage complementary information from the disconnected training network and multiple heterogeneous data sources. Tested by the yeast data with six heterogeneous feature kernels, the results show our method can further improve the prediction performance by up to 2%, which is very close to an upper bound that is obtained by an Approximate Bayesian Computation based sampling method. The proposed evolution deep neural network, coupled with regularized Laplacian kernel, is an effective tool in completing sparse and disconnected PPI networks and in facilitating integration of heterogeneous data sources.

To See or Not to See: Do Front of Pack Nutrition Labels Affect Attention to Overall Nutrition Information?

PubMed Central

Bix, Laura; Sundar, Raghav Prashant; Bello, Nora M.; Peltier, Chad; Weatherspoon, Lorraine J.; Becker, Mark W.

2015-01-01

Background Front of pack (FOP) nutrition labels are concise labels located on the front of food packages that provide truncated nutrition information. These labels are rapidly gaining prominence worldwide, presumably because they attract attention and their simplified formats enable rapid comparisons of nutritional value. Methods Eye tracking was conducted as US consumers interacted with actual packages with and without FOP labels to (1) assess if the presence of an FOP label increases attention to nutrition information when viewers are not specifically tasked with nutrition-related goals; and (2) study the effect of FOP presence on consumer use of more comprehensive, traditional nutrition information presented in the Nutritional Facts Panel (NFP), a mandatory label for most packaged foods in the US. Results Our results indicate that colored FOP labels enhanced the probability that any nutrition information was attended, and resulted in faster detection and longer viewing of nutrition information. However, for cereal packages, these benefits were at the expense of attention to the more comprehensive NFP. Our results are consistent with a potential short cut effect of FOP labels, such that if an FOP was present, participants spent less time attending the more comprehensive NFP. For crackers, FOP labels increased time spent attending to nutrition information, but we found no evidence that their presence reduced the time spent on the nutrition information in the NFP. Conclusions The finding that FOP labels increased attention to overall nutrition information by people who did not have an explicit nutritional goal suggests that these labels may have an advantage in conveying nutrition information to a wide segment of the population. However, for some food types this benefit may come with a short-cut effect; that is, decreased attention to more comprehensive nutrition information. These results have implications for policy and warrant further research into the mechanisms by which FOP labels impact use of nutrition information by consumers for different foods. PMID:26488611

Structural analysis of N-glycans by the glycan-labeling method using 3-aminoquinoline-based liquid matrix in negative-ion MALDI-MS.

PubMed

Nishikaze, Takashi; Kaneshiro, Kaoru; Kawabata, Shin-ichirou; Tanaka, Koichi

2012-11-06

Negative-ion fragmentation of underivatized N-glycans has been proven to be more informative than positive-ion fragmentation. Fluorescent labeling via reductive amination is often employed for glycan analysis, but little is known about the influence of the labeling group on negative-ion fragmentation. We previously demonstrated that the on-target glycan-labeling method using 3-aminoquinoline/α-cyano-4-hydroxycinnamic acid (3AQ/CHCA) liquid matrix enables highly sensitive, rapid, and quantitative N-glycan profiling analysis. The current study investigates the suitability of 3AQ-labeled N-glycans for structural analysis based on negative-ion collision-induced dissociation (CID) spectra. 3AQ-labeled N-glycans exhibited simple and informative CID spectra similar to those of underivatized N-glycans, with product ions due to cross-ring cleavages of the chitobiose core and ions specific to two antennae (D and E ions). The interpretation of diagnostic fragment ions suggested for underivatized N-glycans could be directly applied to the 3AQ-labeled N-glycans. However, fluorescently labeled N-glycans by conventional reductive amination, such as 2-aminobenzamide (2AB)- and 2-pyrydilamine (2PA)-labeled N-glycans, exhibited complicated CID spectra consisting of numerous signals formed by dehydration and multiple cleavages. The complicated spectra of 2AB- and 2PA-labeled N-glycans was found to be due to their open reducing-terminal N-acetylglucosamine (GlcNAc) ring, rather than structural differences in the labeling group in the N-glycan derivative. Finally, as an example, the on-target 3AQ labeling method followed by negative-ion CID was applied to structurally analyze neutral N-glycans released from human epidermal growth factor receptor type 2 (HER2) protein. The glycan-labeling method using 3AQ-based liquid matrix should facilitate highly sensitive quantitative and qualitative analyses of glycans.

Quenched substrates for live-cell labeling of SNAP-tagged fusion proteins with improved fluorescent background.

PubMed

Stöhr, Katharina; Siegberg, Daniel; Ehrhard, Tanja; Lymperopoulos, Konstantinos; Öz, Simin; Schulmeister, Sonja; Pfeifer, Andrea C; Bachmann, Julie; Klingmüller, Ursula; Sourjik, Victor; Herten, Dirk-Peter

2010-10-01

Recent developments in fluorescence microscopy raise the demands for bright and photostable fluorescent tags for specific and background free labeling in living cells. Aside from fluorescent proteins and other tagging methods, labeling of SNAP-tagged proteins has become available thereby increasing the pool of potentially applicable fluorescent dyes for specific labeling of proteins. Here, we report on novel conjugates of benzylguanine (BG) which are quenched in their fluorescence and become highly fluorescent upon labeling of the SNAP-tag, the commercial variant of the human O(6)-alkylguanosyltransferase (hAGT). We identified four conjugates showing a strong increase, i.e., >10-fold, in fluorescence intensity upon labeling of SNAP-tag in vitro. Moreover, we screened a subset of nine BG-dye conjugates in living Escherichia coli and found them all suited for labeling of the SNAP-tag. Here, quenched BG-dye conjugates yield a higher specificity due to reduced contribution from excess conjugate to the fluorescence signal. We further extended the application of these conjugates by labeling a SNAP-tag fusion of the Tar chemoreceptor in live E. coli cells and the eukaryotic transcription factor STAT5b in NIH 3T3 mouse fibroblast cells. Aside from the labeling efficiency and specificity in living cells, we discuss possible mechanisms that might be responsible for the changes in fluorescence emission upon labeling of the SNAP-tag, as well as problems we encountered with nonspecific labeling with certain conjugates in eukaryotic cells.

Specifying the brain anatomy underlying temporo-parietal junction activations for theory of mind: A review using probabilistic atlases from different imaging modalities.

PubMed

Schurz, Matthias; Tholen, Matthias G; Perner, Josef; Mars, Rogier B; Sallet, Jerome

2017-09-01

In this quantitative review, we specified the anatomical basis of brain activity reported in the Temporo-Parietal Junction (TPJ) in Theory of Mind (ToM) research. Using probabilistic brain atlases, we labeled TPJ peak coordinates reported in the literature. This was carried out for four different atlas modalities: (i) gyral-parcellation, (ii) sulco-gyral parcellation, (iii) cytoarchitectonic parcellation and (iv) connectivity-based parcellation. In addition, our review distinguished between two ToM task types (false belief and social animations) and a nonsocial task (attention reorienting). We estimated the mean probabilities of activation for each atlas label, and found that for all three task types part of TPJ activations fell into the same areas: (i) Angular Gyrus (AG) and Lateral Occpital Cortex (LOC) in terms of a gyral atlas, (ii) AG and Superior Temporal Sulcus (STS) in terms of a sulco-gyral atlas, (iii) areas PGa and PGp in terms of cytoarchitecture and (iv) area TPJp in terms of a connectivity-based parcellation atlas. Beside these commonalities, we also found that individual task types showed preferential activation for particular labels. Main findings for the right hemisphere were preferential activation for false belief tasks in AG/PGa, and in Supramarginal Gyrus (SMG)/PFm for attention reorienting. Social animations showed strongest selective activation in the left hemisphere, specifically in left Middle Temporal Gyrus (MTG). We discuss how our results (i.e., identified atlas structures) can provide a new reference for describing future findings, with the aim to integrate different labels and terminologies used for studying brain activity around the TPJ. Hum Brain Mapp 38:4788-4805, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Site-Specific Antibody Labeling by Covalent Photoconjugation of Z Domains Functionalized for Alkyne-Azide Cycloaddition Reactions.

