Sense and sensitivity in bioprocessing-detecting cellular metabolites with biosensors.

PubMed

Dekker, Linda; Polizzi, Karen M

2017-10-01

Biosensors use biological elements to detect or quantify an analyte of interest. In bioprocessing, biosensors are employed to monitor key metabolites. There are two main types: fully biological systems or biological recognition coupled with physical/chemical detection. New developments in chemical biosensors include multiplexed detection using microfluidics. Synthetic biology can be used to engineer new biological biosensors with improved characteristics. Although there have been few biosensors developed for bioprocessing thus far, emerging trends can be applied in the future. A range of new platform technologies will enable rapid engineering of new biosensors based on transcriptional activation, riboswitches, and Förster Resonance Energy Transfer. However, translation to industry remains a challenge and more research into the robustness biosensors at scale is needed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fluorogenic PNA probes

PubMed Central

2018-01-01

Fluorogenic oligonucleotide probes that can produce a change in fluorescence signal upon binding to specific biomolecular targets, including nucleic acids as well as non-nucleic acid targets, such as proteins and small molecules, have applications in various important areas. These include diagnostics, drug development and as tools for studying biomolecular interactions in situ and in real time. The probes usually consist of a labeled oligonucleotide strand as a recognition element together with a mechanism for signal transduction that can translate the binding event into a measurable signal. While a number of strategies have been developed for the signal transduction, relatively little attention has been paid to the recognition element. Peptide nucleic acids (PNA) are DNA mimics with several favorable properties making them a potential alternative to natural nucleic acids for the development of fluorogenic probes, including their very strong and specific recognition and excellent chemical and biological stabilities in addition to their ability to bind to structured nucleic acid targets. In addition, the uncharged backbone of PNA allows for other unique designs that cannot be performed with oligonucleotides or analogues with negatively-charged backbones. This review aims to introduce the principle, showcase state-of-the-art technologies and update recent developments in the areas of fluorogenic PNA probes during the past 20 years. PMID:29507634

[Bacteriophage λ: electrostatic properties of the genome and its elements].

PubMed

Krutinina, G G; Krutinin, E A; Kamzolova, S G; Osypov, A A

2015-01-01

Bacteriophage λ is a classical model object in molecular biology, but little is still known on the physical properties of its DNA and regulatory elements. A study was made of the electrostatic properties of phage λ DNA and regulatory elements. A global electrostatic potential distribution along the phage genome was found to be nonuniform with main regulatory elements being located in a limited region with a high potential. The RNA polymerase binding frequency on the linearized phage chromosome directly correlates with its local potential. Strong promoters of the phage and its host Escherichia coli have distinct electrostatic upstream elements, which differ in nucleotide sequence. Attachment and recombination sites of phage λ and its host have a higher potential, which possibly facilitates their recognition by integrase. Phage λ and host Rho-independent terminators have a symmetrical M-shaped potential profile, which only slightly depends on the annotated terminator palindrome length, and occur in a region with a substantially higher potential, which may cause polymerase retention, facilitating the formation of a terminator hairpin in RNA. It was concluded that virtually all elements of phage λ genome have potential distribution specifics, which are related to their structural properties and may play a role in their biological function. The global potential distribution along the phage genome reflects the architecture of the regulation of its transcription and integration in the host genome.

Evolutionary plasticity of the NHL domain underlies distinct solutions to RNA recognition.

PubMed

Kumari, Pooja; Aeschimann, Florian; Gaidatzis, Dimos; Keusch, Jeremy J; Ghosh, Pritha; Neagu, Anca; Pachulska-Wieczorek, Katarzyna; Bujnicki, Janusz M; Gut, Heinz; Großhans, Helge; Ciosk, Rafal

2018-04-19

RNA-binding proteins regulate all aspects of RNA metabolism. Their association with RNA is mediated by RNA-binding domains, of which many remain uncharacterized. A recently reported example is the NHL domain, found in prominent regulators of cellular plasticity like the C. elegans LIN-41. Here we employ an integrative approach to dissect the RNA specificity of LIN-41. Using computational analysis, structural biology, and in vivo studies in worms and human cells, we find that a positively charged pocket, specific to the NHL domain of LIN-41 and its homologs (collectively LIN41), recognizes a stem-loop RNA element, whose shape determines the binding specificity. Surprisingly, the mechanism of RNA recognition by LIN41 is drastically different from that of its more distant relative, the fly Brat. Our phylogenetic analysis suggests that this reflects a rapid evolution of the domain, presenting an interesting example of a conserved protein fold that acquired completely different solutions to RNA recognition.

Developments in Molecular Recognition and Sensing at Interfaces

PubMed Central

Ariga, Katsuhiko; Hill, Jonathan P.; Endo, Hiroshi

2007-01-01

In biological systems, molecular recognition events occur mostly within interfacial environments such as at membrane surfaces, enzyme reaction sites, or at the interior of the DNA double helix. Investigation of molecular recognition at model interfaces provides great insights into biological phenomena. Molecular recognition at interfaces not only has relevance to biological systems but is also important for modern applications such as high sensitivity sensors. Selective binding of guest molecules in solution to host molecules located at solid surfaces is crucial for electronic or photonic detection of analyte substances. In response to these demands, molecular recognition at interfaces has been investigated extensively during the past two decades using Langmuir monolayers, self-assembled monolayers, and lipid assemblies as recognition media. In this review, advances of molecular recognition at interfaces are briefly summarized.

Structural insight into RNA recognition motifs: versatile molecular Lego building blocks for biological systems.

PubMed

Muto, Yutaka; Yokoyama, Shigeyuki

2012-01-01

'RNA recognition motifs (RRMs)' are common domain-folds composed of 80-90 amino-acid residues in eukaryotes, and have been identified in many cellular proteins. At first they were known as RNA binding domains. Through discoveries over the past 20 years, however, the RRMs have been shown to exhibit versatile molecular recognition activities and to behave as molecular Lego building blocks to construct biological systems. Novel RNA/protein recognition modes by RRMs are being identified, and more information about the molecular recognition by RRMs is becoming available. These RNA/protein recognition modes are strongly correlated with their biological significance. In this review, we would like to survey the recent progress on these versatile molecular recognition modules. Copyright © 2012 John Wiley & Sons, Ltd.

Structural hierarchy controlling dimerization and target DNA recognition in the AHR transcriptional complex.

PubMed

Seok, Seung-Hyeon; Lee, Woojong; Jiang, Li; Molugu, Kaivalya; Zheng, Aiping; Li, Yitong; Park, Sanghyun; Bradfield, Christopher A; Xing, Yongna

2017-05-23

The aryl hydrocarbon receptor (AHR) belongs to the PAS (PER-ARNT-SIM) family transcription factors and mediates broad responses to numerous environmental pollutants and cellular metabolites, modulating diverse biological processes from adaptive metabolism, acute toxicity, to normal physiology of vascular and immune systems. The AHR forms a transcriptionally active heterodimer with ARNT (AHR nuclear translocator), which recognizes the dioxin response element (DRE) in the promoter of downstream genes. We determined the crystal structure of the mammalian AHR-ARNT heterodimer in complex with the DRE, in which ARNT curls around AHR into a highly intertwined asymmetric architecture, with extensive heterodimerization interfaces and AHR interdomain interactions. Specific recognition of the DRE is determined locally by the DNA-binding residues, which discriminates it from the closely related hypoxia response element (HRE), and is globally affected by the dimerization interfaces and interdomain interactions. Changes at the interdomain interactions caused either AHR constitutive nuclear localization or failure to translocate to nucleus, underlying an allosteric structural pathway for mediating ligand-induced exposure of nuclear localization signal. These observations, together with the global higher flexibility of the AHR PAS-A and its loosely packed structural elements, suggest a dynamic structural hierarchy for complex scenarios of AHR activation induced by its diverse ligands.

Structural hierarchy controlling dimerization and target DNA recognition in the AHR transcriptional complex

PubMed Central

Lee, Woojong; Jiang, Li; Molugu, Kaivalya; Zheng, Aiping; Li, Yitong; Park, Sanghyun; Bradfield, Christopher A.; Xing, Yongna

2017-01-01

The aryl hydrocarbon receptor (AHR) belongs to the PAS (PER-ARNT-SIM) family transcription factors and mediates broad responses to numerous environmental pollutants and cellular metabolites, modulating diverse biological processes from adaptive metabolism, acute toxicity, to normal physiology of vascular and immune systems. The AHR forms a transcriptionally active heterodimer with ARNT (AHR nuclear translocator), which recognizes the dioxin response element (DRE) in the promoter of downstream genes. We determined the crystal structure of the mammalian AHR–ARNT heterodimer in complex with the DRE, in which ARNT curls around AHR into a highly intertwined asymmetric architecture, with extensive heterodimerization interfaces and AHR interdomain interactions. Specific recognition of the DRE is determined locally by the DNA-binding residues, which discriminates it from the closely related hypoxia response element (HRE), and is globally affected by the dimerization interfaces and interdomain interactions. Changes at the interdomain interactions caused either AHR constitutive nuclear localization or failure to translocate to nucleus, underlying an allosteric structural pathway for mediating ligand-induced exposure of nuclear localization signal. These observations, together with the global higher flexibility of the AHR PAS-A and its loosely packed structural elements, suggest a dynamic structural hierarchy for complex scenarios of AHR activation induced by its diverse ligands. PMID:28396409

Structural hierarchy controlling dimerization and target DNA recognition in the AHR transcriptional complex

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

Seok, Seung-Hyeon; Lee, Woojong; Jiang, Li

he aryl hydrocarbon receptor (AHR) belongs to the PAS (PER-ARNT-SIM) family transcription factors and mediates broad responses to numerous environmental pollutants and cellular metabolites, modulating diverse biological processes from adaptive metabolism, acute toxicity, to normal physiology of vascular and immune systems. The AHR forms a transcriptionally active heterodimer with ARNT (AHR nuclear translocator), which recognizes the dioxin response element (DRE) in the promoter of downstream genes. We determined the crystal structure of the mammalian AHR–ARNT heterodimer in complex with the DRE, in which ARNT curls around AHR into a highly intertwined asymmetric architecture, with extensive heterodimerization interfaces and AHR interdomainmore » interactions. Specific recognition of the DRE is determined locally by the DNA-binding residues, which discriminates it from the closely related hypoxia response element (HRE), and is globally affected by the dimerization interfaces and interdomain interactions. Changes at the interdomain interactions caused either AHR constitutive nuclear localization or failure to translocate to nucleus, underlying an allosteric structural pathway for mediating ligand-induced exposure of nuclear localization signal. These observations, together with the global higher flexibility of the AHR PAS-A and its loosely packed structural elements, suggest a dynamic structural hierarchy for complex scenarios of AHR activation induced by its diverse ligands.« less

Advancing Peptide-Based Biorecognition Elements for Biosensors Using in-Silico Evolution.

PubMed

Xiao, Xingqing; Kuang, Zhifeng; Slocik, Joseph M; Tadepalli, Sirimuvva; Brothers, Michael; Kim, Steve; Mirau, Peter A; Butkus, Claire; Farmer, Barry L; Singamaneni, Srikanth; Hall, Carol K; Naik, Rajesh R

2018-05-25

Sensors for human health and performance monitoring require biological recognition elements (BREs) at device interfaces for the detection of key molecular biomarkers that are measurable biological state indicators. BREs, including peptides, antibodies, and nucleic acids, bind to biomarkers in the vicinity of the sensor surface to create a signal proportional to the biomarker concentration. The discovery of BREs with the required sensitivity and selectivity to bind biomarkers at low concentrations remains a fundamental challenge. In this study, we describe an in-silico approach to evolve higher sensitivity peptide-based BREs for the detection of cardiac event marker protein troponin I (cTnI) from a previously identified BRE as the parental affinity peptide. The P2 affinity peptide, evolved using our in-silico method, was found to have ∼16-fold higher affinity compared to the parent BRE and ∼10 fM (0.23 pg/mL) limit of detection. The approach described here can be applied towards designing BREs for other biomarkers for human health monitoring.

Recognition of Double Stranded RNA by Guanidine-Modified Peptide Nucleic Acids (GPNA)

PubMed Central

Gupta, Pankaj; Muse, Oluwatoyosi; Rozners, Eriks

2011-01-01

Double helical RNA has become an attractive target for molecular recognition because many non-coding RNAs play important roles in control of gene expression. Recently, we discovered that short peptide nucleic acids (PNA) bind strongly and sequence selectively to a homopurine tract of double helical RNA via triple helix formation. Herein we tested if the molecular recognition of RNA can be enhanced by α-guanidine modification of PNA. Our study was motivated by the discovery of Ly and co-workers that the guanidine modification greatly enhances the cellular delivery of PNA. Isothermal titration calorimetry showed that the guanidine-modified PNA (GPNA) had reduced affinity and sequence selectivity for triple helical recognition of RNA. The data suggested that in contrast to unmodified PNA, which formed a 1:1 PNA-RNA triple helix, GPNA preferred a 2:1 GPNA-RNA triplex-invasion complex. Nevertheless, promising results were obtained for recognition of biologically relevant double helical RNA. Consistent with enhanced strand invasion ability, GPNA derived from D-arginine recognized the transactivation response element (TAR) of HIV-1 with high affinity and sequence selectivity, presumably via Watson-Crick duplex formation. On the other hand, strong and sequence selective triple helices were formed by unmodified and nucelobase-modified PNAs and the purine rich strand of bacterial A-site. These results suggest that appropriate chemical modifications of PNA may enhance molecular recognition of complex non-coding RNAs. PMID:22146072

Metal oxide nanosensors using polymeric membranes, enzymes and antibody receptors as ion and molecular recognition elements.

PubMed

Willander, Magnus; Khun, Kimleang; Ibupoto, Zafar Hussain

2014-05-16

The concept of recognition and biofunctionality has attracted increasing interest in the fields of chemistry and material sciences. Advances in the field of nanotechnology for the synthesis of desired metal oxide nanostructures have provided a solid platform for the integration of nanoelectronic devices. These nanoelectronics-based devices have the ability to recognize molecular species of living organisms, and they have created the possibility for advanced chemical sensing functionalities with low limits of detection in the nanomolar range. In this review, various metal oxides, such as ZnO-, CuO-, and NiO-based nanosensors, are described using different methods (receptors) of functionalization for molecular and ion recognition. These functionalized metal oxide surfaces with a specific receptor involve either a complex formation between the receptor and the analyte or an electrostatic interaction during the chemical sensing of analytes. Metal oxide nanostructures are considered revolutionary nanomaterials that have a specific surface for the immobilization of biomolecules with much needed orientation, good conformation and enhanced biological activity which further improve the sensing properties of nanosensors. Metal oxide nanostructures are associated with certain unique optical, electrical and molecular characteristics in addition to unique functionalities and surface charge features which shows attractive platforms for interfacing biorecognition elements with effective transducing properties for signal amplification. There is a great opportunity in the near future for metal oxide nanostructure-based miniaturization and the development of engineering sensor devices.

Automated Recognition of RNA Structure Motifs by Their SHAPE Data Signatures.

PubMed

Radecki, Pierce; Ledda, Mirko; Aviran, Sharon

2018-06-14

High-throughput structure profiling (SP) experiments that provide information at nucleotide resolution are revolutionizing our ability to study RNA structures. Of particular interest are RNA elements whose underlying structures are necessary for their biological functions. We previously introduced patteRNA , an algorithm for rapidly mining SP data for patterns characteristic of such motifs. This work provided a proof-of-concept for the detection of motifs and the capability of distinguishing structures displaying pronounced conformational changes. Here, we describe several improvements and automation routines to patteRNA . We then consider more elaborate biological situations starting with the comparison or integration of results from searches for distinct motifs and across datasets. To facilitate such analyses, we characterize patteRNA ’s outputs and describe a normalization framework that regularizes results. We then demonstrate that our algorithm successfully discerns between highly similar structural variants of the human immunodeficiency virus type 1 (HIV-1) Rev response element (RRE) and readily identifies its exact location in whole-genome structure profiles of HIV-1. This work highlights the breadth of information that can be gleaned from SP data and broadens the utility of data-driven methods as tools for the detection of novel RNA elements.

The Use of NMR to Study Transient Carbohydrate-Protein Interactions.

PubMed

Nieto, Pedro M

2018-01-01

Carbohydrates are biologically ubiquitous and are essential to the existence of all known living organisms. Although they are better known for their role as energy sources (glucose/glycogen or starch) or structural elements (chitin or cellulose), carbohydrates also participate in the recognition events of molecular recognition processes. Such interactions with other biomolecules (nucleic acids, proteins, and lipids) are fundamental to life and disease. This review focuses on the application of NMR methods to understand at the atomic level the mechanisms by which sugar molecules can be recognized by proteins to form complexes, creating new entities with different properties to those of the individual component molecules. These processes have recently gained attention as new techniques have been developed, while at the same time old techniques have been reinvented and adapted to address newer emerging problems.