PubMed

Perols, Anna; Arcos Famme, Melina; Eriksson Karlström, Amelie

2015-11-01

Antibodies are extensively used in research, diagnostics, and therapy, and for many applications the antibodies need to be labeled. Labeling is typically performed by using amine-reactive probes that target surface-exposed lysine residues, resulting in heterogeneously labeled antibodies. An alternative labeling strategy is based on the immunoglobulin G (IgG)-binding protein domain Z, which binds to the Fc region of IgG. Introducing the photoactivable amino acid benzoylphenylalanine (BPA) into the Z domain makes it possible for a covalent bond to be be formed between the Z domain and the antibody on UV irradiation, to produce a site-specifically labeled product. Z32 BPA was synthesized by solid-phase peptide synthesis and further functionalized to give alkyne-Z32 BPA and azide-Z32 BPA for Cu(I) -catalyzed cycloaddition, as well as DBCO-Z32 BPA for Cu-free strain-promoted cycloaddition. The Z32 BPA variants were conjugated to the human IgG1 antibody trastuzumab and site-specifically labeled with biotin or fluorescein. The fluorescently labeled trastuzumab showed specific staining of the membranes of HER2-expressing cells in immunofluorescence microscopy. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Site-specific labeling of RNA at internal ribose hydroxyl groups: terbium-assisted deoxyribozymes at work.

PubMed

Büttner, Lea; Javadi-Zarnaghi, Fatemeh; Höbartner, Claudia

2014-06-04

A general and efficient single-step method was established for site-specific post-transcriptional labeling of RNA. Using Tb(3+) as accelerating cofactor for deoxyribozymes, various labeled guanosines were site-specifically attached to 2'-OH groups of internal adenosines in in vitro transcribed RNA. The DNA-catalyzed 2',5'-phosphodiester bond formation proceeded efficiently with fluorescent, spin-labeled, biotinylated, or cross-linker-modified guanosine triphosphates. The sequence context of the labeling site was systematically analyzed by mutating the nucleotides flanking the targeted adenosine. Labeling of adenosines in a purine-rich environment showed the fastest reactions and highest yields. Overall, practically useful yields >70% were obtained for 13 out of 16 possible nucleotide (nt) combinations. Using this approach, we demonstrate preparative labeling under mild conditions for up to ~160-nt-long RNAs, including spliceosomal U6 small nuclear RNA and a cyclic-di-AMP binding riboswitch RNA.

A novel universal DNA labeling and amplification system for rapid microarray-based detection of 117 antibiotic resistance genes in Gram-positive bacteria.

PubMed

Strauss, Christian; Endimiani, Andrea; Perreten, Vincent

2015-01-01

A rapid and simple DNA labeling system has been developed for disposable microarrays and has been validated for the detection of 117 antibiotic resistance genes abundant in Gram-positive bacteria. The DNA was fragmented and amplified using phi-29 polymerase and random primers with linkers. Labeling and further amplification were then performed by classic PCR amplification using biotinylated primers specific for the linkers. The microarray developed by Perreten et al. (Perreten, V., Vorlet-Fawer, L., Slickers, P., Ehricht, R., Kuhnert, P., Frey, J., 2005. Microarray-based detection of 90 antibiotic resistance genes of gram-positive bacteria. J.Clin.Microbiol. 43, 2291-2302.) was improved by additional oligonucleotides. A total of 244 oligonucleotides (26 to 37 nucleotide length and with similar melting temperatures) were spotted on the microarray, including genes conferring resistance to clinically important antibiotic classes like β-lactams, macrolides, aminoglycosides, glycopeptides and tetracyclines. Each antibiotic resistance gene is represented by at least 2 oligonucleotides designed from consensus sequences of gene families. The specificity of the oligonucleotides and the quality of the amplification and labeling were verified by analysis of a collection of 65 strains belonging to 24 species. Association between genotype and phenotype was verified for 6 antibiotics using 77 Staphylococcus strains belonging to different species and revealed 95% test specificity and a 93% predictive value of a positive test. The DNA labeling and amplification is independent of the species and of the target genes and could be used for different types of microarrays. This system has also the advantage to detect several genes within one bacterium at once, like in Staphylococcus aureus strain BM3318, in which up to 15 genes were detected. This new microarray-based detection system offers a large potential for applications in clinical diagnostic, basic research, food safety and surveillance programs for antimicrobial resistance. Copyright © 2014 Elsevier B.V. All rights reserved.

Diffraction pattern simulation of cellulose fibrils using distributed and quantized pair distances

DOE PAGES

Zhang, Yan; Inouye, Hideyo; Crowley, Michael; ...

2016-10-14

Intensity simulation of X-ray scattering from large twisted cellulose molecular fibrils is important in understanding the impact of chemical or physical treatments on structural properties such as twisting or coiling. This paper describes a highly efficient method for the simulation of X-ray diffraction patterns from complex fibrils using atom-type-specific pair-distance quantization. Pair distances are sorted into arrays which are labelled by atom type. Histograms of pair distances in each array are computed and binned and the resulting population distributions are used to represent the whole pair-distance data set. These quantized pair-distance arrays are used with a modified and vectorized Debyemore » formula to simulate diffraction patterns. This approach utilizes fewer pair distances in each iteration, and atomic scattering factors are moved outside the iteration since the arrays are labelled by atom type. As a result, this algorithm significantly reduces the computation time while maintaining the accuracy of diffraction pattern simulation, making possible the simulation of diffraction patterns from large twisted fibrils in a relatively short period of time, as is required for model testing and refinement.« less

Diffraction pattern simulation of cellulose fibrils using distributed and quantized pair distances

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yan; Inouye, Hideyo; Crowley, Michael

Intensity simulation of X-ray scattering from large twisted cellulose molecular fibrils is important in understanding the impact of chemical or physical treatments on structural properties such as twisting or coiling. This paper describes a highly efficient method for the simulation of X-ray diffraction patterns from complex fibrils using atom-type-specific pair-distance quantization. Pair distances are sorted into arrays which are labelled by atom type. Histograms of pair distances in each array are computed and binned and the resulting population distributions are used to represent the whole pair-distance data set. These quantized pair-distance arrays are used with a modified and vectorized Debyemore » formula to simulate diffraction patterns. This approach utilizes fewer pair distances in each iteration, and atomic scattering factors are moved outside the iteration since the arrays are labelled by atom type. This algorithm significantly reduces the computation time while maintaining the accuracy of diffraction pattern simulation, making possible the simulation of diffraction patterns from large twisted fibrils in a relatively short period of time, as is required for model testing and refinement.« less

Diffraction pattern simulation of cellulose fibrils using distributed and quantized pair distances

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yan; Inouye, Hideyo; Crowley, Michael

Intensity simulation of X-ray scattering from large twisted cellulose molecular fibrils is important in understanding the impact of chemical or physical treatments on structural properties such as twisting or coiling. This paper describes a highly efficient method for the simulation of X-ray diffraction patterns from complex fibrils using atom-type-specific pair-distance quantization. Pair distances are sorted into arrays which are labelled by atom type. Histograms of pair distances in each array are computed and binned and the resulting population distributions are used to represent the whole pair-distance data set. These quantized pair-distance arrays are used with a modified and vectorized Debyemore » formula to simulate diffraction patterns. This approach utilizes fewer pair distances in each iteration, and atomic scattering factors are moved outside the iteration since the arrays are labelled by atom type. As a result, this algorithm significantly reduces the computation time while maintaining the accuracy of diffraction pattern simulation, making possible the simulation of diffraction patterns from large twisted fibrils in a relatively short period of time, as is required for model testing and refinement.« less

Methodology for the specification of communication activities within the framework of a multi-layered architecture: Toward the definition of a knowledge base

NASA Astrophysics Data System (ADS)

Amyay, Omar

A method defined in terms of synthesis and verification steps is presented. The specification of the services and protocols of communication within a multilayered architecture of the Open Systems Interconnection (OSI) type is an essential issue for the design of computer networks. The aim is to obtain an operational specification of the protocol service couple of a given layer. Planning synthesis and verification steps constitute a specification trajectory. The latter is based on the progressive integration of the 'initial data' constraints and verification of the specification originating from each synthesis step, through validity constraints that characterize an admissible solution. Two types of trajectories are proposed according to the style of the initial specification of the service protocol couple: operational type and service supplier viewpoint; knowledge property oriented type and service viewpoint. Synthesis and verification activities were developed and formalized in terms of labeled transition systems, temporal logic and epistemic logic. The originality of the second specification trajectory and the use of the epistemic logic are shown. An 'artificial intelligence' approach enables a conceptual model to be defined for a knowledge base system for implementing the method proposed. It is structured in three levels of representation of the knowledge relating to the domain, the reasoning characterizing synthesis and verification activities and the planning of the steps of a specification trajectory.

Specificity of lecithin:cholesterol acyltransferase and atherogenic risk: comparative studies on the plasma composition and in vitro synthesis of cholesteryl esters in 14 vertebrate species.

PubMed

Liu, M; Bagdade, J D; Subbaiah, P V

1995-08-01

To determine whether the specificity of lecithin: cholesterol acyltransferase (LCAT) influences the susceptibility to atherosclerosis, we compared the composition and in vitro synthesis of cholesteryl ester (CE) in the plasmas of 14 vertebrate species with varying predisposition to atherosclerosis. The susceptible species (Group I) had significantly higher ratios of 16:0 CE/20:4 CE in their plasma than the resistant species (Group II). The in vitro formation of labeled CE species in native plasma from labeled cholesterol correlated highly with the mass composition, showing that the LCAT reaction is the predominant source of plasma CE in all the animal species examined. Isolated LCATs from Group I species also synthesized CE with higher ratios of 16:0/20:4 than LCATs from Group II when egg phosphatidylcholine (PC) was used as the acyl donor. In addition, the Group I LCATs exhibited lower specificity towards sn-2-20:4 and sn-2-22:6 PCs, and higher specificity towards sn-2-18:2 PC species than Group II LCATs. With 16:0-20:4 PC as the substrate, all Group I LCATs synthesized more 16:0 CE than 20:4 CE, whereas all Group II LCATs, with the exception of dog enzyme, synthesized predominantly 20:4 CE, showing that the two types of LCAT have different positional specificities towards this PC. These results suggest that there are two classes of LCAT in nature that differ from each other in their substrate and positional specificities, possibly because of differences in their active-site architectures. We propose that the presence of one type of LCAT, which cannot efficiently transfer certain long chain polyunsaturated acyl groups and which consequently synthesizes more saturated CE, may increase the risk of atherosclerosis.

Searching for flavor labels in food products: the influence of color-flavor congruence and association strength.

PubMed

Velasco, Carlos; Wan, Xiaoang; Knoeferle, Klemens; Zhou, Xi; Salgado-Montejo, Alejandro; Spence, Charles

2015-01-01

Prior research provides robust support for the existence of a number of associations between colors and flavors. In the present study, we examined whether congruent (vs. incongruent) combinations of product packaging colors and flavor labels would facilitate visual search for products labeled with specific flavors. The two experiments reported here document a Stroop-like effect between flavor words and packaging colors. The participants were able to search for packaging flavor labels more rapidly when the color of the packaging was congruent with the flavor label (e.g., red/tomato) than when it was incongruent (e.g., yellow/tomato). In addition, when the packaging color was incongruent, those flavor labels that were more strongly associated with a specific color yielded slower reaction times and more errors (Stroop interference) than those that were less strongly tied to a specific color. Importantly, search efficiency was affected both by color/flavor congruence and association strength. Taken together, these results therefore highlight the role of color congruence and color-word association strength when it comes to searching for specific flavor labels.

A Magic-Angle Spinning NMR Method for the Site-Specific Measurement of Proton Chemical-Shift Anisotropy in Biological and Organic Solids.

PubMed

Hou, Guangjin; Gupta, Rupal; Polenova, Tatyana; Vega, Alexander J

2014-02-01

Proton chemical shifts are a rich probe of structure and hydrogen bonding environments in organic and biological molecules. Until recently, measurements of 1 H chemical shift tensors have been restricted to either solid systems with sparse proton sites or were based on the indirect determination of anisotropic tensor components from cross-relaxation and liquid-crystal experiments. We have introduced an MAS approach that permits site-resolved determination of CSA tensors of protons forming chemical bonds with labeled spin-1/2 nuclei in fully protonated solids with multiple sites, including organic molecules and proteins. This approach, originally introduced for the measurements of chemical shift tensors of amide protons, is based on three RN -symmetry based experiments, from which the principal components of the 1 H CS tensor can be reliably extracted by simultaneous triple fit of the data. In this article, we expand our approach to a much more challenging system involving aliphatic and aromatic protons. We start with a review of the prior work on experimental-NMR and computational-quantum-chemical approaches for the measurements of 1 H chemical shift tensors and for relating these to the electronic structures. We then present our experimental results on U- 13 C, 15 N-labeled histdine demonstrating that 1 H chemical shift tensors can be reliably determined for the 1 H 15 N and 1 H 13 C spin pairs in cationic and neutral forms of histidine. Finally, we demonstrate that the experimental 1 H(C) and 1 H(N) chemical shift tensors are in agreement with Density Functional Theory calculations, therefore establishing the usefulness of our method for characterization of structure and hydrogen bonding environment in organic and biological solids.

Improved specificity of hippocampal memory trace labeling.

PubMed

Cazzulino, Alejandro S; Martinez, Randy; Tomm, Nicole K; Denny, Christine A

2016-06-01

Recent studies have focused on the identification and manipulation of memory traces in rodent models. The two main mouse models utilized are either a CreER(T2) /loxP tamoxifen (TAM)- or a tetracycline transactivator/tetracycline-response element doxycycline-inducible system. These systems, however, could be improved to label a more specific population of activated neurons corresponding to behavior. Here, we sought to identify an improved selective estrogen receptor (ER) modulator (SERM) in which we could label an individual memory trace in ArcCreER(T2) mice. We found that 4-hydroxytamoxifen (4-OHT) is a selective SERM in the ArcCreER(T2) × Rosa26-CAG-stop(flox) -channelrhodospin (ChR2)-enhanced yellow fluorescent protein (eYFP) mice. The half-life of 4-OHT is shorter than TAM, allowing for more specificity of memory trace labeling. Furthermore, 4-OHT allowed for context-specific labeling in the dentate gyrus and CA3. In summary, we believe that 4-OHT improves the specificity of memory trace labeling and will allow for refined memory trace studies in the future. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Sparse models for correlative and integrative analysis of imaging and genetic data

PubMed Central

Lin, Dongdong; Cao, Hongbao; Calhoun, Vince D.

2014-01-01

The development of advanced medical imaging technologies and high-throughput genomic measurements has enhanced our ability to understand their interplay as well as their relationship with human behavior by integrating these two types of datasets. However, the high dimensionality and heterogeneity of these datasets presents a challenge to conventional statistical methods; there is a high demand for the development of both correlative and integrative analysis approaches. Here, we review our recent work on developing sparse representation based approaches to address this challenge. We show how sparse models are applied to the correlation and integration of imaging and genetic data for biomarker identification. We present examples on how these approaches are used for the detection of risk genes and classification of complex diseases such as schizophrenia. Finally, we discuss future directions on the integration of multiple imaging and genomic datasets including their interactions such as epistasis. PMID:25218561

A high-capacity model for one shot association learning in the brain

PubMed Central

Einarsson, Hafsteinn; Lengler, Johannes; Steger, Angelika

2014-01-01

We present a high-capacity model for one-shot association learning (hetero-associative memory) in sparse networks. We assume that basic patterns are pre-learned in networks and associations between two patterns are presented only once and have to be learned immediately. The model is a combination of an Amit-Fusi like network sparsely connected to a Willshaw type network. The learning procedure is palimpsest and comes from earlier work on one-shot pattern learning. However, in our setup we can enhance the capacity of the network by iterative retrieval. This yields a model for sparse brain-like networks in which populations of a few thousand neurons are capable of learning hundreds of associations even if they are presented only once. The analysis of the model is based on a novel result by Janson et al. on bootstrap percolation in random graphs. PMID:25426060

Analysis, tuning and comparison of two general sparse solvers for distributed memory computers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Amestoy, P.R.; Duff, I.S.; L'Excellent, J.-Y.

2000-06-30

We describe the work performed in the context of a Franco-Berkeley funded project between NERSC-LBNL located in Berkeley (USA) and CERFACS-ENSEEIHT located in Toulouse (France). We discuss both the tuning and performance analysis of two distributed memory sparse solvers (superlu from Berkeley and mumps from Toulouse) on the 512 processor Cray T3E from NERSC (Lawrence Berkeley National Laboratory). This project gave us the opportunity to improve the algorithms and add new features to the codes. We then quite extensively analyze and compare the two approaches on a set of large problems from real applications. We further explain the main differencesmore » in the behavior of the approaches on artificial regular grid problems. As a conclusion to this activity report, we mention a set of parallel sparse solvers on which this type of study should be extended.« less

A high-capacity model for one shot association learning in the brain.

PubMed

Einarsson, Hafsteinn; Lengler, Johannes; Steger, Angelika

2014-01-01

We present a high-capacity model for one-shot association learning (hetero-associative memory) in sparse networks. We assume that basic patterns are pre-learned in networks and associations between two patterns are presented only once and have to be learned immediately. The model is a combination of an Amit-Fusi like network sparsely connected to a Willshaw type network. The learning procedure is palimpsest and comes from earlier work on one-shot pattern learning. However, in our setup we can enhance the capacity of the network by iterative retrieval. This yields a model for sparse brain-like networks in which populations of a few thousand neurons are capable of learning hundreds of associations even if they are presented only once. The analysis of the model is based on a novel result by Janson et al. on bootstrap percolation in random graphs.