Neonatal Recognition Processes and Attachment: The Masking Experiment.

ERIC Educational Resources Information Center

Cassel, Thomas Z. K.; Sander, Louis W.

This research project was designed to determine whether 1-week-old neonates would indicate biological recognition of their mothers. Biological recognition is defined as the particular configuration of sensory, kinesthetic, and motor cues and the temporal patterning of these cues which characterizes infants' exchange processes with their…

Low Temperature Performance of High-Speed Neural Network Circuits

NASA Technical Reports Server (NTRS)

Duong, T.; Tran, M.; Daud, T.; Thakoor, A.

1995-01-01

Artificial neural networks, derived from their biological counterparts, offer a new and enabling computing paradigm specially suitable for such tasks as image and signal processing with feature classification/object recognition, global optimization, and adaptive control. When implemented in fully parallel electronic hardware, it offers orders of magnitude speed advantage. Basic building blocks of the new architecture are the processing elements called neurons implemented as nonlinear operational amplifiers with sigmoidal transfer function, interconnected through weighted connections called synapses implemented using circuitry for weight storage and multiply functions either in an analog, digital, or hybrid scheme.

The human RNA-binding protein and E3 ligase MEX-3C binds the MEX-3-recognition element (MRE) motif with high affinity.

PubMed

Yang, Lingna; Wang, Chongyuan; Li, Fudong; Zhang, Jiahai; Nayab, Anam; Wu, Jihui; Shi, Yunyu; Gong, Qingguo

2017-09-29

MEX-3 is a K-homology (KH) domain-containing RNA-binding protein first identified as a translational repressor in Caenorhabditis elegans , and its four orthologs (MEX-3A-D) in human and mouse were subsequently found to have E3 ubiquitin ligase activity mediated by a RING domain and critical for RNA degradation. Current evidence implicates human MEX-3C in many essential biological processes and suggests a strong connection with immune diseases and carcinogenesis. The highly conserved dual KH domains in MEX-3 proteins enable RNA binding and are essential for the recognition of the 3'-UTR and post-transcriptional regulation of MEX-3 target transcripts. However, the molecular mechanisms of translational repression and the consensus RNA sequence recognized by the MEX-3C KH domain are unknown. Here, using X-ray crystallography and isothermal titration calorimetry, we investigated the RNA-binding activity and selectivity of human MEX-3C dual KH domains. Our high-resolution crystal structures of individual KH domains complexed with a noncanonical U-rich and a GA-rich RNA sequence revealed that the KH1/2 domains of human MEX-3C bound MRE10, a 10-mer RNA (5'-CAGAGUUUAG-3') consisting of an eight-nucleotide MEX-3-recognition element (MRE) motif, with high affinity. Of note, we also identified a consensus RNA motif recognized by human MEX-3C. The potential RNA-binding sites in the 3'-UTR of the human leukocyte antigen serotype ( HLA-A2 ) mRNA were mapped with this RNA-binding motif and further confirmed by fluorescence polarization. The binding motif identified here will provide valuable information for future investigations of the functional pathways controlled by human MEX-3C and for predicting potential mRNAs regulated by this enzyme. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Application of a Nanostructured Enzymatic Biosensor Based on Fullerene and Gold Nanoparticles to Polyphenol Detection.

PubMed

Tortolini, Cristina; Sanzò, Gabriella; Antiochia, Riccarda; Mazzei, Franco; Favero, Gabriele

2017-01-01

Electrochemical biosensors provide an attractive means of analyzing the content of a biological sample due to the direct conversion of a biological event to an electronic signal. The signal transduction and the general performance of electrochemical biosensors are often determined by the surface architectures that connect the sensing element to the biological sample at the nanometer scale. The most common surface modification techniques, the various electrochemical transduction mechanisms, and the choice of the recognition receptor molecules all influence the ultimate sensitivity of the sensor. We show herein a novel electrochemical biosensing platform based on the coupling of two different nanostructured materials (gold nanoparticles and fullerenols) displaying interesting electrochemical features. The use of these nanomaterials improved the electrochemical performance of the proposed biosensor.An application of the nanostructured enzyme-based biosensor has been developed for evaluating the detection of polyphenols either in buffer solution or in real wine samples.

Recognizing Biological Motion and Emotions from Point-Light Displays in Autism Spectrum Disorders

PubMed Central

Nackaerts, Evelien; Wagemans, Johan; Helsen, Werner; Swinnen, Stephan P.; Wenderoth, Nicole; Alaerts, Kaat

2012-01-01

One of the main characteristics of Autism Spectrum Disorder (ASD) are problems with social interaction and communication. Here, we explored ASD-related alterations in ‘reading’ body language of other humans. Accuracy and reaction times were assessed from two observational tasks involving the recognition of ‘biological motion’ and ‘emotions’ from point-light displays (PLDs). Eye movements were recorded during the completion of the tests. Results indicated that typically developed-participants were more accurate than ASD-subjects in recognizing biological motion or emotions from PLDs. No accuracy differences were revealed on two control-tasks (involving the indication of color-changes in the moving point-lights). Group differences in reaction times existed on all tasks, but effect sizes were higher for the biological and emotion recognition tasks. Biological motion recognition abilities were related to a person’s ability to recognize emotions from PLDs. However, ASD-related atypicalities in emotion recognition could not entirely be attributed to more basic deficits in biological motion recognition, suggesting an additional ASD-specific deficit in recognizing the emotional dimension of the point light displays. Eye movements were assessed during the completion of tasks and results indicated that ASD-participants generally produced more saccades and shorter fixation-durations compared to the control-group. However, especially for emotion recognition, these altered eye movements were associated with reductions in task-performance. PMID:22970227

Recognizing biological motion and emotions from point-light displays in autism spectrum disorders.

PubMed

Nackaerts, Evelien; Wagemans, Johan; Helsen, Werner; Swinnen, Stephan P; Wenderoth, Nicole; Alaerts, Kaat

2012-01-01

One of the main characteristics of Autism Spectrum Disorder (ASD) are problems with social interaction and communication. Here, we explored ASD-related alterations in 'reading' body language of other humans. Accuracy and reaction times were assessed from two observational tasks involving the recognition of 'biological motion' and 'emotions' from point-light displays (PLDs). Eye movements were recorded during the completion of the tests. Results indicated that typically developed-participants were more accurate than ASD-subjects in recognizing biological motion or emotions from PLDs. No accuracy differences were revealed on two control-tasks (involving the indication of color-changes in the moving point-lights). Group differences in reaction times existed on all tasks, but effect sizes were higher for the biological and emotion recognition tasks. Biological motion recognition abilities were related to a person's ability to recognize emotions from PLDs. However, ASD-related atypicalities in emotion recognition could not entirely be attributed to more basic deficits in biological motion recognition, suggesting an additional ASD-specific deficit in recognizing the emotional dimension of the point light displays. Eye movements were assessed during the completion of tasks and results indicated that ASD-participants generally produced more saccades and shorter fixation-durations compared to the control-group. However, especially for emotion recognition, these altered eye movements were associated with reductions in task-performance.

A virus-MIPs fluorescent sensor based on FRET for highly sensitive detection of JEV.

PubMed

Liang, Caishuang; Wang, Huan; He, Kui; Chen, Chunyan; Chen, Xiaoming; Gong, Hang; Cai, Changqun

2016-11-01

Major stumbling blocks in the recognition and detection of virus are the unstable biological recognition element or the complex detection means. Here a fluorescent sensor based on virus-molecular imprinted polymers (virus-MIPs) was designed for specific recognition and highly sensitive detection of Japanese encephalitis virus (JEV). The virus-MIPs were anchored on the surface of silica microspheres modified by fluorescent dye, pyrene-1-carboxaldehyde (PC). The fluorescence intensity of PC can be enhanced by the principle of fluorescence resonance energy transfer (FRET), where virus acted as energy donor and PC acted as energy acceptor. The enhanced fluorescence intensity was proportional to the concentration of virus in the range of 24-960pM, with a limit of detection (LOD, 3σ) of 9.6pM, and the relative standard deviation was 1.99%. In additional, the specificity study confirmed the resultant MIPs has high-selectivity for JEV. This sensor would become a new key for the detection of virus because of its high sensitive, simple operation, high stability and low cost. Copyright © 2016. Published by Elsevier B.V.

Scientific names of organisms: attribution, rights, and licensing

PubMed Central

2014-01-01

Background As biological disciplines extend into the ‘big data’ world, they will need a names-based infrastructure to index and interconnect distributed data. The infrastructure must have access to all names of all organisms if it is to manage all information. Those who compile lists of species hold different views as to the intellectual property rights that apply to the lists. This creates uncertainty that impedes the development of a much-needed infrastructure for sharing biological data in the digital world. Findings The laws in the United States of America and European Union are consistent with the position that scientific names of organisms and their compilation in checklists, classifications or taxonomic revisions are not subject to copyright. Compilations of names, such as classifications or checklists, are not creative in the sense of copyright law. Many content providers desire credit for their efforts. Conclusions A ‘blue list’ identifies elements of checklists, classifications and monographs to which intellectual property rights do not apply. To promote sharing, authors of taxonomic content, compilers, intermediaries, and aggregators should receive citable recognition for their contributions, with the greatest recognition being given to the originating authors. Mechanisms for achieving this are discussed. PMID:24495358

Siderocalin-mediated recognition, sensitization, and cellular uptake of actinides.

PubMed

Allred, Benjamin E; Rupert, Peter B; Gauny, Stacey S; An, Dahlia D; Ralston, Corie Y; Sturzbecher-Hoehne, Manuel; Strong, Roland K; Abergel, Rebecca J

2015-08-18

Synthetic radionuclides, such as the transuranic actinides plutonium, americium, and curium, present severe health threats as contaminants, and understanding the scope of the biochemical interactions involved in actinide transport is instrumental in managing human contamination. Here we show that siderocalin, a mammalian siderophore-binding protein from the lipocalin family, specifically binds lanthanide and actinide complexes through molecular recognition of the ligands chelating the metal ions. Using crystallography, we structurally characterized the resulting siderocalin-transuranic actinide complexes, providing unprecedented insights into the biological coordination of heavy radioelements. In controlled in vitro assays, we found that intracellular plutonium uptake can occur through siderocalin-mediated endocytosis. We also demonstrated that siderocalin can act as a synergistic antenna to sensitize the luminescence of trivalent lanthanide and actinide ions in ternary protein-ligand complexes, dramatically increasing the brightness and efficiency of intramolecular energy transfer processes that give rise to metal luminescence. Our results identify siderocalin as a potential player in the biological trafficking of f elements, but through a secondary ligand-based metal sequestration mechanism. Beyond elucidating contamination pathways, this work is a starting point for the design of two-stage biomimetic platforms for photoluminescence, separation, and transport applications.

Siderocalin-mediated recognition, sensitization, and cellular uptake of actinides

PubMed Central

Allred, Benjamin E.; Rupert, Peter B.; Gauny, Stacey S.; An, Dahlia D.; Ralston, Corie Y.; Sturzbecher-Hoehne, Manuel; Strong, Roland K.; Abergel, Rebecca J.

2015-01-01

Synthetic radionuclides, such as the transuranic actinides plutonium, americium, and curium, present severe health threats as contaminants, and understanding the scope of the biochemical interactions involved in actinide transport is instrumental in managing human contamination. Here we show that siderocalin, a mammalian siderophore-binding protein from the lipocalin family, specifically binds lanthanide and actinide complexes through molecular recognition of the ligands chelating the metal ions. Using crystallography, we structurally characterized the resulting siderocalin–transuranic actinide complexes, providing unprecedented insights into the biological coordination of heavy radioelements. In controlled in vitro assays, we found that intracellular plutonium uptake can occur through siderocalin-mediated endocytosis. We also demonstrated that siderocalin can act as a synergistic antenna to sensitize the luminescence of trivalent lanthanide and actinide ions in ternary protein–ligand complexes, dramatically increasing the brightness and efficiency of intramolecular energy transfer processes that give rise to metal luminescence. Our results identify siderocalin as a potential player in the biological trafficking of f elements, but through a secondary ligand-based metal sequestration mechanism. Beyond elucidating contamination pathways, this work is a starting point for the design of two-stage biomimetic platforms for photoluminescence, separation, and transport applications. PMID:26240330

Metal Oxide Nanosensors Using Polymeric Membranes, Enzymes and Antibody Receptors as Ion and Molecular Recognition Elements

PubMed Central

Willander, Magnus; Khun, Kimleang; Ibupoto, Zafar Hussain

2014-01-01

The concept of recognition and biofunctionality has attracted increasing interest in the fields of chemistry and material sciences. Advances in the field of nanotechnology for the synthesis of desired metal oxide nanostructures have provided a solid platform for the integration of nanoelectronic devices. These nanoelectronics-based devices have the ability to recognize molecular species of living organisms, and they have created the possibility for advanced chemical sensing functionalities with low limits of detection in the nanomolar range. In this review, various metal oxides, such as ZnO-, CuO-, and NiO-based nanosensors, are described using different methods (receptors) of functionalization for molecular and ion recognition. These functionalized metal oxide surfaces with a specific receptor involve either a complex formation between the receptor and the analyte or an electrostatic interaction during the chemical sensing of analytes. Metal oxide nanostructures are considered revolutionary nanomaterials that have a specific surface for the immobilization of biomolecules with much needed orientation, good conformation and enhanced biological activity which further improve the sensing properties of nanosensors. Metal oxide nanostructures are associated with certain unique optical, electrical and molecular characteristics in addition to unique functionalities and surface charge features which shows attractive platforms for interfacing biorecognition elements with effective transducing properties for signal amplification. There is a great opportunity in the near future for metal oxide nanostructure-based miniaturization and the development of engineering sensor devices. PMID:24841244

Biological activity of natural flavonoids as impacted by protein flexibility: an example of flavanones.

PubMed

Ding, Fei; Peng, Wei

2015-04-01

Naturally multifunctional Rutaceae hesperidin and its aglycone hesperetin have a great variety of biopharmaceutical activities, e.g. anti-cancer, anti-inflammatory, antioxidant and antitumor; however, the influence of the molecular structures of hesperidin and hesperetin, and in particular, the structural properties such as flexibility and dynamic features of protein on the biological activities of these bioactive compounds remains ambiguous. In the present study, the biomolecular recognition of crucial biopolymer - albumin from human serum (HSA) with Rutaceae, the recognition differences between HSA-hesperidin and HSA-hesperetin, the key elements that lead to the discrepancies as well as the structural characters of protein to the recognition processes were comparatively examined by employing biophysical approaches at the molecular scale. The results illustrated distinctly that (1) aglycone hesperetin can form stronger noncovalent bonds with HSA and possess higher recognition stability as compared with hesperidin. This phenomenon suggest that the introduction of glycoside structure into flavanone may possibly not be able to increase the noncovalent recognition of flavanone by a biopolymer, and conversely, this event will probably decrease the recognition capacity. (2) Although hesperidin and hesperetin can be located within subdomains IIA and IIIA, respectively, the conformational stability of flavanones in subdomain IIA is greater than subdomain IIIA; as a result, the recognition ability of subdomain IIIA with flavanones is patently lesser than subdomain IIA. These discrepancies likely originate from the unique characteristics of the respective cavity, or more specifically, subdomain IIA is basically a closed space, whereas subdomain IIIA is a semi-open region. Meanwhile, the detailed analyses of root-mean-square fluctuation interpreted the recognition of flavanones by subdomain IIA on HSA, which would evoke larger conformational alterations in several amino acid residues, and the similar phenomenon also resides in subdomain IIIA, which signifies that the flexible characteristics of different binding patches in protein may possess fairly notable effects on the HSA-flavanones recognition. Moreover, the integral structural changes of HSA exhibit some disparities on account of the dissimilarities of recognition capability to the protein-flavanone biointeractions, and all these conclusions received further forceful supports from fluorescence and circular dichroism experiments in solution. Perhaps the work emerged herein could not only help us to better evaluate the bioavailability of natural flavanones with or without glycoside, but to understand the sketches of the three-dimensional structure trait of certain biomacromolecules for the medicinal properties of flavonoids in the human body.

A model for genesis of transcription systems.

PubMed

Burton, Zachary F; Opron, Kristopher; Wei, Guowei; Geiger, James H

2016-01-01

Repeating sequences generated from RNA gene fusions/ligations dominate ancient life, indicating central importance of building structural complexity in evolving biological systems. A simple and coherent story of life on earth is told from tracking repeating motifs that generate α/β proteins, 2-double-Ψ-β-barrel (DPBB) type RNA polymerases (RNAPs), general transcription factors (GTFs), and promoters. A general rule that emerges is that biological complexity that arises through generation of repeats is often bounded by solubility and closure (i.e., to form a pseudo-dimer or a barrel). Because the first DNA genomes were replicated by DNA template-dependent RNA synthesis followed by RNA template-dependent DNA synthesis via reverse transcriptase, the first DNA replication origins were initially 2-DPBB type RNAP promoters. A simplifying model for evolution of promoters/replication origins via repetition of core promoter elements is proposed. The model can explain why Pribnow boxes in bacterial transcription (i.e., (-12)TATAATG(-6)) so closely resemble TATA boxes (i.e., (-31)TATAAAAG(-24)) in archaeal/eukaryotic transcription. The evolution of anchor DNA sequences in bacterial (i.e., (-35)TTGACA(-30)) and archaeal (BRE(up); BRE for TFB recognition element) promoters is potentially explained. The evolution of BRE(down) elements of archaeal promoters is potentially explained.

Action and emotion recognition from point light displays: an investigation of gender differences.

PubMed

Alaerts, Kaat; Nackaerts, Evelien; Meyns, Pieter; Swinnen, Stephan P; Wenderoth, Nicole

2011-01-01

Folk psychology advocates the existence of gender differences in socio-cognitive functions such as 'reading' the mental states of others or discerning subtle differences in body-language. A female advantage has been demonstrated for emotion recognition from facial expressions, but virtually nothing is known about gender differences in recognizing bodily stimuli or body language. The aim of the present study was to investigate potential gender differences in a series of tasks, involving the recognition of distinct features from point light displays (PLDs) depicting bodily movements of a male and female actor. Although recognition scores were considerably high at the overall group level, female participants were more accurate than males in recognizing the depicted actions from PLDs. Response times were significantly higher for males compared to females on PLD recognition tasks involving (i) the general recognition of 'biological motion' versus 'non-biological' (or 'scrambled' motion); or (ii) the recognition of the 'emotional state' of the PLD-figures. No gender differences were revealed for a control test (involving the identification of a color change in one of the dots) and for recognizing the gender of the PLD-figure. In addition, previous findings of a female advantage on a facial emotion recognition test (the 'Reading the Mind in the Eyes Test' (Baron-Cohen, 2001)) were replicated in this study. Interestingly, a strong correlation was revealed between emotion recognition from bodily PLDs versus facial cues. This relationship indicates that inter-individual or gender-dependent differences in recognizing emotions are relatively generalized across facial and bodily emotion perception. Moreover, the tight correlation between a subject's ability to discern subtle emotional cues from PLDs and the subject's ability to basically discriminate biological from non-biological motion provides indications that differences in emotion recognition may - at least to some degree - be related to more basic differences in processing biological motion per se.

Trichomonas vaginalis ribosomal RNA: identification and characterisation of the transcription promoter and terminator sequences.

PubMed

Franco, Bernardo; Hernández, Roberto; López-Villaseñor, Imelda

2012-09-01

Trichomonas vaginalis is a parasitic protozoan of both medical and biological relevance. Transcriptional studies in this organism have focused mainly on type II pol promoters, whereas the elements necessary for transcription by polI or polIII have not been investigated. Here, with the aid of a transient transcription system, we characterised the rDNA intergenic region, defining both the promoter and the terminator sequences required for transcription. We defined the promoter as a compact region of approximately 180 bp. We also identified a potential upstream control element (UCE) that was located 80 bp upstream of the transcription start point (TSP). A transcription termination element was identified within a 34 bp region that was located immediately downstream of the 28S coding sequence. The function of this element depends upon polarity and the presence of both a stretch of uridine residues (U's) and a hairpin structure in the transcript. Our observations provide a strong basis for the study of DNA recognition by the polI transcriptional machinery in this early divergent organism. Copyright © 2012 Elsevier B.V. All rights reserved.

Array of Chemosensitive Resistors with Composites of Gas Chromatography (GC) Materials and Carbon Black for Detection and Recognition of VOCs: A Basic Study

PubMed Central

Wyszynski, Bartosz; Yatabe, Rui; Nakao, Atsuo; Nakatani, Masaya; Oki, Akio; Oka, Hiroaki; Toko, Kiyoshi

2017-01-01

Mimicking the biological olfaction, large odor-sensor arrays can be used to acquire a broad range of chemical information, with a potentially high degree of redundancy, to allow for enhanced control over the sensitivity and selectivity of artificial olfaction systems. The arrays should consist of the largest possible number of individual sensing elements while being miniaturized. Chemosensitive resistors are one of the sensing platforms that have a potential to satisfy these two conditions. In this work we test viability of fabricating a 16-element chemosensitive resistor array for detection and recognition of volatile organic compounds (VOCs). The sensors were fabricated using blends of carbon black and gas chromatography (GC) stationary-phase materials preselected based on their sorption properties. Blends of the selected GC materials with carbon black particles were subsequently coated over chemosensitive resistor devices and the resulting sensors/arrays evaluated in exposure experiments against vapors of pyrrole, benzenal, nonanal, and 2-phenethylamine at 150, 300, 450, and 900 ppb. Responses of the fabricated 16-element array were stable and differed for each individual odorant sample, proving the blends of GC materials with carbon black particles can be effectively used for fabrication of large odor-sensing arrays based on chemosensitive resistors. The obtained results suggest that the proposed sensing devices could be effective in discriminating odor/vapor samples at the sub-ppm level. PMID:28696353

Improved detection sensitivity of γ-aminobutyric acid based on graphene oxide interface on an optical microfiber.

PubMed

Zhou, Jun; Huang, Yunyun; Chen, Chaoyan; Xiao, Aoxiang; Guo, Tuan; Guan, Bai-Ou

2018-05-11

Interfacing bio-recognition elements to optical materials is a longstanding challenge to manufacture sensitive biosensors and inexpensive diagnostic devices. In this work, a graphene oxide (GO) interface has been constructed between silica microfiber and bio-recognition elements to develop an improved γ-aminobutyric acid (GABA) sensing approach. The GO interface, which was located at the site with the strongest evanescent field on the microfiber surface, improved the detection sensitivity by providing a larger platform for more bio-recognition element immobilization, and amplifying surface refractive index change caused by combination between bio-recognition elements and target molecules. Owing to the interface improvement, the microfiber has a three times improved sensitivity of 1.03 nm/log M for GABA detection, and hence a lowest limit of detection of 2.91 × 10-18 M, which is 7 orders of magnitude higher than that without the GO interface. Moreover, the micrometer-sized footprint and non-radioactive nature enable easy implantation in human brains for in vivo applications.

Finite element analysis of dental implants with validation: to what extent can we expect the model to predict biological phenomena? A literature review and proposal for classification of a validation process.

PubMed

Chang, Yuanhan; Tambe, Abhijit Anil; Maeda, Yoshinobu; Wada, Masahiro; Gonda, Tomoya

2018-03-08

A literature review of finite element analysis (FEA) studies of dental implants with their model validation process was performed to establish the criteria for evaluating validation methods with respect to their similarity to biological behavior. An electronic literature search of PubMed was conducted up to January 2017 using the Medical Subject Headings "dental implants" and "finite element analysis." After accessing the full texts, the context of each article was searched using the words "valid" and "validation" and articles in which these words appeared were read to determine whether they met the inclusion criteria for the review. Of 601 articles published from 1997 to 2016, 48 that met the eligibility criteria were selected. The articles were categorized according to their validation method as follows: in vivo experiments in humans (n = 1) and other animals (n = 3), model experiments (n = 32), others' clinical data and past literature (n = 9), and other software (n = 2). Validation techniques with a high level of sufficiency and efficiency are still rare in FEA studies of dental implants. High-level validation, especially using in vivo experiments tied to an accurate finite element method, needs to become an established part of FEA studies. The recognition of a validation process should be considered when judging the practicality of an FEA study.

Pattern recognition neural-net by spatial mapping of biology visual field

NASA Astrophysics Data System (ADS)

Lin, Xin; Mori, Masahiko

2000-05-01

The method of spatial mapping in biology vision field is applied to artificial neural networks for pattern recognition. By the coordinate transform that is called the complex-logarithm mapping and Fourier transform, the input images are transformed into scale- rotation- and shift- invariant patterns, and then fed into a multilayer neural network for learning and recognition. The results of computer simulation and an optical experimental system are described.

Fusing Sensor Paradigms to Acquire Chemical Information: An Integrative Role for Smart Biopolymeric Hydrogels

PubMed Central

Kim, Eunkyoung; Liu, Yi; Ben-Yoav, Hadar; Winkler, Thomas E.; Yan, Kun; Shi, Xiaowen; Shen, Jana; Kelly, Deanna L.; Ghodssi, Reza; Bentley, William E.

2017-01-01

The Information Age transformed our lives but it has had surprisingly little impact on the way chemical information (e.g., from our biological world) is acquired, analyzed and communicated. Sensor systems are poised to change this situation by providing rapid access to chemical information. This access will be enabled by technological advances from various fields: biology enables the synthesis, design and discovery of molecular recognition elements as well as the generation of cell-based signal processors; physics and chemistry are providing nano-components that facilitate the transmission and transduction of signals rich with chemical information; microfabrication is yielding sensors capable of receiving these signals through various modalities; and signal processing analysis enhances the extraction of chemical information. The authors contend that integral to the development of functional sensor systems will be materials that (i) enable the integrative and hierarchical assembly of various sensing components (for chemical recognition and signal transduction) and (ii) facilitate meaningful communication across modalities. It is suggested that stimuli-responsive self-assembling biopolymers can perform such integrative functions, and redox provides modality-spanning communication capabilities. Recent progress toward the development of electrochemical sensors to manage schizophrenia is used to illustrate the opportunities and challenges for enlisting sensors for chemical information processing. PMID:27616350

A highly sensitive and selective fluorescent sensor for detection of sulfide anion based on the steric hindrance effect

NASA Astrophysics Data System (ADS)

Chen, Guanfan; Tang, Mengzhuo; Fu, Xiufang; Cheng, Fenmin; Zou, Xianghua; Wang, Jingpei; Zeng, Rongjin

2018-01-01

Sulfide anions are not only generated as a byproduct from industrial processes but also as a crucial kind of element in biological systems. Therefore, fluorescent probes for detecting sulfide anion with sensitive and selective characters are highly popular. In this study, we report a highly sensitive and selective fluorescent sensor M1 for detection of sulfide anion based on the steric hindrance effect, where the recognition unit, dinitrobenzenesulfonate ester group is linked to aromatic ortho-position in the porphyrin, and correspondingly the fluorescence of fluorescein is efficiently quenched. Compared with the sensors with recognition unit linked to the other aromatic positions, the fluorescent sensor M1 has a lower fluorescence background. Furthermore, the corresponding fluorescence responses (F/F0) of M1 for mercapto amino-acid GSH, Hcy and Cys, were all far lower than the relative fluorescence ratio F/F0 values for S2-. It means that M1 is sensitive and selective to detection of S2-, and has an anti-disturbance ability to the biologically-relevant thiols, GSH, Hcy and Cys, and has the prospect of application in the exact detection of sulfide anions in living organisms. This approach offers some useful insights for realizing sensitive and selective fluorescent turn-on sensing in the detection assays for other analytes.

Global shape recognition is modulated by the spatial distance of local elements--evidence from simultanagnosia.

PubMed

Huberle, Elisabeth; Karnath, Hans-Otto

2006-01-01

Simultanagnosia is a rare deficit that impairs individuals in perceiving several objects at the same time. It is usually observed following bilateral parieto-occipital brain damage. Despite the restrictions in perceiving the global aspect of a scene, processing of individual objects remains unaffected. The mechanisms underlying simultanagnosia are not well understood. Previous findings indicated that the integration of multiple objects into a holistic representation of the environment is not impossible per se, but might depend on the spatial relationship between individual objects. The present study examined the influence of inter-element distances between individual objects on the recognition of global shapes in two patients with simultanagnosia. We presented Navon hierarchical letter stimuli with different inter-element distances between letters at the Local Scale. Improved recognition at the Global Scale was observed in both patients by reducing the inter-element distance. Global shape recognition in simultanagnosia thus seems to be modulated by the spatial distance of local elements and does not appear to be an all-or-nothing phenomenon depending on spatial continuity. The findings seem to argue against a deficit in visual working memory capacity as the primary deficit in simultanagnosia. However, further research is necessary to investigate alternative interpretations.

Introducing memory and association mechanism into a biologically inspired visual model.

PubMed

Qiao, Hong; Li, Yinlin; Tang, Tang; Wang, Peng

2014-09-01

A famous biologically inspired hierarchical model (HMAX model), which was proposed recently and corresponds to V1 to V4 of the ventral pathway in primate visual cortex, has been successfully applied to multiple visual recognition tasks. The model is able to achieve a set of position- and scale-tolerant recognition, which is a central problem in pattern recognition. In this paper, based on some other biological experimental evidence, we introduce the memory and association mechanism into the HMAX model. The main contributions of the work are: 1) mimicking the active memory and association mechanism and adding the top down adjustment to the HMAX model, which is the first try to add the active adjustment to this famous model and 2) from the perspective of information, algorithms based on the new model can reduce the computation storage and have a good recognition performance. The new model is also applied to object recognition processes. The primary experimental results show that our method is efficient with a much lower memory requirement.

Action and Emotion Recognition from Point Light Displays: An Investigation of Gender Differences

PubMed Central

Alaerts, Kaat; Nackaerts, Evelien; Meyns, Pieter; Swinnen, Stephan P.; Wenderoth, Nicole

2011-01-01

Folk psychology advocates the existence of gender differences in socio-cognitive functions such as ‘reading’ the mental states of others or discerning subtle differences in body-language. A female advantage has been demonstrated for emotion recognition from facial expressions, but virtually nothing is known about gender differences in recognizing bodily stimuli or body language. The aim of the present study was to investigate potential gender differences in a series of tasks, involving the recognition of distinct features from point light displays (PLDs) depicting bodily movements of a male and female actor. Although recognition scores were considerably high at the overall group level, female participants were more accurate than males in recognizing the depicted actions from PLDs. Response times were significantly higher for males compared to females on PLD recognition tasks involving (i) the general recognition of ‘biological motion’ versus ‘non-biological’ (or ‘scrambled’ motion); or (ii) the recognition of the ‘emotional state’ of the PLD-figures. No gender differences were revealed for a control test (involving the identification of a color change in one of the dots) and for recognizing the gender of the PLD-figure. In addition, previous findings of a female advantage on a facial emotion recognition test (the ‘Reading the Mind in the Eyes Test’ (Baron-Cohen, 2001)) were replicated in this study. Interestingly, a strong correlation was revealed between emotion recognition from bodily PLDs versus facial cues. This relationship indicates that inter-individual or gender-dependent differences in recognizing emotions are relatively generalized across facial and bodily emotion perception. Moreover, the tight correlation between a subject's ability to discern subtle emotional cues from PLDs and the subject's ability to basically discriminate biological from non-biological motion provides indications that differences in emotion recognition may - at least to some degree – be related to more basic differences in processing biological motion per se. PMID:21695266

Close encounters of the third kind: disordered domains and the interactions of proteins.

PubMed

Tompa, Peter; Fuxreiter, Monika; Oldfield, Christopher J; Simon, Istvan; Dunker, A Keith; Uversky, Vladimir N

2009-03-01

Protein-protein interactions are thought to be mediated by domains, which are autonomous folding units of proteins. Recently, a second type of interaction has been suggested, mediated by short segments termed linear motifs, which are related to recognition elements of intrinsically disordered regions. Here, we propose a third kind of protein-protein recognition mechanism, mediated by disordered regions longer than 20-30 residues. Bioinformatics predictions and well-characterized examples, such as the kinase-inhibitory domain of Cdk inhibitors and the Wiskott-Aldrich syndrome protein (WASP)-homology domain 2 of actin-binding proteins, show that these disordered regions conform to the definition of domains rather than motifs, i.e., they represent functional, evolutionary, and structural units. Their functions are distinct from those of short motifs and ordered domains, and establish a third kind of interaction principle. With these points, we argue that these long disordered regions should be recognized as a distinct class of biologically functional protein domains.

DNA nanotechnology-enabled biosensors.

PubMed

Chao, Jie; Zhu, Dan; Zhang, Yinan; Wang, Lianhui; Fan, Chunhai

2016-02-15

Biosensors employ biological molecules to recognize the target and utilize output elements which can translate the biorecognition event into electrical, optical or mass-sensitive signals to determine the quantities of the target. DNA-based biosensors, as a sub-field to biosensor, utilize DNA strands with short oligonucleotides as probes for target recognition. Although DNA-based biosensors have offered a promising alternative for fast, simple and cheap detection of target molecules, there still exist key challenges including poor stability and reproducibility that hinder their competition with the current gold standard for DNA assays. By exploiting the self-recognition properties of DNA molecules, researchers have dedicated to make versatile DNA nanostructures in a highly rigid, controllable and functionalized manner, which offers unprecedented opportunities for developing DNA-based biosensors. In this review, we will briefly introduce the recent advances on design and fabrication of static and dynamic DNA nanostructures, and summarize their applications for fabrication and functionalization of DNA-based biosensors. Copyright © 2015 Elsevier B.V. All rights reserved.