PCV2 vaccination induces IFN-γ/TNF-α co-producing T cells with a potential role in protection.

PubMed

Koinig, Hanna C; Talker, Stephanie C; Stadler, Maria; Ladinig, Andrea; Graage, Robert; Ritzmann, Mathias; Hennig-Pauka, Isabel; Gerner, Wilhelm; Saalmüller, Armin

2015-03-03

Porcine circovirus type 2 (PCV2) is one of the economically most important pathogens for swine production worldwide. Vaccination is a powerful tool to control porcine circovirus diseases (PCVD). However, it is not fully understood how PCV2 vaccination interacts with the porcine immune system. Especially knowledge on the cellular immune response against PCV2 is sparse. In this study we analysed antigen-specific T cell responses against PCV2 in a controlled vaccination and infection experiment. We focused on the ability of CD4(+) T cells to produce cytokines using multicolour flow cytometry (FCM). Vaccination with a PCV2 subunit vaccine (Ingelvac CircoFLEX®) induced PCV2-specific antibodies only in five out of 12 animals. Conversely, vaccine-antigen specific CD4(+) T cells which simultaneously produced IFN-γ and TNF-α and had a phenotype of central and effector memory T cells were detected in all vaccinated piglets. After challenge, seroconversion occurred earlier in vaccinated and infected pigs compared to the non-vaccinated, infected group. Vaccinated pigs were fully protected against viremia after subsequent challenge. Therefore, our data suggests that the induction of IFN-γ/TNF-α co-producing T cells by PCV2 vaccination may serve as a potential correlate of protection for this type of vaccine.

Strain-Specific Changes in Locomotor Behavior in Larval Zebrafish Elicited by Cholinergic Challenge

EPA Science Inventory

Some studies have compared the baseline behavior of different strains of larval zebrafish (Danio rerio), but there is sparse information on strain-specific responses to chemical challenges. The following study examines both the basal activity and response to a pharmacological cha...

An Automated Approach to Examining Conversational Dynamics between People with Dementia and Their Carers

PubMed Central

Atay, Christina; Conway, Erin R.; Angus, Daniel; Wiles, Janet; Baker, Rosemary; Chenery, Helen J.

2015-01-01

The progressive neuropathology involved in dementia frequently causes a gradual decline in communication skills. Communication partners who are unaware of the specific communication problems faced by people with dementia (PWD) can inadvertently challenge their conversation partner, leading to distress and a reduced flow of information between speakers. Previous research has produced an extensive literature base recommending strategies to facilitate conversational engagement in dementia. However, empirical evidence for the beneficial effects of these strategies on conversational dynamics is sparse. This study uses a time-efficient computational discourse analysis tool called Discursis to examine the link between specific communication behaviours and content-based conversational engagement in 20 conversations between PWD living in residential aged-care facilities and care staff members. Conversations analysed here were baseline conversations recorded before staff members underwent communication training. Care staff members spontaneously exhibited a wide range of facilitative and non-facilitative communication behaviours, which were coded for analysis of conversation dynamics within these baseline conversations. A hybrid approach combining manual coding and automated Discursis metric analysis provides two sets of novel insights. Firstly, this study revealed nine communication behaviours that, if used by the care staff member in a given turn, significantly increased the appearance of subsequent content-based engagement in the conversation by PWD. Secondly, the current findings reveal alignment between human- and computer-generated labelling of communication behaviour for 8 out of the total 22 behaviours under investigation. The approach demonstrated in this study provides an empirical procedure for the detailed evaluation of content-based conversational engagement associated with specific communication behaviours. PMID:26658135

Parents' meal choices for their children at fast food and family restaurants with different menu labeling presentations

PubMed Central

2018-01-01

BACKGROUND/OBJECTIVES This study examined the effect of nutrition labeling formats on parents' food choices for their children at different restaurant types. SUBJECTS/METHODS An online survey was conducted with 1,980 parents of children aged 3–12 years. Participants were randomly assigned to fast food or family restaurant scenarios, and one of four menu stimuli conditions: no labeling, low-calorie symbol (symbol), numeric value (numeric), and both low-calorie symbol and numeric value (symbol + numeric). Participants selected menu items for their children. Menu choices and total calories were compared by nutrition labeling formats in each type of the restaurant. RESULTS Low-calorie item selections were scored and a two-way analysis of variance (ANOVA) was conducted for an interaction effect between restaurant and labeling type. In the fast food restaurant group, parents presented with low-calorie symbols selected the lowest calorie items more often than those not presented with the format. Parents in the symbol + numeric condition selected significantly fewer calories (653 kcal) than those in the no labeling (677 kcal) or numeric conditions (674 kcal) (P = 0.006). In the family restaurant group, no significant difference were observed among different labeling conditions. A significant interaction between restaurant and labeling type on low-calorie selection score (F = 6.03, P < 0.01) suggests that the effect of nutrition labeling format interplays with restaurant type to jointly affect parents' food choices for their children. CONCLUSIONS The provision of easily interpretable nutritional information format at fast food restaurants may encourage healthier food choices of parents for their children; however, the effects were negligible at family restaurants. PMID:29854330

Personal messages reduce vandalism and theft of unattended scientific equipment

PubMed Central

Clarin, B-Markus; Bitzilekis, Eleftherios; Siemers, Björn M; Goerlitz, Holger R

2014-01-01

Scientific equipment, such as animal traps and autonomous data collection systems, is regularly left in the field unattended, making it an easy target for vandalism or theft. We tested the effectiveness of three label types, which differed in their information content and tone of the message, that is, personal,neutral or threatening, for reducing incidents of vandalism and theft of unattended scientific field equipment. The three label types were attached to 20 scientific equipment dummies each, which were placed semi-hidden and evenly distributed in four public parks in Munich, Germany. While the label type had no effect on the severity of the interactions with our equipment dummies, the personal label reduced the overall number of interactions by c. 40–60%, compared with the dummies showing the neutral or threatening label type. We suggest that researchers, in addition to securing their field equipment, label it with personal and polite messages that inform about the ongoing research and directly appeal to the public not to disturb the equipment. Further studies should extend these results to areas with different socio-economic structure. PMID:25866614

Personal messages reduce vandalism and theft of unattended scientific equipment.

PubMed

Clarin, B-Markus; Bitzilekis, Eleftherios; Siemers, Björn M; Goerlitz, Holger R

2014-02-01

Scientific equipment, such as animal traps and autonomous data collection systems, is regularly left in the field unattended, making it an easy target for vandalism or theft. We tested the effectiveness of three label types, which differed in their information content and tone of the message, that is, personal , neutral or threatening , for reducing incidents of vandalism and theft of unattended scientific field equipment. The three label types were attached to 20 scientific equipment dummies each, which were placed semi-hidden and evenly distributed in four public parks in Munich, Germany. While the label type had no effect on the severity of the interactions with our equipment dummies, the personal label reduced the overall number of interactions by c . 40-60%, compared with the dummies showing the neutral or threatening label type. We suggest that researchers, in addition to securing their field equipment, label it with personal and polite messages that inform about the ongoing research and directly appeal to the public not to disturb the equipment. Further studies should extend these results to areas with different socio-economic structure.

Subject-Specific Sparse Dictionary Learning for Atlas-Based Brain MRI Segmentation.

PubMed

Roy, Snehashis; He, Qing; Sweeney, Elizabeth; Carass, Aaron; Reich, Daniel S; Prince, Jerry L; Pham, Dzung L

2015-09-01

Quantitative measurements from segmentations of human brain magnetic resonance (MR) images provide important biomarkers for normal aging and disease progression. In this paper, we propose a patch-based tissue classification method from MR images that uses a sparse dictionary learning approach and atlas priors. Training data for the method consists of an atlas MR image, prior information maps depicting where different tissues are expected to be located, and a hard segmentation. Unlike most atlas-based classification methods that require deformable registration of the atlas priors to the subject, only affine registration is required between the subject and training atlas. A subject-specific patch dictionary is created by learning relevant patches from the atlas. Then the subject patches are modeled as sparse combinations of learned atlas patches leading to tissue memberships at each voxel. The combination of prior information in an example-based framework enables us to distinguish tissues having similar intensities but different spatial locations. We demonstrate the efficacy of the approach on the application of whole-brain tissue segmentation in subjects with healthy anatomy and normal pressure hydrocephalus, as well as lesion segmentation in multiple sclerosis patients. For each application, quantitative comparisons are made against publicly available state-of-the art approaches.