Glucose Oxidase Biosensor Modeling and Predictors Optimization by Machine Learning Methods.

PubMed

Gonzalez-Navarro, Felix F; Stilianova-Stoytcheva, Margarita; Renteria-Gutierrez, Livier; Belanche-Muñoz, Lluís A; Flores-Rios, Brenda L; Ibarra-Esquer, Jorge E

2016-10-26

Biosensors are small analytical devices incorporating a biological recognition element and a physico-chemical transducer to convert a biological signal into an electrical reading. Nowadays, their technological appeal resides in their fast performance, high sensitivity and continuous measuring capabilities; however, a full understanding is still under research. This paper aims to contribute to this growing field of biotechnology, with a focus on Glucose-Oxidase Biosensor (GOB) modeling through statistical learning methods from a regression perspective. We model the amperometric response of a GOB with dependent variables under different conditions, such as temperature, benzoquinone, pH and glucose concentrations, by means of several machine learning algorithms. Since the sensitivity of a GOB response is strongly related to these dependent variables, their interactions should be optimized to maximize the output signal, for which a genetic algorithm and simulated annealing are used. We report a model that shows a good generalization error and is consistent with the optimization.

A biomimetic colorimetric logic gate system based on multi-functional peptide-mediated gold nanoparticle assembly

NASA Astrophysics Data System (ADS)

Li, Yong; Li, Wang; He, Kai-Yu; Li, Pei; Huang, Yan; Nie, Zhou; Yao, Shou-Zhuo

2016-04-01

In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation.In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation. Electronic supplementary information (ESI) available: Additional figures (Tables S1-S3 and Fig. S1-S6). See DOI: 10.1039/c6nr01072e

Effect of buffer at nanoscale molecular recognition interfaces - electrostatic binding of biological polyanions.

PubMed

Rodrigo, Ana C; Laurini, Erik; Vieira, Vânia M P; Pricl, Sabrina; Smith, David K

2017-10-19

We investigate the impact of an over-looked component on molecular recognition in water-buffer. The binding of a cationic dye to biological polyanion heparin is shown by isothermal calorimetry to depend on buffer (Tris-HCl > HEPES > PBS). The heparin binding of self-assembled multivalent (SAMul) cationic micelles is even more buffer dependent. Multivalent electrostatic molecular recognition is buffer dependent as a result of competitive interactions between the cationic binding interface and anions present in the buffer.

A facile approach to construct versatile signal amplification system for bacterial detection.

PubMed

Qi, Peng; Zhang, Dun; Wan, Yi; Lv, Dandan

2014-01-01

In this work, a facile approach to design versatile signal amplification system for bacterial detection has been presented. Bio-recognition elements and signaling molecules can be immobilized on the surface of Fe₃O₄@MnO₂ nanomaterials with the help of bioinspired polydopamine (PDA). Fe₃O₄@MnO₂ nanoplates were chosen as carrier for bio-recognizing and signaling molecules because this kind of nanomaterial was superparamagnetic and the existence of MnO₂ could enhance the polymerization of dopamine due to its strong oxidative ability. This nanocomposite system was versatile because PDA around Fe₃O₄@MnO₂ nanoplates provided a stable and convenient platform for immobilization of biological and chemical materials, and various kinds of bio-recognizing and signaling molecules could be immobilized by reaction with pendant amino groups of dopamine to meet different detection requirements. Since a substantial amount of signaling molecules were immobilized on the surface of the nanocomposites, so the sensitivity of detection would be improved when the prepared nanocomposites were selectively conjugated with target pathogen. In the experimental section, a sandwich-type electrochemical biosensor was developed to verify the amplified bacterial detection sensitivity. Concanavalin A (conA) and ferrocene (Fc) were chosen as bio-recognition elements and signaling molecules for detection of Desulforibrio caledoiensis, respectively. The conA and Fc modified nanocomposites were conjugated on electrode by the selective recognition between conA and target bacteria, and the bacterial population was obtained by quantification of the electrochemical signal of Fc moieties. The experimental results showed that the detection sensitivity for D. caledoiensis was improved by taking advantage of this signal amplification system. © 2013 Elsevier B.V. All rights reserved.

A real-time control system of gene expression using ligand-bound nucleic acid aptamer for metabolic engineering.

PubMed

Wang, Jing; Cui, Xun; Yang, Le; Zhang, Zhe; Lv, Liping; Wang, Haoyuan; Zhao, Zhenmin; Guan, Ningzi; Dong, Lichun; Chen, Rachel

2017-07-01

Artificial control of bio-functions through regulating gene expression is one of the most important and attractive technologies to build novel living systems that are useful in the areas of chemical synthesis, nanotechnology, pharmacology, cell biology. Here, we present a novel real-time control system of gene regulation that includes an enhancement element by introducing duplex DNA aptamers upstream promoter and a repression element by introducing a RNA aptamer upstream ribosome binding site. With the presence of ligands corresponding to the DNA aptamers, the expression of the target gene can be potentially enhanced at the transcriptional level by strengthening the recognition capability of RNAP to the recognition region and speeding up the separation efficiency of the unwinding region due to the induced DNA bubble around the thrombin-bound aptamers; while with the presence of RNA aptamer ligand, the gene expression can be repressed at the translational level by weakening the recognition capability of ribosome to RBS due to the shielding of RBS by the formed aptamer-ligand complex upstream RBS. The effectiveness and potential utility of the developed gene regulation system were demonstrated by regulating the expression of ecaA gene in the cell-free systems. The realistic metabolic engineering application of the system has also tested by regulating the expression of mgtC gene and thrombin cDNA in Escherichia coli JD1021 for controlling metabolic flux and improving thrombin production, verifying that the real-time control system of gene regulation is able to realize the dynamic regulation of gene expression with potential applications in bacterial physiology studies and metabolic engineering. Copyright © 2017. Published by Elsevier Inc.

Fast neuromimetic object recognition using FPGA outperforms GPU implementations.

PubMed

Orchard, Garrick; Martin, Jacob G; Vogelstein, R Jacob; Etienne-Cummings, Ralph

2013-08-01

Recognition of objects in still images has traditionally been regarded as a difficult computational problem. Although modern automated methods for visual object recognition have achieved steadily increasing recognition accuracy, even the most advanced computational vision approaches are unable to obtain performance equal to that of humans. This has led to the creation of many biologically inspired models of visual object recognition, among them the hierarchical model and X (HMAX) model. HMAX is traditionally known to achieve high accuracy in visual object recognition tasks at the expense of significant computational complexity. Increasing complexity, in turn, increases computation time, reducing the number of images that can be processed per unit time. In this paper we describe how the computationally intensive and biologically inspired HMAX model for visual object recognition can be modified for implementation on a commercial field-programmable aate Array, specifically the Xilinx Virtex 6 ML605 evaluation board with XC6VLX240T FPGA. We show that with minor modifications to the traditional HMAX model we can perform recognition on images of size 128 × 128 pixels at a rate of 190 images per second with a less than 1% loss in recognition accuracy in both binary and multiclass visual object recognition tasks.

Topological side-chain classification of beta-turns: ideal motifs for peptidomimetic development.

PubMed

Tran, Tran Trung; McKie, Jim; Meutermans, Wim D F; Bourne, Gregory T; Andrews, Peter R; Smythe, Mark L

2005-08-01

Beta-turns are important topological motifs for biological recognition of proteins and peptides. Organic molecules that sample the side chain positions of beta-turns have shown broad binding capacity to multiple different receptors, for example benzodiazepines. Beta-turns have traditionally been classified into various types based on the backbone dihedral angles (phi2, psi2, phi3 and psi3). Indeed, 57-68% of beta-turns are currently classified into 8 different backbone families (Type I, Type II, Type I', Type II', Type VIII, Type VIa1, Type VIa2 and Type VIb and Type IV which represents unclassified beta-turns). Although this classification of beta-turns has been useful, the resulting beta-turn types are not ideal for the design of beta-turn mimetics as they do not reflect topological features of the recognition elements, the side chains. To overcome this, we have extracted beta-turns from a data set of non-homologous and high-resolution protein crystal structures. The side chain positions, as defined by C(alpha)-C(beta) vectors, of these turns have been clustered using the kth nearest neighbor clustering and filtered nearest centroid sorting algorithms. Nine clusters were obtained that cluster 90% of the data, and the average intra-cluster RMSD of the four C(alpha)-C(beta) vectors is 0.36. The nine clusters therefore represent the topology of the side chain scaffold architecture of the vast majority of beta-turns. The mean structures of the nine clusters are useful for the development of beta-turn mimetics and as biological descriptors for focusing combinatorial chemistry towards biologically relevant topological space.

Bio-recognitive photonics of a DNA-guided organic semiconductor

PubMed Central

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-01

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA–DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an ‘inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA–DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition. PMID:26725969

Protein recognition using synthetic small-molecular binders toward optical protein sensing in vitro and in live cells.

PubMed

Kubota, Ryou; Hamachi, Itaru

2015-07-07

Chemical sensing of amino acids, peptides, and proteins provides fruitful information to understand their biological functions, as well as to develop the medical and technological applications. To detect amino acids, peptides, and proteins in vitro and in vivo, vast kinds of chemical sensors including small synthetic binders/sensors, genetically-encoded fluorescent proteins and protein-based semisynthetic biosensors have been intensely investigated. This review deals with concepts, strategies, and applications of protein recognition and sensing using small synthetic binders/sensors, which are now actively studied but still in the early stage of investigation. The recognition strategies for peptides and proteins can be divided into three categories: (i) recognition of protein substructures, (ii) protein surface recognition, and (iii) protein sensing through protein-ligand interaction. Here, we overview representative examples of protein recognition and sensing, and discuss biological or diagnostic applications such as potent inhibitors/modulators of protein-protein interactions.

Bio-recognitive photonics of a DNA-guided organic semiconductor.

PubMed

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-04

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA-DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an 'inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA-DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition.

Bio-recognitive photonics of a DNA-guided organic semiconductor

NASA Astrophysics Data System (ADS)

Back, Seung Hyuk; Park, Jin Hyuk; Cui, Chunzhi; Ahn, Dong June

2016-01-01

Incorporation of duplex DNA with higher molecular weights has attracted attention for a new opportunity towards a better organic light-emitting diode (OLED) capability. However, biological recognition by OLED materials is yet to be addressed. In this study, specific oligomeric DNA-DNA recognition is successfully achieved by tri (8-hydroxyquinoline) aluminium (Alq3), an organic semiconductor. Alq3 rods crystallized with guidance from single-strand DNA molecules show, strikingly, a unique distribution of the DNA molecules with a shape of an `inverted' hourglass. The crystal's luminescent intensity is enhanced by 1.6-fold upon recognition of the perfect-matched target DNA sequence, but not in the case of a single-base mismatched one. The DNA-DNA recognition forming double-helix structure is identified to occur only in the rod's outer periphery. This study opens up new opportunities of Alq3, one of the most widely used OLED materials, enabling biological recognition.

A promoter recognition mechanism common to yeast mitochondrial and phage t7 RNA polymerases.

PubMed

Nayak, Dhananjaya; Guo, Qing; Sousa, Rui

2009-05-15

Yeast mitochondrial (YMt) and phage T7 RNA polymerases (RNAPs) are two divergent representatives of a large family of single subunit RNAPs that are also found in the mitochondria and chloroplasts of higher eukaryotes, mammalian nuclei, and many other bacteriophage. YMt and phage T7 promoters differ greatly in sequence and length, and the YMt RNAP uses an accessory factor for initiation, whereas T7 RNAP does not. We obtain evidence here that, despite these apparent differences, both the YMt and T7 RNAPs utilize a similar promoter recognition loop to bind their respective promoters. Mutations in this element in YMt RNAP specifically disrupt mitochondrial promoter utilization, and experiments with site-specifically tethered chemical nucleases indicate that this element binds the mitochondrial promoter almost identically to how the promoter recognition loop from the phage RNAP binds its promoter. Sequence comparisons reveal that the other members of the single subunit RNAP family display loops of variable sequence and size at a position corresponding to the YMt and T7 RNAP promoter recognition loops. We speculate that these elements may be involved in promoter recognition in most or all of these enzymes and that this element's structure allows it to accommodate significant sequence and length variation to provide a mechanism for rapid evolution of new promoter specificities in this RNAP family.

Microfluidics Integrated Biosensors: A Leading Technology towards Lab-on-a-Chip and Sensing Applications

PubMed Central

Luka, George; Ahmadi, Ali; Najjaran, Homayoun; Alocilja, Evangelyn; DeRosa, Maria; Wolthers, Kirsten; Malki, Ahmed; Aziz, Hassan; Althani, Asmaa; Hoorfar, Mina

2015-01-01

A biosensor can be defined as a compact analytical device or unit incorporating a biological or biologically derived sensitive recognition element immobilized on a physicochemical transducer to measure one or more analytes. Microfluidic systems, on the other hand, provide throughput processing, enhance transport for controlling the flow conditions, increase the mixing rate of different reagents, reduce sample and reagents volume (down to nanoliter), increase sensitivity of detection, and utilize the same platform for both sample preparation and detection. In view of these advantages, the integration of microfluidic and biosensor technologies provides the ability to merge chemical and biological components into a single platform and offers new opportunities for future biosensing applications including portability, disposability, real-time detection, unprecedented accuracies, and simultaneous analysis of different analytes in a single device. This review aims at representing advances and achievements in the field of microfluidic-based biosensing. The review also presents examples extracted from the literature to demonstrate the advantages of merging microfluidic and biosensing technologies and illustrate the versatility that such integration promises in the future biosensing for emerging areas of biological engineering, biomedical studies, point-of-care diagnostics, environmental monitoring, and precision agriculture. PMID:26633409

Antifouling aptasensor for the detection of adenosine triphosphate in biological media based on mixed self-assembled aptamer and zwitterionic peptide.

PubMed

Wang, Guixiang; Su, Xiaoli; Xu, Qingjun; Xu, Guiyun; Lin, Jiehua; Luo, Xiliang

2018-03-15

Direct detection of targets in complex biological media with conventional biosensors is an enormous challenge due to the nonspecific adsorption and severe biofouling. In this work, a facile strategy for sensitive and low fouling detection of adenosine triphosphate (ATP) is developed through the construction of a mixed self-assembled biosensing interface, which was composed of zwitterionic peptide (antifouling material) and ATP aptamer (bio-recognition element). The peptide and aptamer (both containing thiol groups) were simultaneously self-assembled onto gold electrode surface electrodeposited with gold nanoparticles. The developed aptasensor possessed high selectivity and sensitivity for ATP, and it showed a wide linear response range towards ATP from 0.1pM to 5nM. Owing to the presence of peptide with excellent antifouling property in the biosensing interface, the aptasensor can detect ATP in complex biological media with remarkably reduced biofouling or nonspecific adsorption effect. Moreover, it can directly detect ATP in 1% human whole blood without suffering from any significant interference, indicating its great potential for practical assaying of ATP in biological samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Limited Bandwidth Recognition of Collective Behaviors in Bio-Inspired Swarms

DTIC Science & Technology

2014-05-01

Nevai, K. M. Passino, and P. Srinivasan. Stability of choice in the honey bee nest-site selection processs. Journal of Theoretical Biology , 263(1):93...and N. Franks. Collective memory and spatial sorting in animal groups. Journal of Theoretical Biology , 218(1):1–11, 2002. [4] D. Cvetkovic, P...motion from local attraction. Journal of Theoretical Biology , 283(1):145–151, 2011. [18] G. Sukthankar and K. Sycara. Robust recognition of physical team

Fluorescent 2D WS2 Nanosheets Bearing Chemical Affinity Elements for the Recognition of Glycated Hemoglobin.

PubMed

Yang, Jin-Kyoung; Lee, Hye-Rim; Hwang, In-Jun; Kim, Hye-In; Yim, DaBin; Kim, Jong-Ho

2018-05-14

It is required to exfoliate and functionalize 2D transition metal dichalcogenides (TMDs) in an aqueous solution for biological and medical applications. Herein, the approach for the simultaneous exfoliation and functionalization of 2D WS 2 nanosheets using boronic acid-modified poly(vinyl alcohol) (B-PVA) in an aqueous solution is reported, and the B-PVA-functionalized WS 2 nanosheets (B-PVA-WS 2 ) are exploited as a fluorescent biosensor for the detection of glycated hemoglobin, HbA1c. The synthetic B-PVA polymer facilitates the exfoliation and functionalization of WS 2 nanosheets from the bulk counterpart in the aqueous solution via a pulsed sonication process, resulting in fluorescent B-PVA-WS 2 nanohybrids with a specific recognition of HbA1c. The fluorescence of the B-PVA-WS 2 is quenched in the presence of HbA1c, whereas PVA-functionalized WS 2 (PVA-WS 2 ), not bearing boronic acid as a recognition moiety, shows no fluorescence changes upon the addition of the target. The B-PVA-WS 2 is able to selectively detect HbA1c at the concentration as low as 3.3 × 10 -8 m based on its specific fluorescence quenching. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Biologically inspired emotion recognition from speech

NASA Astrophysics Data System (ADS)

Caponetti, Laura; Buscicchio, Cosimo Alessandro; Castellano, Giovanna

2011-12-01

Emotion recognition has become a fundamental task in human-computer interaction systems. In this article, we propose an emotion recognition approach based on biologically inspired methods. Specifically, emotion classification is performed using a long short-term memory (LSTM) recurrent neural network which is able to recognize long-range dependencies between successive temporal patterns. We propose to represent data using features derived from two different models: mel-frequency cepstral coefficients (MFCC) and the Lyon cochlear model. In the experimental phase, results obtained from the LSTM network and the two different feature sets are compared, showing that features derived from the Lyon cochlear model give better recognition results in comparison with those obtained with the traditional MFCC representation.

The development of Army relevant peptide-based surface enhanced Raman scattering (SERS) sensors for biological threat detection

NASA Astrophysics Data System (ADS)

Farrell, Mikella E.; Strobbia, Pietro; Sarkes, Deborah A.; Stratis-Cullum, Dimitra N.; Cullum, Brian M.; Pellegrino, Paul M.

2016-05-01

The utility of peptide-based molecular sensing for the development of novel biosensors has resulted in a significant increase in their development and usage for sensing targets like chemical, biological, energetic and toxic materials. Using peptides as a molecular recognition element is particularly advantageous because there are several mature peptide synthesis protocols that already exist, peptide structures can be tailored, selected and manipulated to be highly discerning towards desired targets, peptides can be modified to be very stable in a host of environments and stable under many different conditions, and through the development of bifunctionalized peptides can be synthesized to also bind onto desired sensing platforms (various metal materials, glass, etc.). Two examples of the several Army relevant biological targets for peptide-based sensing platforms include Ricin and Abrin. Ricin and Abrin are alarming threats because both can be weaponized and there is no antidote for exposure. Combining the sensitivity of SERS with the selectivity of a bifunctional peptide allows for the emergence of dynamic hazard sensor for Army application.

The Design, Synthesis, and Biological Evaluation of New Paclitaxel Analogs With the Ability to Evade Efflux by P-Glycoprotein

DTIC Science & Technology

2005-05-01

H O R1 7 10 13 3’ O O OH NH O O OH AcO HO O BzO H O Ph 7 10 13 3’ O 1 (R1=Ph...R2= Ac, paclitaxel) 2 (TX-67) 1a (R1=t-BuO R2= H , docetaxel) Figure 1. Paclitaxel, Docetaxel and TX-67 4 1.1 Seelig model vs. Active Transport...BzO H O O Type I Type I Type II Type I Type I Type II 3` 13 2 4 7 10 1` OH O Pgp repulsion motif Figure 2. TX-67 recognition elements

Recognition Is Still a Top Motivator.

ERIC Educational Resources Information Center

Cherrington, David J.; Wixom, B. Jackson, Jr.

1983-01-01

Motivation theories can be generalized to a common principle of human behavior: people do what they are reinforced or rewarded for doing. The most successful motivational recognition programs share five key elements: a recognition symbol, an attractive means of display, a meaningful presentation, effective promotion, and periodic evaluation. (MLF)

Modeling of biologically motivated self-learning equivalent-convolutional recurrent-multilayer neural structures (BLM_SL_EC_RMNS) for image fragments clustering and recognition

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Lazarev, Alexander A.; Nikitovich, Diana V.

2018-03-01

The biologically-motivated self-learning equivalence-convolutional recurrent-multilayer neural structures (BLM_SL_EC_RMNS) for fragments images clustering and recognition will be discussed. We shall consider these neural structures and their spatial-invariant equivalental models (SIEMs) based on proposed equivalent two-dimensional functions of image similarity and the corresponding matrix-matrix (or tensor) procedures using as basic operations of continuous logic and nonlinear processing. These SIEMs can simply describe the signals processing during the all training and recognition stages and they are suitable for unipolar-coding multilevel signals. The clustering efficiency in such models and their implementation depends on the discriminant properties of neural elements of hidden layers. Therefore, the main models and architecture parameters and characteristics depends on the applied types of non-linear processing and function used for image comparison or for adaptive-equivalent weighing of input patterns. We show that these SL_EC_RMNSs have several advantages, such as the self-study and self-identification of features and signs of the similarity of fragments, ability to clustering and recognize of image fragments with best efficiency and strong mutual correlation. The proposed combined with learning-recognition clustering method of fragments with regard to their structural features is suitable not only for binary, but also color images and combines self-learning and the formation of weight clustered matrix-patterns. Its model is constructed and designed on the basis of recursively continuous logic and nonlinear processing algorithms and to k-average method or method the winner takes all (WTA). The experimental results confirmed that fragments with a large numbers of elements may be clustered. For the first time the possibility of generalization of these models for space invariant case is shown. The experiment for an images of different dimensions (a reference array) and fragments with diferent dimensions for clustering is carried out. The experiments, using the software environment Mathcad showed that the proposed method is universal, has a significant convergence, the small number of iterations is easily, displayed on the matrix structure, and confirmed its prospects. Thus, to understand the mechanisms of self-learning equivalence-convolutional clustering, accompanying her to the competitive processes in neurons, and the neural auto-encoding-decoding and recognition principles with the use of self-learning cluster patterns is very important which used the algorithm and the principles of non-linear processing of two-dimensional spatial functions of images comparison. The experimental results show that such models can be successfully used for auto- and hetero-associative recognition. Also they can be used to explain some mechanisms, known as "the reinforcementinhibition concept". Also we demonstrate a real model experiments, which confirm that the nonlinear processing by equivalent function allow to determine the neuron-winners and customize the weight matrix. At the end of the report, we will show how to use the obtained results and to propose new more efficient hardware architecture of SL_EC_RMNS based on matrix-tensor multipliers. Also we estimate the parameters and performance of such architectures.

Environmental mineralogy - Understanding element behavior in ecosystems

NASA Astrophysics Data System (ADS)

Brown, Gordon E., Jr.; Calas, Georges

2011-02-01

Environmental Mineralogy has developed over the past decade in response to the recognition that minerals are linked in many important ways with the global ecosystem. Minerals are the main repositories of the chemical elements in Earth's crust and thus are the main sources of elements needed for the development of civilization, contaminant and pollutant elements that impact global and local ecosystems, and elements that are essential plant nutrients. These elements are released from minerals through natural processes, such as chemical weathering, and anthropogenic activities, such as mining and energy production, agriculture and industrial activities, and careless waste disposal. Minerals also play key roles in the biogeochemical cycling of the elements, sequestering elements and releasing them as the primary minerals in crustal rocks undergo various structural and compositional transformations in response to physical, chemical, and biological processes that produce secondary minerals and soils. These processes have resulted in the release of toxic elements such as arsenic in groundwater aquifers, which is having a major impact on the health of millions of people in South and Southeast Asia. The interfaces between mineral surfaces and aqueous solutions are the locations of most chemical reactions that control the composition of the natural environment, including the composition of natural waters. The nuclear fuel cycle, from uranium mining to the disposition of high-level nuclear waste, is also intimately related to minerals. A fundamental understanding of these processes requires molecular-scale information about minerals, their bulk structures and properties such as solubility, their surfaces, and their interactions with aqueous solutions, atmospheric and soil gases, natural organic matter, and biological organisms. Gaining this understanding is further complicated by the presence of natural, incidental, and manufactured nanoparticles in the environment, which are becoming increasingly important due to the rapidly developing field of nanotechnology. As a result of this complexity, Environmental Mineralogy requires the use of the most modern molecular-scale analytical and theoretical methods and overlaps substantially with closely related fields such as Environmental Sciences, low-temperature Geochemistry, and Geomicrobiology. This paper provides brief overviews of the above topics and discusses the complexity of minerals, natural vs. anthropogenic inputs of elements and pollutants into the biosphere, the role of minerals in the biogeochemical cycling of elements, natural nanoparticles, and the Environmental Mineralogy of three major potential pollutant elements (Hg, As and U).

78 FR 73208 - Underwriters Laboratories, Inc.: Application for Expansion

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-05

... Laboratories, Inc., requests the addition of multiple test standards to its scope of recognition. This... Laboratory (NRTL). UL requests the addition of multiple test standards to their NRTL scope of recognition... recognition has three elements: (1) The type of products the NRTL may test, with each type specified by its...

Implicit Relational Effects in Associative Recognition

ERIC Educational Resources Information Center

Algarabel, S.; Pitarque, A.; Combita, L. M.; Rodriguez, L. A.

2013-01-01

We study the contribution of implicit relatedness to associative recognition in two experiments. In the first experiment, we showed an implicit improvement in recognition when the stimulus elements of each word pair shared common letters and they were unpaired at test. Moreover, when asked to study the stimuli under divided attention, recollection…

Innate Pattern Recognition and Categorization in a Jumping Spider

PubMed Central

Dolev, Yinnon; Nelson, Ximena J.

2014-01-01

The East African jumping spider Evarcha culicivora feeds indirectly on vertebrate blood by preferentially preying upon blood-fed Anopheles mosquitoes, the vectors of human malaria1, using the distinct resting posture and engorged abdomen characteristic of these specific prey as key elements for their recognition. To understand perceptual categorization of objects by these spiders, we investigated their predatory behavior toward different digital stimuli - abstract ‘stick figure’ representations of Anopheles constructed solely by known key identification elements, disarranged versions of these, as well as non-prey items and detailed images of alternative prey. We hypothesized that the abstract images representing Anopheles would be perceived as potential prey, and would be preferred to those of non-preferred prey. Spiders perceived the abstract stick figures of Anopheles specifically as their preferred prey, attacking them significantly more often than non-preferred prey, even when the comprising elements of the Anopheles stick figures were disarranged and disconnected from each other. However, if the relative angles between the elements of the disconnected stick figures of Anopheles were altered, the otherwise identical set of elements was no longer perceived as prey. These data show that E. culicivora is capable of making discriminations based on abstract concepts, such as the hypothetical angle formed by discontinuous elements. It is this inter-element angle rather than resting posture that is important for correct identification of Anopheles. Our results provide a glimpse of the underlying processes of object recognition in animals with minute brains, and suggest that these spiders use a local processing approach for object recognition, rather than a holistic or global approach. This study provides an excellent basis for a comparative analysis on feature extraction and detection by animals as diverse as bees and mammals. PMID:24893306

Why the long face? The importance of vertical image structure for biological "barcodes" underlying face recognition.

PubMed

Spence, Morgan L; Storrs, Katherine R; Arnold, Derek H

2014-07-29

Humans are experts at face recognition. The mechanisms underlying this complex capacity are not fully understood. Recently, it has been proposed that face recognition is supported by a coarse-scale analysis of visual information contained in horizontal bands of contrast distributed along the vertical image axis-a biological facial "barcode" (Dakin & Watt, 2009). A critical prediction of the facial barcode hypothesis is that the distribution of image contrast along the vertical axis will be more important for face recognition than image distributions along the horizontal axis. Using a novel paradigm involving dynamic image distortions, a series of experiments are presented examining famous face recognition impairments from selectively disrupting image distributions along the vertical or horizontal image axes. Results show that disrupting the image distribution along the vertical image axis is more disruptive for recognition than matched distortions along the horizontal axis. Consistent with the facial barcode hypothesis, these results suggest that human face recognition relies disproportionately on appropriately scaled distributions of image contrast along the vertical image axis. © 2014 ARVO.

Cognitive Processing Hardware Elements

DTIC Science & Technology

2005-01-31

characters. Results will be presented below. 1 4. Recognition of human faces. There are many other possible applications such as facial recognition and...For the experiments in facial recognition , we have used a 3-layer autoassociative neural network having the following specifications: "* The input...using the facial recognition system described in the section above as an example. This system uses an autoassociative neural network containing over 10

Protein-protein recognition control by modulating electrostatic interactions.

PubMed

Han, Song; Yin, Shijin; Yi, Hong; Mouhat, Stéphanie; Qiu, Su; Cao, Zhijian; Sabatier, Jean-Marc; Wu, Yingliang; Li, Wenxin

2010-06-04

Protein-protein control recognition remains a huge challenge, and its development depends on understanding the chemical and biological mechanisms by which these interactions occur. Here we describe a protein-protein control recognition technique based on the dominant electrostatic interactions occurring between the proteins. We designed a potassium channel inhibitor, BmP05-T, that was 90.32% identical to wild-type BmP05. Negatively charged residues were translocated from the nonbinding interface to the binding interface of BmP05 inhibitor, such that BmP05-T now used BmP05 nonbinding interface as the binding interface. This switch demonstrated that nonbinding interfaces were able to control the orientation of protein binding interfaces in the process of protein-protein recognition. The novel function findings of BmP05-T peptide suggested that the control recognition technique described here had the potential for use in designing and utilizing functional proteins in many biological scenarios.

Carbohydrate Recognition by Boronolectins, Small Molecules, and Lectins

PubMed Central

Jin, Shan; Cheng, Yunfeng; Reid, Suazette; Li, Minyong; Wang, Binghe

2009-01-01

Carbohydrates are known to mediate a large number of biological and pathological events. Small and macromolecules capable of carbohydrate recognition have great potentials as research tools, diagnostics, vectors for targeted delivery of therapeutic and imaging agents, and therapeutic agents. However, this potential is far from being realized. One key issue is the difficulty in the development of “binders” capable of specific recognition of carbohydrates of biological relevance. This review discusses systematically the general approaches that are available in developing carbohydrate sensors and “binders/receptors,” and their applications. The focus is on discoveries during the last five years. PMID:19291708

U.S. Army Research Laboratory (ARL) Corporate Dari Document Transcription and Translation Guidelines

DTIC Science & Technology

2012-10-01

text file format. 15. SUBJECT TERMS Transcription, Translation, guidelines, ground truth, Optical character recognition , OCR, Machine Translation, MT...foreign language into a target language in order to train, test, and evaluate optical character recognition (OCR) and machine translation (MT) embedded...graphic element and should not be transcribed. Elements that are not part of the primary text such as handwritten annotations or stamps should not be

Associated impairment of the categories of conspecifics and biological entities: cognitive and neuroanatomical aspects of a new case.

PubMed

Capitani, Erminio; Chieppa, Francesca; Laiacona, Marcella

2010-05-01

Case A.C.A. presented an associated impairment of visual recognition and semantic knowledge for celebrities and biological objects. This case was relevant for (a) the neuroanatomical correlations, and (b) the relationship between visual recognition and semantics within the biological domain and the conspecifics domain. A.C.A. was not affected by anterior temporal damage. Her bilateral vascular lesions were localized on the medial and inferior temporal gyrus on the right and on the intermediate fusiform gyrus on the left, without concomitant lesions of the parahippocampal gyrus or posterior fusiform. Data analysis was based on a novel methodology developed to estimate the rate of stored items in the visual structural description system (SDS) or in the face recognition unit. For each biological object, no particular correlation was found between the visual information accessed through the semantic system and that tapped by the picture reality judgement. Findings are discussed with reference to whether a putative resource commonality is likely between biological objects and conspecifics, and whether or not either category may depend on an exclusive neural substrate.

Investigating the Use of Term Recall and Recognition Tools in Learning Terminology and Concepts in a Senior Biology Classroom

ERIC Educational Resources Information Center

Evergreen, Merrin; Cooper, Rebecca; Loughran, John

2016-01-01

This paper investigated the use of term recall and recognition tools for learning terminology and concepts in a senior biology classroom. The paper responded to a set of research questions from a teacher researcher perspective, making use of data collected from the teacher researcher's classrooms over several years, based on the implementation of…

75 FR 21666 - Canadian Standards Association; Application for Expansion of Recognition

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-26

... provides its final decision on the application. These notices set forth the NRTL's scope of recognition or... . Each NRTL's scope of recognition has three elements: (1) The type of products the NRTL may test, with.... OSHA will publish a public notice of this final decision in the Federal Register. Authority and...

Glucose Oxidase Biosensor Modeling and Predictors Optimization by Machine Learning Methods †

PubMed Central

Gonzalez-Navarro, Felix F.; Stilianova-Stoytcheva, Margarita; Renteria-Gutierrez, Livier; Belanche-Muñoz, Lluís A.; Flores-Rios, Brenda L.; Ibarra-Esquer, Jorge E.

2016-01-01

Biosensors are small analytical devices incorporating a biological recognition element and a physico-chemical transducer to convert a biological signal into an electrical reading. Nowadays, their technological appeal resides in their fast performance, high sensitivity and continuous measuring capabilities; however, a full understanding is still under research. This paper aims to contribute to this growing field of biotechnology, with a focus on Glucose-Oxidase Biosensor (GOB) modeling through statistical learning methods from a regression perspective. We model the amperometric response of a GOB with dependent variables under different conditions, such as temperature, benzoquinone, pH and glucose concentrations, by means of several machine learning algorithms. Since the sensitivity of a GOB response is strongly related to these dependent variables, their interactions should be optimized to maximize the output signal, for which a genetic algorithm and simulated annealing are used. We report a model that shows a good generalization error and is consistent with the optimization. PMID:27792165

Life Detection on the Early Earth

NASA Technical Reports Server (NTRS)

Runnegar, B.