Several Modified Goodness-Of-Fit Tests for the Cauchy Distribution with Unknown Scale and Location Parameters

DTIC Science & Technology

1994-03-01

labels of a, which is called significance levels. The hypothesis tests are done based on the a levels . The maximum probabilities of making type II error...critical values at specific a levels . This procedure is done for each of the 50,000 samples. The number of the samples passing each test at those specific... a levels is counted. The ratio of the number of accepted samples to 50,000 gives the percentage point. Then, subtracting that value from one would

Evaluation of radiation dose to anthropomorphic paediatric models from positron-emitting labelled tracers

NASA Astrophysics Data System (ADS)

Xie, Tianwu; Zaidi, Habib

2014-03-01

PET uses specific molecules labelled with positron-emitting radionuclides to provide valuable biochemical and physiological information. However, the administration of radiotracers to patients exposes them to low-dose ionizing radiation, which is a concern in the paediatric population since children are at a higher cancer risk from radiation exposure than adults. Therefore, radiation dosimety calculations for commonly used positron-emitting radiotracers in the paediatric population are highly desired. We evaluate the absorbed dose and effective dose for 19 positron-emitting labelled radiotracers in anthropomorphic paediatric models including the newborn, 1-, 5-, 10- and 15-year-old male and female. This is achieved using pre-calculated S-values of positron-emitting radionuclides of UF-NCI paediatric phantoms and published biokinetic data for various radiotracers. The influence of the type of anthropomorphic model, tissue weight factors and direct human- versus mouse-derived biokinetic data on the effective dose for paediatric phantoms was also evaluated. In the case of 18F-FDG, dosimetry calculations of reference paediatric patients from various dose regimens were also calculated. Among the considered radiotracers, 18F-FBPA and 15O-water resulted in the highest and lowest effective dose in the paediatric phantoms, respectively. The ICRP 103 updated tissue-weighting factors decrease the effective dose in most cases. Substantial differences of radiation dose were observed between direct human- versus mouse-derived biokinetic data. Moreover, the effect of using voxel- versus MIRD-type models on the calculation of the effective dose was also studied. The generated database of absorbed organ dose and effective dose for various positron-emitting labelled radiotracers using new generation computational models and the new ICRP tissue-weighting factors can be used for the assessment of radiation risks to paediatric patients in clinical practice. This work also contributes to a better understanding of the factors influencing patient-specific radiation dose calculation.

Immunochemical identification of insect hemocyte populations: monoclonal antibodies distinguish four major hemocyte types in manduca sexta.

PubMed

Willott, E; Trenczek, T; Thrower, L W; Kanost, M R

1994-12-01

We have made 140 monoclonal antibodies to hemocytes (insect blood cells) from Manduca sexta. Four of these antibodies, when used in immunofluorescent microscopy of fixed hemocytes, distinguish the four main morphologically distinct hemocyte types. Plasmatocytes, granular cells, and oenocytoids are each recognized by a unique antibody specific to that type; spherulocytes are recognized by an antibody that also binds to plasmatocytes. When used in flow cytometry with nonfixed hemocytes, three of the four antibodies bind their respective cells; the oenocytoid marker failed to bind to any hemocytes. This set of four monoclonal antibodies may be useful for labeling individual cell types and for separating the different hemocyte types for further study of hemocyte functions.

EGFR-directed Affibody for fluorescence-guided glioma surgery: time-dose analysis (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ribeiro de Souza, Ana Luiza; Marra, Kayla; Gunn, Jason R.; Elliott, Jonathan T.; Samkoe, Kimberley S.; Paulsen, Keith D.; Draney, Daniel R.; Feldwisch, Joachim

2016-03-01

The key to fluorescence guided surgical oncology is the ability to create specific contrast between normal and glioma tissue. The blood brain barrier that limits the delivery of substances to the normal brain is broken in tumors, allowing accumulation of agents in the tumor interior. However, for a clinical success, imaging agents should be in the infiltrative edges to minimize the resection of normal brain while enable the removal of tumor. The aberrant overexpression and/or activation of EGFR is associated with many types of cancers, including glioblastoma and the injection of a fluorescent molecule targeted to these receptors would improve tumor contrast during fluorescence guided surgery. Affibody molecules have intentional medium affinity and high potential specificity, which are the desirable features of a good surgical imaging agent. The aim of this study was evaluate the brain/glioma uptake of ABY029 labeled with near-infrared dye IRDye800CW after intravenous injection. Rats were either inoculated with orthotopic implantations of U251 human glioma cell line or PBS (shams control) in the brain. The tumors were allowed to grow for 2-3 weeks before carrying out fluorescent tracer experiments. Fluorescent imaging of ex vivo brain slices from rats was acquired at different time points after infection of fluorescently labeled EGFR-specific affibody to verify which time provided maximal contrast tumor to normal brain. Although the tumor was most clearly visualized after 1h of IRDye800CW-labeled ABY029 injection, the tumor location could be identified from the background after 48h. These results suggest that the NIR-labeled affibody examined shows excellent potential to increase surgical visualization for confirmed EGFR positive tumors.

Unraveling the Nature of Active Sites in Ethanol Electro-oxidation by Site-Specific Marking of a Pt Catalyst with Isotope-Labeled 13CO.

PubMed

Farias, Manuel J S; Cheuquepán, William; Tanaka, Auro A; Feliu, Juan M

2018-03-15

This works deals with the identification of preferential site-specific activation at a model Pt surface during a multiproduct reaction. The (110)-type steps of a Pt(332) surface were selectively marked by attaching isotope-labeled 13 CO molecules to them, and ethanol oxidation was probed by in situ Foureir transfrom infrared spectroscopy in order to precisely determine the specific sites at which CO 2 , acetic acid, and acetaldehyde were preferentially formed. The (110) steps were active for splitting the C-C bond, but unexpectedly, we provide evidence that the pathway of CO 2 formation was preferentially activated at (111) terraces, rather than at (110) steps. Acetaldehyde was formed at (111) terraces at potentials comparable to those for CO 2 formation also at (111) terraces, while the acetic acid formation pathway became active only when the (110) steps were released by the oxidation of adsorbed 13 CO, at potentials higher than for the formation of CO 2 at (111) terraces of the stepped surface.

Distance Magic-Type and Distance Antimagic-Type Labelings of Graphs

NASA Astrophysics Data System (ADS)

Freyberg, Bryan J.

Generally speaking, a distance magic-type labeling of a graph G of order n is a bijection l from the vertex set of the graph to the first n natural numbers or to the elements of a group of order n, with the property that the weight of each vertex is the same. The weight of a vertex x is defined as the sum (or appropriate group operation) of all the labels of vertices adjacent to x. If instead we require that all weights differ, then we refer to the labeling as a distance antimagic-type labeling. This idea can be generalized for directed graphs; the weight will take into consideration the direction of the arcs. In this manuscript, we provide new results for d-handicap labeling, a distance antimagic-type labeling, and introduce a new distance magic-type labeling called orientable Gamma-distance magic labeling. A d-handicap distance antimagic labeling (or just d-handicap labeling for short) of a graph G = ( V,E) of order n is a bijection l from V to the set {1,2,...,n} with induced weight function [special characters omitted]. such that l(xi) = i and the sequence of weights w(x 1),w(x2),...,w (xn) forms an arithmetic sequence with constant difference d at least 1. If a graph G admits a d-handicap labeling, we say G is a d-handicap graph. A d-handicap incomplete tournament, H(n,k,d ) is an incomplete tournament of n teams ranked with the first n natural numbers such that each team plays exactly k games and the strength of schedule of the ith ranked team is d more than the i + 1st ranked team. That is, strength of schedule increases arithmetically with strength of team. Constructing an H(n,k,d) is equivalent to finding a d-handicap labeling of a k-regular graph of order n.. In Chapter 2 we provide general constructions for every d for large classes of both n and k, providing breadfth and depth to the catalog of known H(n,k,d)'s. In Chapters 3 - 6, we introduce a new type of labeling called orientable Gamma-distance magic labeling. Let Gamma be an abelian group of order n. If for a graph G = (V,E) of order n there exists an orientation of the edges of G and a companion bijection from V to Gamma with the property that there is an element mu of Gamma (called the magic constant) such that [special characters omitted] where w(x) is the weight of vertex x, we say that G is orientable Gamma -distance magic. In addition to introducing the concept, we provide numerous results on orientable Zn-distance magic graphs, where Zn is the cyclic group of order n.. In Chapter 7, we summarize the results of this dissertation and provide suggestions for future work.

Metabolite pools and carbon flow during C4 photosynthesis in maize: 13CO2 labeling kinetics and cell type fractionation.