2004-01-01

Finding evidence for first the existence, and then the nature of life on the early Earth or early Mars requires both the recognition of subtle biosignatures and the elimination of false positives. The history of the search for fossils in increasingly older Precambrian strata illustrates these difficulties very clearly, and new observational and theoretical approaches are both needed and being developed. At the microscopic level of investigation, three-dimensional morphological characterization coupled with in situ chemical (isotopic, elemental, structural) analysis is the desirable first step. Geological context is paramount, as has been demonstrated by the controversies over AH84001, the Greenland graphites, and the Apex chert microfossils . At larger scales, the nature of sedimentary bedforms and the structures they display becomes crucial, and here the methods of condensed matter physics prove most useful in discriminating between biological and non-biological constructions. Ultimately, a combination of geochemical, morphological, and contextural evidence may be required for certain life detection on the early Earth or elsewhere.

Interference with facial emotion recognition by verbal but not visual loads.

PubMed

Reed, Phil; Steed, Ian

2015-12-01

The ability to recognize emotions through facial characteristics is critical for social functioning, but is often impaired in those with a developmental or intellectual disability. The current experiments explored the degree to which interfering with the processing capacities of typically-developing individuals would produce a similar inability to recognize emotions through the facial elements of faces displaying particular emotions. It was found that increasing the cognitive load (in an attempt to model learning impairments in a typically developing population) produced deficits in correctly identifying emotions from facial elements. However, this effect was much more pronounced when using a concurrent verbal task than when employing a concurrent visual task, suggesting that there is a substantial verbal element to the labeling and subsequent recognition of emotions. This concurs with previous work conducted with those with developmental disabilities that suggests emotion recognition deficits are connected with language deficits. Copyright © 2015 Elsevier Ltd. All rights reserved.

Auditory-visual object recognition time suggests specific processing for animal sounds.

PubMed

Suied, Clara; Viaud-Delmon, Isabelle

2009-01-01

Recognizing an object requires binding together several cues, which may be distributed across different sensory modalities, and ignoring competing information originating from other objects. In addition, knowledge of the semantic category of an object is fundamental to determine how we should react to it. Here we investigate the role of semantic categories in the processing of auditory-visual objects. We used an auditory-visual object-recognition task (go/no-go paradigm). We compared recognition times for two categories: a biologically relevant one (animals) and a non-biologically relevant one (means of transport). Participants were asked to react as fast as possible to target objects, presented in the visual and/or the auditory modality, and to withhold their response for distractor objects. A first main finding was that, when participants were presented with unimodal or bimodal congruent stimuli (an image and a sound from the same object), similar reaction times were observed for all object categories. Thus, there was no advantage in the speed of recognition for biologically relevant compared to non-biologically relevant objects. A second finding was that, in the presence of a biologically relevant auditory distractor, the processing of a target object was slowed down, whether or not it was itself biologically relevant. It seems impossible to effectively ignore an animal sound, even when it is irrelevant to the task. These results suggest a specific and mandatory processing of animal sounds, possibly due to phylogenetic memory and consistent with the idea that hearing is particularly efficient as an alerting sense. They also highlight the importance of taking into account the auditory modality when investigating the way object concepts of biologically relevant categories are stored and retrieved.

Structures of the peptide-modifying radical SAM enzyme SuiB elucidate the basis of substrate recognition.

PubMed

Davis, Katherine M; Schramma, Kelsey R; Hansen, William A; Bacik, John P; Khare, Sagar D; Seyedsayamdost, Mohammad R; Ando, Nozomi

2017-09-26

Posttranslational modification of ribosomally synthesized peptides provides an elegant means for the production of biologically active molecules known as RiPPs (ribosomally synthesized and posttranslationally modified peptides). Although the leader sequence of the precursor peptide is often required for turnover, the exact mode of recognition by the modifying enzymes remains unclear for many members of this class of natural products. Here, we have used X-ray crystallography and computational modeling to examine the role of the leader peptide in the biosynthesis of a homolog of streptide, a recently identified peptide natural product with an intramolecular lysine-tryptophan cross-link, which is installed by the radical S -adenosylmethionine (SAM) enzyme, StrB. We present crystal structures of SuiB, a close ortholog of StrB, in various forms, including apo SuiB, SAM-bound SuiB, and a complex of SuiB with SAM and its peptide substrate, SuiA. Although the N-terminal domain of SuiB adopts a typical RRE (RiPP recognition element) motif, which has been implicated in precursor peptide recognition, we observe binding of the leader peptide in the catalytic barrel rather than the N-terminal domain. Computational simulations support a mechanism in which the leader peptide guides posttranslational modification by positioning the cross-linking residues of the precursor peptide within the active site. Together the results shed light onto binding of the precursor peptide and the associated conformational changes needed for the formation of the unique carbon-carbon cross-link in the streptide family of natural products.

Spectral fingerprint of electrostatic forces between biological cells

NASA Astrophysics Data System (ADS)

Murovec, T.; Brosseau, C.

2015-10-01

The prediction of electrostatic forces (EFs) between biological cells still poses challenges of great scientific importance, e.g., cell recognition, electroporation (EP), and mechanosensing. Frequency-domain finite element simulations explore a variety of cell configurations in the range of parameters typical for eukaryotic cells. Here, by applying an electric field to a pair of layered concentric shells, a prototypical model of a biological cell, we provide numerical evidence that the instantaneous EF changes from repulsion to attraction as the drive frequency of the electric field is varied. We identify crossover frequencies and discuss their dependence as a function of field frequency, conductivity of the extracellular medium, and symmetry of the configuration of cells. We present findings which suggest that the spectrum of EFs depends sensitively on the configuration of cells. We discuss the signatures of the collective behavior of systems with many cells in the spectrum of the EF and highlight a few of the observational consequences that this behavior implies. By looking at different cell configurations, we are able to show that the repulsion-to-attraction transition phenomenon is largely associated with an asymmetric electrostatic screening at very small separation between cells. These findings pave the way for the experimental observation of the electromagnetic properties of efficient and simple models of biological tissues.

Spectral fingerprint of electrostatic forces between biological cells.

PubMed

Murovec, T; Brosseau, C

2015-10-01

The prediction of electrostatic forces (EFs) between biological cells still poses challenges of great scientific importance, e.g., cell recognition, electroporation (EP), and mechanosensing. Frequency-domain finite element simulations explore a variety of cell configurations in the range of parameters typical for eukaryotic cells. Here, by applying an electric field to a pair of layered concentric shells, a prototypical model of a biological cell, we provide numerical evidence that the instantaneous EF changes from repulsion to attraction as the drive frequency of the electric field is varied. We identify crossover frequencies and discuss their dependence as a function of field frequency, conductivity of the extracellular medium, and symmetry of the configuration of cells. We present findings which suggest that the spectrum of EFs depends sensitively on the configuration of cells. We discuss the signatures of the collective behavior of systems with many cells in the spectrum of the EF and highlight a few of the observational consequences that this behavior implies. By looking at different cell configurations, we are able to show that the repulsion-to-attraction transition phenomenon is largely associated with an asymmetric electrostatic screening at very small separation between cells. These findings pave the way for the experimental observation of the electromagnetic properties of efficient and simple models of biological tissues.

A portable array biosensor for food safety

NASA Astrophysics Data System (ADS)

Golden, Joel P.; Ngundi, Miriam M.; Shriver-Lake, Lisa C.; Taitt, Chris R.; Ligler, Frances S.

2004-11-01

An array biosensor developed for simultaneous analysis of multiple samples has been utilized to develop assays for toxins and pathogens in a variety of foods. The biochemical component of the multi-analyte biosensor consists of a patterned array of biological recognition elements immobilized on the surface of a planar waveguide. A fluorescence assay is performed on the patterned surface, yielding an array of fluorescent spots, the locations of which are used to identify what analyte is present. Signal transduction is accomplished by means of a diode laser for fluorescence excitation, optical filters and a CCD camera for image capture. A laptop computer controls the miniaturized fluidics system and image capture. Results for four mycotoxin competition assays in buffer and food samples are presented.

On the optimal design of molecular sensing interfaces with lipid bilayer assemblies - A knowledge based approach

NASA Astrophysics Data System (ADS)

Siontorou, Christina G.

2012-12-01

Biosensors are analytic devices that incorporate a biochemical recognition system (biological, biologicalderived or biomimic: enzyme, antibody, DNA, receptor, etc.) in close contact with a physicochemical transducer (electrochemical, optical, piezoelectric, conductimetric, etc.) that converts the biochemical information, produced by the specific biological recognition reaction (analyte-biomolecule binding), into a chemical or physical output signal, related to the concentration of the analyte in the measuring sample. The biosensing concept is based on natural chemoreception mechanisms, which are feasible over/within/by means of a biological membrane, i.e., a structured lipid bilayer, incorporating or attached to proteinaceous moieties that regulate molecular recognition events which trigger ion flux changes (facilitated or passive) through the bilayer. The creation of functional structures that are similar to natural signal transduction systems, correlating and interrelating compatibly and successfully the physicochemical transducer with the lipid film that is self-assembled on its surface while embedding the reconstituted biological recognition system, and at the same time manage to satisfy the basic conditions for measuring device development (simplicity, easy handling, ease of fabrication) is far from trivial. The aim of the present work is to present a methodological framework for designing such molecular sensing interfaces, functioning within a knowledge-based system built on an ontological platform for supplying sub-systems options, compatibilities, and optimization parameters.

A novel paired domain DNA recognition motif can mediate Pax2 repression of gene transcription.

PubMed

Håvik, B; Ragnhildstveit, E; Lorens, J B; Saelemyr, K; Fauske, O; Knudsen, L K; Fjose, A

1999-12-20

The paired domain (PD) is an evolutionarily conserved DNA-binding domain encoded by the Pax gene family of developmental regulators. The Pax proteins are transcription factors and are involved in a variety of processes such as brain development, patterning of the central nervous system (CNS), and B-cell development. In this report we demonstrate that the zebrafish Pax2 PD can interact with a novel type of DNA sequences in vitro, the triple-A motif, consisting of a heptameric nucleotide sequence G/CAAACA/TC with an invariant core of three adjacent adenosines. This recognition sequence was found to be conserved in known natural Pax5 repressor elements involved in controlling the expression of the p53 and J-chain genes. By identifying similar high affinity binding sites in potential target genes of the Pax2 protein, including the pax2 gene itself, we obtained further evidence that the triple-A sites are biologically significant. The putative natural target sites also provide a basis for defining an extended consensus recognition sequence. In addition, we observed in transformation assays a direct correlation between Pax2 repressor activity and the presence of triple-A sites. The results suggest that a transcriptional regulatory function of Pax proteins can be modulated by PD binding to different categories of target sequences. Copyright 1999 Academic Press.

Visual recognition and inference using dynamic overcomplete sparse learning.

PubMed

Murray, Joseph F; Kreutz-Delgado, Kenneth

2007-09-01

We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and expectation-driven segmentation. Using properties of biological vision for guidance, we posit a stochastic generative world model and from it develop a simplified world model (SWM) based on a tractable variational approximation that is designed to enforce sparse coding. Recent developments in computational methods for learning overcomplete representations (Lewicki & Sejnowski, 2000; Teh, Welling, Osindero, & Hinton, 2003) suggest that overcompleteness can be useful for visual tasks, and we use an overcomplete dictionary learning algorithm (Kreutz-Delgado, et al., 2003) as a preprocessing stage to produce accurate, sparse codings of images. Inference is performed by constructing a dynamic multilayer network with feedforward, feedback, and lateral connections, which is trained to approximate the SWM. Learning is done with a variant of the back-propagation-through-time algorithm, which encourages convergence to desired states within a fixed number of iterations. Vision tasks require large networks, and to make learning efficient, we take advantage of the sparsity of each layer to update only a small subset of elements in a large weight matrix at each iteration. Experiments on a set of rotated objects demonstrate various types of visual inference and show that increasing the degree of overcompleteness improves recognition performance in difficult scenes with occluded objects in clutter.

Pattern recognition: A basis for remote sensing data analysis

NASA Technical Reports Server (NTRS)

Swain, P. H.

1973-01-01

The theoretical basis for the pattern-recognition-oriented algorithms used in the multispectral data analysis software system is discussed. A model of a general pattern recognition system is presented. The receptor or sensor is usually a multispectral scanner. For each ground resolution element the receptor produces n numbers or measurements corresponding to the n channels of the scanner.

DEPPDB - DNA electrostatic potential properties database. Electrostatic properties of genome DNA elements.

PubMed

Osypov, Alexander A; Krutinin, Gleb G; Krutinina, Eugenia A; Kamzolova, Svetlana G

2012-04-01

Electrostatic properties of genome DNA are important to its interactions with different proteins, in particular, related to transcription. DEPPDB - DNA Electrostatic Potential (and other Physical) Properties Database - provides information on the electrostatic and other physical properties of genome DNA combined with its sequence and annotation of biological and structural properties of genomes and their elements. Genomes are organized on taxonomical basis, supporting comparative and evolutionary studies. Currently, DEPPDB contains all completely sequenced bacterial, viral, mitochondrial, and plastids genomes according to the NCBI RefSeq, and some model eukaryotic genomes. Data for promoters, regulation sites, binding proteins, etc., are incorporated from established DBs and literature. The database is complemented by analytical tools. User sequences calculations are available. Case studies discovered electrostatics complementing DNA bending in E.coli plasmid BNT2 promoter functioning, possibly affecting host-environment metabolic switch. Transcription factors binding sites gravitate to high potential regions, confirming the electrostatics universal importance in protein-DNA interactions beyond the classical promoter-RNA polymerase recognition and regulation. Other genome elements, such as terminators, also show electrostatic peculiarities. Most intriguing are gene starts, exhibiting taxonomic correlations. The necessity of the genome electrostatic properties studies is discussed.

Laser ablation ICP-MS applications using the timescales of geologic and biologic processes

NASA Astrophysics Data System (ADS)

Ridley, W. I.

2003-04-01

Geochemists commonly examine geologic processes on timescales of 10^4--10^9 years, and accept that often age relations, e.g., chemical zoning in minerals, can only be measured in a relative sense. The progression of a geologic process that involves geochemical changes may be assessed using trace element microbeam techniques, because the textural, and therefore spatial context, of the analytical scheme can be preserved. However, quantification requires appropriate calibration standards. Laser ablation ICP-MS (LA-ICP-MS) is proving particularly useful now that appropriate standards are becoming available. For instance, trace element zoning patterns in primary sulfides (e.g., pyrite, sphalerite, chalcopyrite, galena) and secondary phases can be inverted to examine relative changes in fluid composition during cycles of hydrothermal mineralization. In turn such information provides insights into fluid sources, migration pathways and depositional processes. These studies have only become possible with the development of appropriate sulfide calibration standards. Another example, made possible with the development of appropriate silicate calibration standards, is the quantitative spatial mapping of REE variations in amphibolite-grade garnets. The recognition that the trace and major elements are decoupled provides a better understanding of the various sources of elements during metamorphic re-equilibration. There is also a growing realization that LA-ICP-MS has potential in biochemical studies, and geochemists have begun to turn their attention in this direction, working closely with biologists. Unlike many geologic processes, the timescales of biologic processes are measured in years to centuries and are frequently amenable to absolute dating. Examples that can be cited where LA-ICP-MS has been applied include annual trace metal variations in tree rings, corals, teeth, bones, bird feathers and various animal vibrissae (sea lion, walrus, wolf). The aim of such studies is to correlate trace element variations with changes in environmental variables. Such studies are proving informative in climate change and habitat management. Again, such variations have been quantified with the availability of appropriate organic, carbonate and phosphate calibration standards.

Three Dimensional Object Recognition Using an Unsupervised Neural Network: Understanding the Distinguishing Features

DTIC Science & Technology

1992-12-23

predominance of structural models of recognition, of which a recent example is the Recognition By Components (RBC) theory ( Biederman , 1987 ). Structural...related to recent statistical theory (Huber, 1985; Friedman, 1987 ) and is derived from a biologically motivated computational theory (Bienenstock et...dimensional object recognition (Intrator and Gold, 1991). The method is related to recent statistical theory (Huber, 1985; Friedman, 1987 ) and is derived

Selenium. Role of the Essential Metalloid in Health

PubMed Central

Kurokawa, Suguru; Berry, Marla J.