PubMed

Arrivault, Stéphanie; Obata, Toshihiro; Szecówka, Marek; Mengin, Virginie; Guenther, Manuela; Hoehne, Melanie; Fernie, Alisdair R; Stitt, Mark

2017-01-01

Worldwide efforts to engineer C 4 photosynthesis into C 3 crops require a deep understanding of how this complex pathway operates. CO 2 is incorporated into four-carbon metabolites in the mesophyll, which move to the bundle sheath where they are decarboxylated to concentrate CO 2 around RuBisCO. We performed dynamic 13 CO 2 labeling in maize to analyze C flow in C 4 photosynthesis. The overall labeling kinetics reflected the topology of C 4 photosynthesis. Analyses of cell-specific labeling patterns after fractionation to enrich bundle sheath and mesophyll cells revealed concentration gradients to drive intercellular diffusion of malate, but not pyruvate, in the major CO 2 -concentrating shuttle. They also revealed intercellular concentration gradients of aspartate, alanine, and phosphenolpyruvate to drive a second phosphoenolpyruvate carboxykinase (PEPCK)-type shuttle, which carries 10-14% of the carbon into the bundle sheath. Gradients also exist to drive intercellular exchange of 3-phosphoglycerate and triose-phosphate. There is rapid carbon exchange between the Calvin-Benson cycle and the CO 2 -concentrating shuttle, equivalent to ~10% of carbon gain. In contrast, very little C leaks from the large pools of metabolites in the C concentration shuttle into respiratory metabolism. We postulate that the presence of multiple shuttles, alongside carbon transfer between them and the Calvin-Benson cycle, confers great flexibility in C 4 photosynthesis. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Identifying of meat species using polymerase chain reaction (PCR)

NASA Astrophysics Data System (ADS)

Foong, Chow Ming; Sani, Norrakiah Abdullah

2013-11-01

Meat has been widely consumed as an important protein source in daily life of human. Furthermore, with busy and intense urban lifestyle, processed food is now one of the main protein sources of one's diet. Consumers rely on the food labeling to decide if the meat product purchased is safe and reliable. Therefore, it is important to ensure the food labeling is done in a correct manner to avoid consumer fraud. More consumers are now concern about the food quality and safety as compared to before. This study described the meat species identification and detection method using Polymerase Chain Reaction (PCR) in 8 types of meats (cattle, buffalo, goat, sheep, chicken, duck, pork and horse). The objective of this study is to decide on the specificity of oligonucleotide sequences obtained from previous study. There were 5 proposed oligonucleotide primer in this study. The main important finding in this work is the specificity of oligonucleotide primers to raw meats. It if found that the oligonucleotide primers proposed were not specific to the local raw meat species. Therefore, further study is needed to obtain a species-specific oligonucletide primers for PCR, in order to be applied in food product testing.

Identifying of meat species using polymerase chain reaction (PCR)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Foong, Chow Ming; Sani, Norrakiah Abdullah

Meat has been widely consumed as an important protein source in daily life of human. Furthermore, with busy and intense urban lifestyle, processed food is now one of the main protein sources of one’s diet. Consumers rely on the food labeling to decide if the meat product purchased is safe and reliable. Therefore, it is important to ensure the food labeling is done in a correct manner to avoid consumer fraud. More consumers are now concern about the food quality and safety as compared to before. This study described the meat species identification and detection method using Polymerase Chain Reactionmore » (PCR) in 8 types of meats (cattle, buffalo, goat, sheep, chicken, duck, pork and horse). The objective of this study is to decide on the specificity of oligonucleotide sequences obtained from previous study. There were 5 proposed oligonucleotide primer in this study. The main important finding in this work is the specificity of oligonucleotide primers to raw meats. It if found that the oligonucleotide primers proposed were not specific to the local raw meat species. Therefore, further study is needed to obtain a species-specific oligonucletide primers for PCR, in order to be applied in food product testing.« less

Folded concave penalized sparse linear regression: sparsity, statistical performance, and algorithmic theory for local solutions.

PubMed

Liu, Hongcheng; Yao, Tao; Li, Runze; Ye, Yinyu

2017-11-01

This paper concerns the folded concave penalized sparse linear regression (FCPSLR), a class of popular sparse recovery methods. Although FCPSLR yields desirable recovery performance when solved globally, computing a global solution is NP-complete. Despite some existing statistical performance analyses on local minimizers or on specific FCPSLR-based learning algorithms, it still remains open questions whether local solutions that are known to admit fully polynomial-time approximation schemes (FPTAS) may already be sufficient to ensure the statistical performance, and whether that statistical performance can be non-contingent on the specific designs of computing procedures. To address the questions, this paper presents the following threefold results: (i) Any local solution (stationary point) is a sparse estimator, under some conditions on the parameters of the folded concave penalties. (ii) Perhaps more importantly, any local solution satisfying a significant subspace second-order necessary condition (S 3 ONC), which is weaker than the second-order KKT condition, yields a bounded error in approximating the true parameter with high probability. In addition, if the minimal signal strength is sufficient, the S 3 ONC solution likely recovers the oracle solution. This result also explicates that the goal of improving the statistical performance is consistent with the optimization criteria of minimizing the suboptimality gap in solving the non-convex programming formulation of FCPSLR. (iii) We apply (ii) to the special case of FCPSLR with minimax concave penalty (MCP) and show that under the restricted eigenvalue condition, any S 3 ONC solution with a better objective value than the Lasso solution entails the strong oracle property. In addition, such a solution generates a model error (ME) comparable to the optimal but exponential-time sparse estimator given a sufficient sample size, while the worst-case ME is comparable to the Lasso in general. Furthermore, to guarantee the S 3 ONC admits FPTAS.

Molecular beacon-enabled purification of living cells by targeting cell type-specific mRNAs.

PubMed

Wile, Brian M; Ban, Kiwon; Yoon, Young-Sup; Bao, Gang

2014-10-01

Molecular beacons (MBs) are dual-labeled oligonucleotides that fluoresce only in the presence of complementary mRNA. The use of MBs to target specific mRNAs allows sorting of specific cells from a mixed cell population. In contrast to existing approaches that are limited by available surface markers or selectable metabolic characteristics, the MB-based method enables the isolation of a wide variety of cells. For example, the ability to purify specific cell types derived from pluripotent stem cells (PSCs) is important for basic research and therapeutics. In addition to providing a general protocol for MB design, validation and nucleofection into cells, we describe how to isolate a specific cell population from differentiating PSCs. By using this protocol, we have successfully isolated cardiomyocytes differentiated from mouse or human PSCs (hPSCs) with ∼ 97% purity, as confirmed by electrophysiology and immunocytochemistry. After designing MBs, their ordering and validation requires 2 weeks, and the isolation process requires 3 h.

Signal processing using sparse derivatives with applications to chromatograms and ECG

NASA Astrophysics Data System (ADS)

Ning, Xiaoran

In this thesis, we investigate the sparsity exist in the derivative domain. Particularly, we focus on the type of signals which posses up to Mth (M > 0) order sparse derivatives. Efforts are put on formulating proper penalty functions and optimization problems to capture properties related to sparse derivatives, searching for fast, computationally efficient solvers. Also the effectiveness of these algorithms are applied to two real world applications. In the first application, we provide an algorithm which jointly addresses the problems of chromatogram baseline correction and noise reduction. The series of chromatogram peaks are modeled as sparse with sparse derivatives, and the baseline is modeled as a low-pass signal. A convex optimization problem is formulated so as to encapsulate these non-parametric models. To account for the positivity of chromatogram peaks, an asymmetric penalty function is also utilized with symmetric penalty functions. A robust, computationally efficient, iterative algorithm is developed that is guaranteed to converge to the unique optimal solution. The approach, termed Baseline Estimation And Denoising with Sparsity (BEADS), is evaluated and compared with two state-of-the-art methods using both simulated and real chromatogram data. Promising result is obtained. In the second application, a novel Electrocardiography (ECG) enhancement algorithm is designed also based on sparse derivatives. In the real medical environment, ECG signals are often contaminated by various kinds of noise or artifacts, for example, morphological changes due to motion artifact, non-stationary noise due to muscular contraction (EMG), etc. Some of these contaminations severely affect the usefulness of ECG signals, especially when computer aided algorithms are utilized. By solving the proposed convex l1 optimization problem, artifacts are reduced by modeling the clean ECG signal as a sum of two signals whose second and third-order derivatives (differences) are sparse respectively. At the end, the algorithm is applied to a QRS detection system and validated using the MIT-BIH Arrhythmia database (109452 anotations), resulting a sensitivity of Se = 99.87%$ and a positive prediction of +P = 99.88%.

Comparison between sparsely distributed memory and Hopfield-type neural network models

NASA Technical Reports Server (NTRS)

Keeler, James D.

1986-01-01

The Sparsely Distributed Memory (SDM) model (Kanerva, 1984) is compared to Hopfield-type neural-network models. A mathematical framework for comparing the two is developed, and the capacity of each model is investigated. The capacity of the SDM can be increased independently of the dimension of the stored vectors, whereas the Hopfield capacity is limited to a fraction of this dimension. However, the total number of stored bits per matrix element is the same in the two models, as well as for extended models with higher order interactions. The models are also compared in their ability to store sequences of patterns. The SDM is extended to include time delays so that contextual information can be used to cover sequences. Finally, it is shown how a generalization of the SDM allows storage of correlated input pattern vectors.

Constructing fine-granularity functional brain network atlases via deep convolutional autoencoder.

PubMed

Zhao, Yu; Dong, Qinglin; Chen, Hanbo; Iraji, Armin; Li, Yujie; Makkie, Milad; Kou, Zhifeng; Liu, Tianming

2017-12-01

State-of-the-art functional brain network reconstruction methods such as independent component analysis (ICA) or sparse coding of whole-brain fMRI data can effectively infer many thousands of volumetric brain network maps from a large number of human brains. However, due to the variability of individual brain networks and the large scale of such networks needed for statistically meaningful group-level analysis, it is still a challenging and open problem to derive group-wise common networks as network atlases. Inspired by the superior spatial pattern description ability of the deep convolutional neural networks (CNNs), a novel deep 3D convolutional autoencoder (CAE) network is designed here to extract spatial brain network features effectively, based on which an Apache Spark enabled computational framework is developed for fast clustering of larger number of network maps into fine-granularity atlases. To evaluate this framework, 10 resting state networks (RSNs) were manually labeled from the sparsely decomposed networks of Human Connectome Project (HCP) fMRI data and 5275 network training samples were obtained, in total. Then the deep CAE models are trained by these functional networks' spatial maps, and the learned features are used to refine the original 10 RSNs into 17 network atlases that possess fine-granularity functional network patterns. Interestingly, it turned out that some manually mislabeled outliers in training networks can be corrected by the deep CAE derived features. More importantly, fine granularities of networks can be identified and they reveal unique network patterns specific to different brain task states. By further applying this method to a dataset of mild traumatic brain injury study, it shows that the technique can effectively identify abnormal small networks in brain injury patients in comparison with controls. In general, our work presents a promising deep learning and big data analysis solution for modeling functional connectomes, with fine granularities, based on fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation.

PubMed

Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

2016-12-16

Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency.

Energy Balanced Strategies for Maximizing the Lifetime of Sparsely Deployed Underwater Acoustic Sensor Networks

PubMed Central

Luo, Hanjiang; Guo, Zhongwen; Wu, Kaishun; Hong, Feng; Feng, Yuan

2009-01-01

Underwater acoustic sensor networks (UWA-SNs) are envisioned to perform monitoring tasks over the large portion of the world covered by oceans. Due to economics and the large area of the ocean, UWA-SNs are mainly sparsely deployed networks nowadays. The limited battery resources is a big challenge for the deployment of such long-term sensor networks. Unbalanced battery energy consumption will lead to early energy depletion of nodes, which partitions the whole networks and impairs the integrity of the monitoring datasets or even results in the collapse of the entire networks. On the contrary, balanced energy dissipation of nodes can prolong the lifetime of such networks. In this paper, we focus on the energy balance dissipation problem of two types of sparsely deployed UWA-SNs: underwater moored monitoring systems and sparsely deployed two-dimensional UWA-SNs. We first analyze the reasons of unbalanced energy consumption in such networks, then we propose two energy balanced strategies to maximize the lifetime of networks both in shallow and deep water. Finally, we evaluate our methods by simulations and the results show that the two strategies can achieve balanced energy consumption per node while at the same time prolong the networks lifetime. PMID:22399970

[Neuronal organization of thalamic nucleus reticularis in adult man].

PubMed

Berezhnaia, L A

2005-01-01

The neuronal content of human thalamic nucleus reticularis was studied in serial sections cut in sagittal and frontal projections and impregnated with silver nitrate using Golgi method. The neuronal content of human thalamic nucleus reticularis was found to be more diverse than previously reported in animals and man. Besides two types of sparsely-branched long-dendritic spineless R1 and R2 neurons, this nucleus contained spiny cells. Medium and small-sized sparsely-branched short-dendritic neurons and densely-branched spiny cells were demonstrated. The principle of organization of human thalamic nucleus reticularis is described.

Computing sparse derivatives and consecutive zeros problem

NASA Astrophysics Data System (ADS)

Chandra, B. V. Ravi; Hossain, Shahadat

2013-02-01

We describe a substitution based sparse Jacobian matrix determination method using algorithmic differentiation. Utilizing the a priori known sparsity pattern, a compression scheme is determined using graph coloring. The "compressed pattern" of the Jacobian matrix is then reordered into a form suitable for computation by substitution. We show that the column reordering of the compressed pattern matrix (so as to align the zero entries into consecutive locations in each row) can be viewed as a variant of traveling salesman problem. Preliminary computational results show that on the test problems the performance of nearest-neighbor type heuristic algorithms is highly encouraging.

Differences in overland flow, hydrophobicity and soil moisture dynamics between Mediterranean woodland types in a peri-urban catchment in Portugal

NASA Astrophysics Data System (ADS)

Ferreira, C. S. S.; Walsh, R. P. D.; Shakesby, R. A.; Keizer, J. J.; Soares, D.; González-Pelayo, O.; Coelho, C. O. A.; Ferreira, A. J. D.

2016-02-01

Forest hydrology has been widely investigated, but the impacts of different woodland types on hydrological processes within a peri-urban catchment mosaic are poorly understood. This paper investigates overland flow generation processes in three different types of woodland in a small (6.2 km2) catchment in central Portugal that has undergone strong urban development over the past 50 years. A semi-natural oak stand and a sparse eucalyptus stand on partly abandoned peri-urban land and a dense eucalyptus plantation were each instrumented with three 16 m2 runoff plots and 15 throughfall gauges, which were monitored at c. 1- to 2-week intervals over two hydrological years. In addition, surface soil moisture content (0-5 cm) and hydrophobicity (0-2 cm, 2-5 cm and 5-7 cm) were measured at the same time as overland flow and throughfall. Although all three woodland types produced relatively little overland flow (<3% of the incident rainfall overall), the dense eucalypt stand produced twice as much overland flow as the sparse eucalypt and oak woodland types. This contrast in overland flow can be attributed to infiltration-excess processes operating in storms following dry antecedent weather when severe hydrophobicity was widespread in the dense eucalypt plantation, whereas it was of moderate and low severity and less widespread in the sparse eucalypt and oak woodlands, respectively. In contrast, under wet conditions greater (albeit still small) percentages of overland flow were produced in oak woodland than in the two eucalypt plantations; this was probably linked to saturation-excess overland flow being generated more readily at the oak site as a result of its shallower soil. Differences in water retention in surface depressions affected overland flow generation and downslope flow transport. Implications of the seasonal differentials in overland flow generation between the three distinct woodland types for the hydrological response of peri-urban catchments are addressed.

Aptamer-Functionalized Fluorescent Silica Nanoparticles for Highly Sensitive Detection of Leukemia Cells

NASA Astrophysics Data System (ADS)

Tan, Juntao; Yang, Nuo; Hu, Zixi; Su, Jing; Zhong, Jianhong; Yang, Yang; Yu, Yating; Zhu, Jianmeng; Xue, Dabin; Huang, Yingying; Lai, Zongqiang; Huang, Yong; Lu, Xiaoling; Zhao, Yongxiang

2016-06-01

A simple, highly sensitive method to detect leukemia cells has been developed based on aptamer-modified fluorescent silica nanoparticles (FSNPs). In this strategy, the amine-labeled Sgc8 aptamer was conjugated to carboxyl-modified FSNPs via amide coupling between amino and carboxyl groups. Sensitivity and specificity of Sgc8-FSNPs were assessed using flow cytometry and fluorescence microscopy. These results showed that Sgc8-FSNPs detected leukemia cells with high sensitivity and specificity. Aptamer-modified FSNPs hold promise for sensitive and specific detection of leukemia cells. Changing the aptamer may allow the FSNPs to detect other types of cancer cells.

Proliferating fibroblasts and HeLa cells co-cultured in vitro reciprocally influence growth patterns, protein expression, chromatin features and cell survival.