2015-01-01

Selenium is an essential micronutrient in mammals, but is also recognized as toxic in excess. It is a non-metal with properties that are intermediate between the chalcogen elements sulfur and tellurium. Selenium exerts its biological functions through selenoproteins. Selenoproteins contain selenium in the form of the 21st amino acid, selenocysteine (Sec), which is an analog of cysteine with the sulfur-containing side chain replaced by a Se-containing side chain. Sec is encoded by the codon UGA, which is one of three termination codons for mRNA translation in non-selenoprotein genes. Recognition of the UGA codon as a Sec insertion site instead of stop requires a Sec insertion sequence (SECIS) element in selenoprotein mRNAs and a unique selenocysteyl-tRNA, both of which are recognized by specialized protein factors. Unlike the 20 standard amino acids, Sec is biosynthesized from serine on its tRNA. Twenty-five selenoproteins are encoded in the human genome. Most of the selenoprotein genes were discovered by bioinformatics approaches, searching for SECIS elements downstream of in-frame UGA codons. Sec has been described as having stronger nucleophilic and electrophilic properties than cysteine, and Sec is present in the catalytic site of all selenoenzymes. Most selenoproteins, whose functions are known, are involved in redox systems and signaling pathways. However, several selenoproteins are not well characterized in terms of their function. The selenium field has grown dramatically in the last few decades, and research on selenium biology is providing extensive new information regarding its importance for human health. PMID:24470102

A biomimetic colorimetric logic gate system based on multi-functional peptide-mediated gold nanoparticle assembly.

PubMed

Li, Yong; Li, Wang; He, Kai-Yu; Li, Pei; Huang, Yan; Nie, Zhou; Yao, Shou-Zhuo

2016-04-28

In natural biological systems, proteins exploit various functional peptide motifs to exert target response and activity switch, providing a functional and logic basis for complex cellular activities. Building biomimetic peptide-based bio-logic systems is highly intriguing but remains relatively unexplored due to limited logic recognition elements and complex signal outputs. In this proof-of-principle work, we attempted to address these problems by utilizing multi-functional peptide probes and the peptide-mediated nanoparticle assembly system. Here, the rationally designed peptide probes function as the dual-target responsive element specifically responsive to metal ions and enzymes as well as the mediator regulating the assembly of gold nanoparticles (AuNPs). Taking advantage of Zn2+ ions and chymotrypsin as the model inputs of metal ions and enzymes, respectively, we constructed the peptide logic system computed by the multi-functional peptide probes and outputted by the readable colour change of AuNPs. In this way, the representative binary basic logic gates (AND, OR, INHIBIT, NAND, IMPLICATION) have been achieved by delicately coding the peptide sequence, demonstrating the versatility of our logic system. Additionally, we demonstrated that the three-input combinational logic gate (INHIBIT-OR) could also be successfully integrated and applied as a multi-tasking biosensor for colorimetric detection of dual targets. This nanoparticle-based peptide logic system presents a valid strategy to illustrate peptide information processing and provides a practical platform for executing peptide computing or peptide-related multiplexing sensing, implying that the controllable nanomaterial assembly is a promising and potent methodology for the advancement of biomimetic bio-logic computation.

Enabling fluorescent biosensors for the forensic identification of body fluids.

PubMed

Frascione, Nunzianda; Gooch, James; Daniel, Barbara

2013-11-12

The search for body fluids often forms a crucial element of many forensic investigations. Confirming fluid presence at a scene can not only support or refute the circumstantial claims of a victim, suspect or witness, but may additionally provide a valuable source of DNA for further identification purposes. However, current biological fluid testing techniques are impaired by a number of well-characterised limitations; they often give false positives, cannot be used simultaneously, are sample destructive and lack the ability to visually locate fluid depositions. These disadvantages can negatively affect the outcome of a case through missed or misinterpreted evidence. Biosensors are devices able to transduce a biological recognition event into a measurable signal, resulting in real-time analyte detection. The use of innovative optical sensing technology may enable the highly specific and non-destructive detection of biological fluid depositions through interaction with several fluid-endogenous biomarkers. Despite considerable impact in a variety of analytical disciplines, biosensor application within forensic analyses may be considered extremely limited. This article aims to explore a number of prospective biosensing mechanisms and to outline the challenges associated with their adaptation towards detection of fluid-specific analytes.

Aminoglycosides: Molecular Insights on the Recognition of RNA and Aminoglycoside Mimics

PubMed Central

Chittapragada, Maruthi; Roberts, Sarah; Ham, Young Wan

2009-01-01

RNA is increasingly recognized for its significant functions in biological systems and has recently become an important molecular target for therapeutics development. Aminoglycosides, a large class of clinically significant antibiotics, exert their biological functions by binding to prokaryotic ribosomal RNA (rRNA) and interfering with protein translation, resulting in bacterial cell death. They are also known to bind to viral mRNAs such as HIV-1 RRE and TAR. Consequently, aminoglycosides are accepted as the single most important model in understanding the principles that govern small molecule-RNA recognition, which is essential for the development of novel antibacterial, antiviral or even anti-oncogenic agents. This review outlines the chemical structures and mechanisms of molecular recognition and antibacterial activity of aminoglycosides and various aminoglycoside mimics that have recently been devised to improve biological efficacy, binding affinity and selectivity, or to circumvent bacterial resistance. PMID:19812740

Learning and Recognition of Clothing Genres From Full-Body Images.

PubMed

Hidayati, Shintami C; You, Chuang-Wen; Cheng, Wen-Huang; Hua, Kai-Lung

2018-05-01

According to the theory of clothing design, the genres of clothes can be recognized based on a set of visually differentiable style elements, which exhibit salient features of visual appearance and reflect high-level fashion styles for better describing clothing genres. Instead of using less-discriminative low-level features or ambiguous keywords to identify clothing genres, we proposed a novel approach for automatically classifying clothing genres based on the visually differentiable style elements. A set of style elements, that are crucial for recognizing specific visual styles of clothing genres, were identified based on the clothing design theory. In addition, the corresponding salient visual features of each style element were identified and formulated with variables that can be computationally derived with various computer vision algorithms. To evaluate the performance of our algorithm, a dataset containing 3250 full-body shots crawled from popular online stores was built. Recognition results show that our proposed algorithms achieved promising overall precision, recall, and -score of 88.76%, 88.53%, and 88.64% for recognizing upperwear genres, and 88.21%, 88.17%, and 88.19% for recognizing lowerwear genres, respectively. The effectiveness of each style element and its visual features on recognizing clothing genres was demonstrated through a set of experiments involving different sets of style elements or features. In summary, our experimental results demonstrate the effectiveness of the proposed method in clothing genre recognition.

Restoring the missing features of the corrupted speech using linear interpolation methods

NASA Astrophysics Data System (ADS)

Rassem, Taha H.; Makbol, Nasrin M.; Hasan, Ali Muttaleb; Zaki, Siti Syazni Mohd; Girija, P. N.

2017-10-01

One of the main challenges in the Automatic Speech Recognition (ASR) is the noise. The performance of the ASR system reduces significantly if the speech is corrupted by noise. In spectrogram representation of a speech signal, after deleting low Signal to Noise Ratio (SNR) elements, the incomplete spectrogram is obtained. In this case, the speech recognizer should make modifications to the spectrogram in order to restore the missing elements, which is one direction. In another direction, speech recognizer should be able to restore the missing elements due to deleting low SNR elements before performing the recognition. This is can be done using different spectrogram reconstruction methods. In this paper, the geometrical spectrogram reconstruction methods suggested by some researchers are implemented as a toolbox. In these geometrical reconstruction methods, the linear interpolation along time or frequency methods are used to predict the missing elements between adjacent observed elements in the spectrogram. Moreover, a new linear interpolation method using time and frequency together is presented. The CMU Sphinx III software is used in the experiments to test the performance of the linear interpolation reconstruction method. The experiments are done under different conditions such as different lengths of the window and different lengths of utterances. Speech corpus consists of 20 males and 20 females; each one has two different utterances are used in the experiments. As a result, 80% recognition accuracy is achieved with 25% SNR ratio.

Automated information-analytical system for thunderstorm monitoring and early warning alarms using modern physical sensors and information technologies with elements of artificial intelligence

NASA Astrophysics Data System (ADS)

Boldyreff, Anton S.; Bespalov, Dmitry A.; Adzhiev, Anatoly Kh.

2017-05-01

Methods of artificial intelligence are a good solution for weather phenomena forecasting. They allow to process a large amount of diverse data. Recirculation Neural Networks is implemented in the paper for the system of thunderstorm events prediction. Large amounts of experimental data from lightning sensors and electric field mills networks are received and analyzed. The average recognition accuracy of sensor signals is calculated. It is shown that Recirculation Neural Networks is a promising solution in the forecasting of thunderstorms and weather phenomena, characterized by the high efficiency of the recognition elements of the sensor signals, allows to compress images and highlight their characteristic features for subsequent recognition.

Multi-scale Imaging of Cellular and Sub-cellular Structures using Scanning Probe Recognition Microscopy.

NASA Astrophysics Data System (ADS)

Chen, Q.; Rice, A. F.

2005-03-01

Scanning Probe Recognition Microscopy is a new scanning probe capability under development within our group to reliably return to and directly interact with a specific nanobiological feature of interest. In previous work, we have successfully recognized and classified tubular versus globular biological objects from experimental atomic force microscope images using a method based on normalized central moments [ref. 1]. In this paper we extend this work to include recognition schemes appropriate for cellular and sub-cellular structures. Globular cells containing tubular actin filaments are under investigation. Thus there are differences in external/internal shapes and scales. Continuous Wavelet Transform with a differential Gaussian mother wavelet is employed for multi- scale analysis. [ref. 1] Q. Chen, V. Ayres and L. Udpa, ``Biological Investigation Using Scanning Probe Recognition Microscopy,'' Proceedings 3rd IEEE Conference on Nanotechnology, vol. 2, p 863-865 (2003).

Promoter Recognition by Extracytoplasmic Function σ Factors: Analyzing DNA and Protein Interaction Motifs

PubMed Central

Guzina, Jelena

2016-01-01

ABSTRACT Extracytoplasmic function (ECF) σ factors are the largest and the most diverse group of alternative σ factors, but their mechanisms of transcription are poorly studied. This subfamily is considered to exhibit a rigid promoter structure and an absence of mixing and matching; both −35 and −10 elements are considered necessary for initiating transcription. This paradigm, however, is based on very limited data, which bias the analysis of diverse ECF σ subgroups. Here we investigate DNA and protein recognition motifs involved in ECF σ factor transcription by a computational analysis of canonical ECF subfamily members, much less studied ECF σ subgroups, and the group outliers, obtained from recently sequenced bacteriophages. The analysis identifies an extended −10 element in promoters for phage ECF σ factors; a comparison with bacterial σ factors points to a putative 6-amino-acid motif just C-terminal of domain σ2, which is responsible for the interaction with the identified extension of the −10 element. Interestingly, a similar protein motif is found C-terminal of domain σ2 in canonical ECF σ factors, at a position where it is expected to interact with a conserved motif further upstream of the −10 element. Moreover, the phiEco32 ECF σ factor lacks a recognizable −35 element and σ4 domain, which we identify in a homologous phage, 7-11, indicating that the extended −10 element can compensate for the lack of −35 element interactions. Overall, the results reveal greater flexibility in promoter recognition by ECF σ factors than previously recognized and raise the possibility that mixing and matching also apply to this group, a notion that remains to be biochemically tested. IMPORTANCE ECF σ factors are the most numerous group of alternative σ factors but have been little studied. Their promoter recognition mechanisms are obscured by the large diversity within the ECF σ factor group and the limited similarity with the well-studied housekeeping σ factors. Here we extensively compare bacterial and bacteriophage ECF σ factors and their promoters in order to infer DNA and protein recognition motifs involved in transcription initiation. We predict a more flexible promoter structure than is recognized by the current paradigm, which assumes rigidness, and propose that ECF σ promoter elements may complement (mix and match with) each other's strengths. These results warrant the refocusing of research efforts from the well-studied housekeeping σ factors toward the physiologically highly important, but insufficiently understood, alternative σ factors. PMID:27137497

A Configurable Event-Driven Convolutional Node with Rate Saturation Mechanism for Modular ConvNet Systems Implementation.

PubMed

Camuñas-Mesa, Luis A; Domínguez-Cordero, Yaisel L; Linares-Barranco, Alejandro; Serrano-Gotarredona, Teresa; Linares-Barranco, Bernabé

2018-01-01

Convolutional Neural Networks (ConvNets) are a particular type of neural network often used for many applications like image recognition, video analysis or natural language processing. They are inspired by the human brain, following a specific organization of the connectivity pattern between layers of neurons known as receptive field. These networks have been traditionally implemented in software, but they are becoming more computationally expensive as they scale up, having limitations for real-time processing of high-speed stimuli. On the other hand, hardware implementations show difficulties to be used for different applications, due to their reduced flexibility. In this paper, we propose a fully configurable event-driven convolutional node with rate saturation mechanism that can be used to implement arbitrary ConvNets on FPGAs. This node includes a convolutional processing unit and a routing element which allows to build large 2D arrays where any multilayer structure can be implemented. The rate saturation mechanism emulates the refractory behavior in biological neurons, guaranteeing a minimum separation in time between consecutive events. A 4-layer ConvNet with 22 convolutional nodes trained for poker card symbol recognition has been implemented in a Spartan6 FPGA. This network has been tested with a stimulus where 40 poker cards were observed by a Dynamic Vision Sensor (DVS) in 1 s time. Different slow-down factors were applied to characterize the behavior of the system for high speed processing. For slow stimulus play-back, a 96% recognition rate is obtained with a power consumption of 0.85 mW. At maximum play-back speed, a traffic control mechanism downsamples the input stimulus, obtaining a recognition rate above 63% when less than 20% of the input events are processed, demonstrating the robustness of the network.

A Configurable Event-Driven Convolutional Node with Rate Saturation Mechanism for Modular ConvNet Systems Implementation

PubMed Central

Camuñas-Mesa, Luis A.; Domínguez-Cordero, Yaisel L.; Linares-Barranco, Alejandro; Serrano-Gotarredona, Teresa; Linares-Barranco, Bernabé

2018-01-01

Convolutional Neural Networks (ConvNets) are a particular type of neural network often used for many applications like image recognition, video analysis or natural language processing. They are inspired by the human brain, following a specific organization of the connectivity pattern between layers of neurons known as receptive field. These networks have been traditionally implemented in software, but they are becoming more computationally expensive as they scale up, having limitations for real-time processing of high-speed stimuli. On the other hand, hardware implementations show difficulties to be used for different applications, due to their reduced flexibility. In this paper, we propose a fully configurable event-driven convolutional node with rate saturation mechanism that can be used to implement arbitrary ConvNets on FPGAs. This node includes a convolutional processing unit and a routing element which allows to build large 2D arrays where any multilayer structure can be implemented. The rate saturation mechanism emulates the refractory behavior in biological neurons, guaranteeing a minimum separation in time between consecutive events. A 4-layer ConvNet with 22 convolutional nodes trained for poker card symbol recognition has been implemented in a Spartan6 FPGA. This network has been tested with a stimulus where 40 poker cards were observed by a Dynamic Vision Sensor (DVS) in 1 s time. Different slow-down factors were applied to characterize the behavior of the system for high speed processing. For slow stimulus play-back, a 96% recognition rate is obtained with a power consumption of 0.85 mW. At maximum play-back speed, a traffic control mechanism downsamples the input stimulus, obtaining a recognition rate above 63% when less than 20% of the input events are processed, demonstrating the robustness of the network. PMID:29515349

A microflow chemiluminescence sensor for indirect determination of dibutyl phthalate by hydrolyzing based on biological recognition materials.

PubMed

Qiu, Huamin; Fan, Lulu; Li, Xiangjun; Li, Leilei; Sun, Min; Luo, Chuannan

2013-03-05

A microflow chemiluminescence (CL) sensor for determination of dibutyl phthalate (DBP) based on magnetic molecularly imprinted polymer (MMIP) as recognition element was fabricated. Briefly, a hydrophilic molecularly imprinted polymer layer was produced at the surface of Fe₃O₄@SiO₂ magnetic nanoparticles (MNPs) via combination of molecular imprinting and reversible stimuli responsive hydrogel. In this protocol, the initial step involved co-precipitation of Fe²⁺ and Fe³⁺ in an ammonia solution. Silica was then coated on the Fe₃O₄ nanoparticles using a sol-gel method to obtain silica shell magnetic nanoparticles. The MMIP was synthesized using methacrylic acid (MAA) as functional monomer and ethylene glycol dimethacrylate (EGDMA) as cross-linker and 2,2-azobisisobutyronitrile (AIBN) as initiator in chloroform. Then the synthesized MMIP and magnetic non-molecular imprinted polymers (MNIP) were employed as recognition by packing into lab-made straight shape tubes, connected in CL analyzer for establishing the novel sensor with a single channel syringe pump. And a mixer for hydrolyzing of DBP was followed. Based on this experiment principle, DBP was determined indirectly. And the MMIP showed satisfactory recognition capacity to DBP, resulting to the wide linear range of 3.84 × 10⁻⁸ to 2.08 × 10⁻⁵ M and the low detection limit of 2.09 × 10⁻⁹ M (3σ) for DBP. The relative standard deviation (RSD) for DBP (3.20 × 10⁻⁶ M) was 1.40% (n=11). Besides improving sensitivity and selectivity, the sensor was reusable. The proposed DBP-MMIP-CL sensor has been successfully applied to determine DBP in drink samples. Copyright © 2012 Elsevier B.V. All rights reserved.