PubMed

Delinasios, John G; Angeli, Flora; Koumakis, George; Kumar, Shant; Kang, Wen-Hui; Sica, Gigliola; Iacopino, Fortunata; Lama, Gina; Lamprecht, Sergio; Sigal-Batikoff, Ina; Tsangaris, George T; Farfarelos, Christos D; Farfarelos, Maria C; Vairaktaris, Eleftherios; Vassiliou, Stavros; Delinasios, George J

2015-04-01

to identify biological interactions between proliferating fibroblasts and HeLa cells in vitro. Fibroblasts were isolated from both normal and tumour human tissues. Coverslip co-cultures of HeLa and fibroblasts in various ratios with medium replacement every 48 h were studied using fixed cell staining with dyes such as Giemsa and silver staining, with immunochemistry for Ki-67 and E-cadherin, with dihydrofolate reductase (DHFR) enzyme reaction, as well as live cell staining for non-specific esterases and lipids. Other techniques included carmine cell labeling, autoradiography and apoptosis assessment. Under conditions of feeding and cell: cell ratios allowing parallel growth of human fibroblasts and HeLa cells, co-cultured for up to 20 days, a series of phenomena occur consecutively: profound affinity between the two cell types and exchange of small molecules; encircling of the HeLa colonies by the fibroblasts and enhanced growth of both cell types at their contact areas; expression of carbonic anhydrase in both cell types and high expression of non-specific esterases and cytoplasmic argyrophilia in the surrounding fibroblasts; intense production and secretion of lipid droplets by the surrounding fibroblasts; development of a complex net of argyrophilic projections of the fibroblasts; E-cadherin expression in the HeLa cells; from the 10th day onwards, an increasing detachment of batches of HeLa cells at the peripheries of colonies and appearance of areas with many multi-nucleated and apoptotic HeLa cells, and small HeLa fragments; from the 17th day, appearance of fibroblasts blocked at the G2-M phase. Co-cultures at approximately 17-20 days display a cell-cell fight with foci of (a) sparse growth of both cell types, (b) overgrowth of the fibroblasts and (c) regrowth of HeLa in small colonies. These results indicate that during their interaction with HeLa cells in vitro, proliferating fibroblasts can be activated against HeLa. This type of activation is not observed if fibroblast proliferation is blocked by contact inhibition of growth at confluency, or by omitting replacement of the nutrient medium. The present observations show that: (a) interaction between proliferating fibroblasts and HeLa cells in vitro drastically influences each other's protein expression, growth pattern, chromatin features and survival; (b) these functions depend on the fibroblast/HeLa ratio, cell topology (cell-cell contact and the architectural pattern developed during co-culture) and frequent medium change, as prerequisites for fibroblast proliferation; (c) this co-culture model is useful in the study of the complex processes within the tumour microenvironment, as well as the in vitro reproduction and display of several phenomena conventionally seen in tumour cytological sections, such as desmoplasia, apoptosis, nuclear abnormalities; and (d) overgrown fibroblasts adhering to the boundaries of HeLa colonies produce and secrete lipid droplets. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Multiparameter Cell Cycle Analysis.

PubMed

Jacobberger, James W; Sramkoski, R Michael; Stefan, Tammy; Woost, Philip G

2018-01-01

Cell cycle cytometry and analysis are essential tools for studying cells of model organisms and natural populations (e.g., bone marrow). Methods have not changed much for many years. The simplest and most common protocol is DNA content analysis, which is extensively published and reviewed. The next most common protocol, 5-bromo-2-deoxyuridine S phase labeling detected by specific antibodies, is also well published and reviewed. More recently, S phase labeling using 5'-ethynyl-2'-deoxyuridine incorporation and a chemical reaction to label substituted DNA has been established as a basic, reliable protocol. Multiple antibody labeling to detect epitopes on cell cycle regulated proteins, which is what this chapter is about, is the most complex of these cytometric cell cycle assays, requiring knowledge of the chemistry of fixation, the biochemistry of antibody-antigen reactions, and spectral compensation. However, because this knowledge is relatively well presented methodologically in many papers and reviews, this chapter will present a minimal Methods section for one mammalian cell type and an extended Notes section, focusing on aspects that are problematic or not well described in the literature. Most of the presented work involves how to segment the data to produce a complete, progressive, and compartmentalized cell cycle analysis from early G1 to late mitosis (telophase). A more recent development, using fluorescent proteins fused with proteins or peptides that are degraded by ubiquitination during specific periods of the cell cycle, termed "Fucci" (fluorescent, ubiquitination-based cell cycle indicators) provide an analysis similar in concept to multiple antibody labeling, except in this case cells can be analyzed while living and transgenic organisms can be created to perform cell cycle analysis ex or in vivo (Sakaue-Sawano et al., Cell 132:487-498, 2007). This technology will not be discussed.

Prediction of siRNA potency using sparse logistic regression.

PubMed

Hu, Wei; Hu, John

2014-06-01

RNA interference (RNAi) can modulate gene expression at post-transcriptional as well as transcriptional levels. Short interfering RNA (siRNA) serves as a trigger for the RNAi gene inhibition mechanism, and therefore is a crucial intermediate step in RNAi. There have been extensive studies to identify the sequence characteristics of potent siRNAs. One such study built a linear model using LASSO (Least Absolute Shrinkage and Selection Operator) to measure the contribution of each siRNA sequence feature. This model is simple and interpretable, but it requires a large number of nonzero weights. We have introduced a novel technique, sparse logistic regression, to build a linear model using single-position specific nucleotide compositions which has the same prediction accuracy of the linear model based on LASSO. The weights in our new model share the same general trend as those in the previous model, but have only 25 nonzero weights out of a total 84 weights, a 54% reduction compared to the previous model. Contrary to the linear model based on LASSO, our model suggests that only a few positions are influential on the efficacy of the siRNA, which are the 5' and 3' ends and the seed region of siRNA sequences. We also employed sparse logistic regression to build a linear model using dual-position specific nucleotide compositions, a task LASSO is not able to accomplish well due to its high dimensional nature. Our results demonstrate the superiority of sparse logistic regression as a technique for both feature selection and regression over LASSO in the context of siRNA design.

Flotation of mastitis pathogens with cream from subclinically infected quarters. Prospects for developing a cream-rising test for detecting mastitis caused by major mastitis pathogens.

PubMed

Sandholm, M; Kaartinen, L; Hyvönen, P; Veijalainen, K; Kuosa, P L

1989-02-01

Bacterial isolates, originating from 36 subclinically infected quarter milk samples, were labelled with 75Se and checked for cream-rising at various temperatures in a system analogous to the ABR test ("Abortus Bang Ringprobe"; the cream-rising test based on stained brucella organisms for detection of brucellosis). Diagnostic specificity and sensitivity were analyzed in experiments where labelled bacterial isolates were mixed with a number of quarter milk samples with known bacteriological status as well as samples from healthy control quarters. Creaming at 37 degrees C resulted in specific "recognization" as the bacterial isolates showed preferential flotation in the milk samples from which they had been isolated as well as is milk samples harbouring the same bacterial species. At lower creaming temperatures, the specificity was lost since all the isolates became concentrated in the cream phase irrespective of the milk sample. When comparing the specific recognization by cream of the respective bacteria, bacterial species vary: The prospects for developing diagnostic cream-rising tests for Streptococcus agalactiae, Staphylococcus aureus and Escherichia coli seems promising, but less so for coagulase-negative staphylococci, Streptococcus dysgalactiae, and Streptococcus uberis. The mechanism behind the cream-rising of labelled bacteria at 37 degrees C seems to lie in specific fat globule membrane-bound immunity of IgA type. Therefore the milk fat globules from chronically infected quarters function as absorbents for the respective isolates. Flotation of bacteria with cream indicates an in vivo mechanism enabling bacteria to invade the upper parts of milk ducts within the udder.(ABSTRACT TRUNCATED AT 250 WORDS)

Inferring product healthfulness from nutrition labelling. The influence of reference points.

PubMed

van Herpen, Erica; Hieke, Sophie; van Trijp, Hans C M

2014-01-01

Despite considerable research on nutrition labelling, it has proven difficult to find a front-of-pack label which is informative about product healthfulness across various situations. This study examines the ability of different types of nutrition labelling schemes (multiple traffic light label, nutrition table, GDA, logo) to communicate product healthfulness (a) across different product categories, (b) between options from the same product category, and (c) when viewed in isolation and in comparison with another product. Results of two experiments in Germany and The Netherlands show that a labelling scheme with reference point information at the nutrient level (e.g., the traffic light label) can achieve all three objectives. Although other types of labelling schemes are also capable of communicating healthfulness, labelling schemes lacking reference point information (e.g., nutrition tables) are less effective when no comparison product is available, and labelling schemes based on overall product healthfulness within the category (e.g., logos) can diminish consumers' ability to differentiate between categories, leading to a potential misinterpretation of product healthfulness. None of the labels affected food preferences.