Label-free biosensing with functionalized nanopipette probes.

PubMed

Umehara, Senkei; Karhanek, Miloslav; Davis, Ronald W; Pourmand, Nader

2009-03-24

Nanopipette technology can uniquely identify biomolecules such as proteins based on differences in size, shape, and electrical charge. These differences are determined by the detection of changes in ionic current as the proteins interact with the nanopipette tip coated with probe molecules. Here we show that electrostatic, biotin-streptavidin, and antibody-antigen interactions on the nanopipette tip surface affect ionic current flowing through a 50-nm pore. Highly charged polymers interacting with the glass surface modulated the rectification property of the nanopipette electrode. Affinity-based binding between the probes tethered to the surface and their target proteins caused a change in the ionic current due to a partial blockade or an altered surface charge. These findings suggest that nanopipettes functionalized with appropriate molecular recognition elements can be used as nanosensors in biomedical and biological research.

Plant tissue-based chemiluminescence biosensor for ethanol.

PubMed

Huang, Yuming; Wu, Fangqiong

2006-07-01

A plant tissue-based chemiluminescence biosensor for ethanol based on using mushroom (Agaricus bisporus) tissue as the recognition element is proposed in this paper. The principle for ethanol sensing relies on the luminol-potassium hexacyanoferrate(III)-hydrogen peroxide transducer reaction, in which hydrogen peroxide is produced from the ethanol enzymatic catalytic oxidation by oxygen under the catalysis of alcohol oxidase in the tissue column. Under optimum conditions, the method allowed the measurement of ethanol in the range of 0.001 - 2 mmol/l with a detection limit (3 sigma) of 0.2 micromol/l. The relative standard deviation (RSD) was 4.14% (n = 11) for 0.05 mmol/l ethanol. The proposed method has been applied to the determination of ethanol in biological fluids and beverages with satisfactory results.

Biomining of MoS2 with Peptide-based Smart Biomaterials.

PubMed

Cetinel, Sibel; Shen, Wei-Zheng; Aminpour, Maral; Bhomkar, Prasanna; Wang, Feng; Borujeny, Elham Rafie; Sharma, Kumakshi; Nayebi, Niloofar; Montemagno, Carlo

2018-02-20

Biomining of valuable metals using a target specific approach promises increased purification yields and decreased cost. Target specificity can be implemented with proteins/peptides, the biological molecules, responsible from various structural and functional pathways in living organisms by virtue of their specific recognition abilities towards both organic and inorganic materials. Phage display libraries are used to identify peptide biomolecules capable of specifically recognizing and binding organic/inorganic materials of interest with high affinities. Using combinatorial approaches, these molecular recognition elements can be converted into smart hybrid biomaterials and harnessed for biotechnological applications. Herein, we used a commercially available phage-display library to identify peptides with specific binding affinity to molybdenite (MoS 2 ) and used them to decorate magnetic NPs. These peptide-coupled NPs could capture MoS 2 under a variety of environmental conditions. The same batch of NPs could be re-used multiple times to harvest MoS 2 , clearly suggesting that this hybrid material was robust and recyclable. The advantages of this smart hybrid biomaterial with respect to its MoS 2 -binding specificity, robust performance under environmentally challenging conditions and its recyclability suggests its potential application in harvesting MoS 2 from tailing ponds and downstream mining processes.

Rolling-Element Bearings

NASA Technical Reports Server (NTRS)

Hamrock, B. J.; Anderson, W. J.

1983-01-01

Rolling element bearings are a precision, yet simple, machine element of great utility. A brief history of rolling element bearings is reviewed and the type of rolling element bearings, their geometry and kinematics, as well as the materials they are made from and the manufacturing processes they involve are described. Unloaded and unlubricated rolling element bearings, loaded but unlubricated rolling element bearings and loaded and lubricated rolling element bearings are considered. The recognition and understanding of elastohydrodynamic lubrication covered, represents one of the major development in rolling element bearings.

Stem Cell Hydrogel, Jump-Starting Zika Drug Discovery, and Engineering RNA Recognition.

PubMed

Kostic, Milka

2016-08-18

Every month the editors of Cell Chemical Biology bring you highlights of the most recent chemical biology literature that impressed them with creativity and potential for follow up work. Our August 2016 selection includes a description of hydrogels with self-tunable stiffness that are used to profile lipid metabolites during stems cell differentiation, a look at whether we can find a drug repurposing solution to Zika virus infection, and an engineered RNA recognition motif (RRM). Copyright © 2016. Published by Elsevier Ltd.

Future of biosensors: a personal view.

PubMed

Scheller, Frieder W; Yarman, Aysu; Bachmann, Till; Hirsch, Thomas; Kubick, Stefan; Renneberg, Reinhard; Schumacher, Soeren; Wollenberger, Ulla; Teller, Carsten; Bier, Frank F

2014-01-01

Biosensors representing the technological counterpart of living senses have found routine application in amperometric enzyme electrodes for decentralized blood glucose measurement, interaction analysis by surface plasmon resonance in drug development, and to some extent DNA chips for expression analysis and enzyme polymorphisms. These technologies have already reached a highly advanced level and need minor improvement at most. The dream of the "100-dollar" personal genome may come true in the next few years provided that the technological hurdles of nanopore technology or of polymerase-based single molecule sequencing can be overcome. Tailor-made recognition elements for biosensors including membrane-bound enzymes and receptors will be prepared by cell-free protein synthesis. As alternatives for biological recognition elements, molecularly imprinted polymers (MIPs) have been created. They have the potential to substitute antibodies in biosensors and biochips for the measurement of low-molecular-weight substances, proteins, viruses, and living cells. They are more stable than proteins and can be produced in large amounts by chemical synthesis. Integration of nanomaterials, especially of graphene, could lead to new miniaturized biosensors with high sensitivity and ultrafast response. In the future individual therapy will include genetic profiling of isoenzymes and polymorphic forms of drug-metabolizing enzymes especially of the cytochrome P450 family. For defining the pharmacokinetics including the clearance of a given genotype enzyme electrodes will be a useful tool. For decentralized online patient control or the integration into everyday "consumables" such as drinking water, foods, hygienic articles, clothing, or for control of air conditioners in buildings and cars and swimming pools, a new generation of "autonomous" biosensors will emerge.

Synergistic Modification Induced Specific Recognition between Histone and TRIM24 via Fluctuation Correlation Network Analysis

NASA Astrophysics Data System (ADS)

Zhang, Jinmai; Luo, Huajie; Liu, Hao; Ye, Wei; Luo, Ray; Chen, Hai-Feng

2016-04-01

Histone modification plays a key role in gene regulation and gene expression. TRIM24 as a histone reader can recognize histone modification. However the specific recognition mechanism between TRIM24 and histone modification is unsolved. Here, systems biology method of dynamics correlation network based on molecular dynamics simulation was used to answer the question. Our network analysis shows that the dynamics correlation network of H3K23ac is distinctly different from that of wild type and other modifications. A hypothesis of “synergistic modification induced recognition” is then proposed to link histone modification and TRIM24 binding. These observations were further confirmed from community analysis of networks with mutation and network perturbation. Finally, a possible recognition pathway is also identified based on the shortest path search for H3K23ac. Significant difference of recognition pathway was found among different systems due to methylation and acetylation modifications. The analysis presented here and other studies show that the dynamic network-based analysis might be a useful general strategy to study the biology of protein post-translational modification and associated recognition.

Structural requirements for recognition of the HLA-Dw14 class II epitope: A key HLA determinant associated with rheumatoid arthritis

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

Hiraiwa, Akikazu; Yamanaka, Katsuo; Kwok, W.W.

Although HLA genes have been shown to be associated with certain diseases, the basis for this association is unknown. Recent studies, however, have documented patterns of nucleotide sequence variation among some HLA genes associated with a particular disease. For rheumatoid arthritis, HLA genes in most patients have a shared nucleotide sequence encoding a key structural element of an HLA class II polypeptide; this sequence element is critical for the interaction of the HLA molecule with antigenic peptides and with responding T cells, suggestive of a direct role for this sequence element in disease susceptibility. The authors describe the serological andmore » cellular immunologic characteristics encoded by this rheumatoid arthritis-associated sequence element. Site-directed mutagenesis of the DRB1 gene was used to define amino acids critical for antibody and T-cell recognition of this structural element, focusing on residues that distinguish the rheumatoid arthritis-associated alleles Dw4 and Dw14 from a closely related allele, Dw10, not associated with disease. Both the gain and loss of rheumatoid arthritis-associated epitopes were highly dependent on three residues within a discrete domain of the HLA-DR molecule. Recognition was most strongly influenced by the following amino acids (in order): 70 > 71 > 67. Some alloreactive T-cell clones were also influenced by amino acid variation in portions of the DR molecule lying outside the shared sequence element.« less

Why an extended evolutionary synthesis is necessary

PubMed Central

2017-01-01

Since the last major theoretical integration in evolutionary biology—the modern synthesis (MS) of the 1940s—the biosciences have made significant advances. The rise of molecular biology and evolutionary developmental biology, the recognition of ecological development, niche construction and multiple inheritance systems, the ‘-omics’ revolution and the science of systems biology, among other developments, have provided a wealth of new knowledge about the factors responsible for evolutionary change. Some of these results are in agreement with the standard theory and others reveal different properties of the evolutionary process. A renewed and extended theoretical synthesis, advocated by several authors in this issue, aims to unite pertinent concepts that emerge from the novel fields with elements of the standard theory. The resulting theoretical framework differs from the latter in its core logic and predictive capacities. Whereas the MS theory and its various amendments concentrate on genetic and adaptive variation in populations, the extended framework emphasizes the role of constructive processes, ecological interactions and systems dynamics in the evolution of organismal complexity as well as its social and cultural conditions. Single-level and unilinear causation is replaced by multilevel and reciprocal causation. Among other consequences, the extended framework overcomes many of the limitations of traditional gene-centric explanation and entails a revised understanding of the role of natural selection in the evolutionary process. All these features stimulate research into new areas of evolutionary biology. PMID:28839929

Goat anti-rabbit IgG conjugated fluorescent dye-doped silica nanoparticles for human breast carcinoma cell recognition.

PubMed

Chen, Min-Yan; Chen, Ze-Zhong; Wu, Ling-Ling; Tang, Hong-Wu; Pang, Dai-Wen

2013-11-12

We report an indirect method for cancer cell recognition using photostable fluorescent silica nanoprobes as biological labels. The dye-doped fluorescent silica nanoparticles were synthesized using the water-in-oil (W/O) reverse microemulsion method. The silica matrix was produced by the controlled hydrolysis of tetraethylorthosilicate (TEOS) in water nanodroplets with the initiation of ammonia (NH3·H2O). Fluorescein isothiocyanate (FITC) or rhodamine B isothiocyanate conjugated with dextran (RBITC-Dextran) was doped in silica nanoparticles (NPs) with a size of 60 ± 5 nm as a fluorescent signal element by covalent bonding and steric hindrance, respectively. The secondary antibody, goat anti-rabbit IgG, was conjugated on the surface of the PEG-terminated modified FITC-doped or RBITC-Dextran-doped silica nanoparticles (PFSiNPs or PBSiNPs) by covalent binding to the PEG linkers using the cyanogen bromide method. The concentrations of goat anti-rabbit IgG covering the nanoprobes were quantified via the Bradford method. In the proof-of-concept experiment, an epithelial cell adhesion molecule (EpCAM) on the human breast cancer SK-Br-3 cell surface was used as the tumor marker, and the nanoparticle functionalized with rabbit anti-EpCAM antibody was employed as the nanoprobe for cancer cell recognition. Compared with fluorescent dye labeled IgG (FITC-IgG and RBITC-IgG), the designed nanoprobes display dramatically increased stability of fluorescence as well as photostability under continuous irradiation.

Saturation of recognition elements blocks evolution of new tRNA identities

PubMed Central

Saint-Léger, Adélaïde; Bello, Carla; Dans, Pablo D.; Torres, Adrian Gabriel; Novoa, Eva Maria; Camacho, Noelia; Orozco, Modesto; Kondrashov, Fyodor A.; Ribas de Pouplana, Lluís

2016-01-01

Understanding the principles that led to the current complexity of the genetic code is a central question in evolution. Expansion of the genetic code required the selection of new transfer RNAs (tRNAs) with specific recognition signals that allowed them to be matured, modified, aminoacylated, and processed by the ribosome without compromising the fidelity or efficiency of protein synthesis. We show that saturation of recognition signals blocks the emergence of new tRNA identities and that the rate of nucleotide substitutions in tRNAs is higher in species with fewer tRNA genes. We propose that the growth of the genetic code stalled because a limit was reached in the number of identity elements that can be effectively used in the tRNA structure. PMID:27386510

Attention, biological motion, and action recognition.

PubMed

Thompson, James; Parasuraman, Raja

2012-01-02

Interacting with others in the environment requires that we perceive and recognize their movements and actions. Neuroimaging and neuropsychological studies have indicated that a number of brain regions, particularly the superior temporal sulcus, are involved in a number of processes essential for action recognition, including the processing of biological motion and processing the intentions of actions. We review the behavioral and neuroimaging evidence suggesting that while some aspects of action recognition might be rapid and effective, they are not necessarily automatic. Attention is particularly important when visual information about actions is degraded or ambiguous, or if competing information is present. We present evidence indicating that neural responses associated with the processing of biological motion are strongly modulated by attention. In addition, behavioral and neuroimaging evidence shows that drawing inferences from the actions of others is attentionally demanding. The role of attention in action observation has implications for everyday social interactions and workplace applications that depend on observing, understanding and interpreting actions. Published by Elsevier Inc.

Separation and enrichment of trace ractopamine in biological samples by uniformly-sized molecularly imprinted polymers

PubMed Central

Li, Ya; Fu, Qiang; Liu, Meng; Jiao, Yuan-Yuan; Du, Wei; Yu, Chong; Liu, Jing; Chang, Chun; Lu, Jian

2012-01-01

In order to prepare a high capacity packing material for solid-phase extraction with specific recognition ability of trace ractopamine in biological samples, uniformly-sized, molecularly imprinted polymers (MIPs) were prepared by a multi-step swelling and polymerization method using methacrylic acid as a functional monomer, ethylene glycol dimethacrylate as a cross-linker, and toluene as a porogen respectively. Scanning electron microscope and specific surface area were employed to identify the characteristics of MIPs. Ultraviolet spectroscopy, Fourier transform infrared spectroscopy, Scatchard analysis and kinetic study were performed to interpret the specific recognition ability and the binding process of MIPs. The results showed that, compared with other reports, MIPs synthetized in this study showed high adsorption capacity besides specific recognition ability. The adsorption capacity of MIPs was 0.063 mmol/g at 1 mmol/L ractopamine concentration with the distribution coefficient 1.70. The resulting MIPs could be used as solid-phase extraction materials for separation and enrichment of trace ractopamine in biological samples. PMID:29403774

Meta-Research: Broadening the Scope of PLOS Biology.

PubMed

Kousta, Stavroula; Ferguson, Christine; Ganley, Emma

2016-01-01

In growing recognition of the importance of how scientific research is designed, performed, communicated, and evaluated, PLOS Biology announces a broadening of its scope to cover meta-research articles.

Comparative analysis of microbial fuel cell based biosensors developed with a mixed culture and Shewanella loihica PV-4 and underlying biological mechanism.

PubMed

Yi, Yue; Xie, Beizhen; Zhao, Ting; Liu, Hong

2018-06-13

Microbial fuel cell based biosensors (MFC-biosensors) utilize anode biofilms as biological recognition elements to monitor biochemical oxygen demand (BOD) and biotoxicity. However, the relatively poor sensitivity constrains the application of MFC-biosensors. To address this limitation, this study provided a systematic comparison of sensitivity between the MFC-biosensors constructed with two inocula. Higher biomass density and viability were both observed in the anode biofilm of the mixed culture MFC, which resulted in better sensitivity for BOD assessment. Compared with using mixed culture as inoculum, the anode biofilm developed with Shewanella loihica PV-4 presented lower content of extracellular polymeric substances and poorer ability to secrete protein under toxic shocks. Moreover, the looser structure in the S. loihica PV-4 biofilm further facilitated its susceptibilities to toxic agents. Therefore, the MFC-biosensor with a pure culture of S. loihica PV-4 delivered higher sensitivity for biotoxicity monitoring. This study proposed a new perspective to enhance sensor performance. Copyright © 2018 Elsevier Ltd. All rights reserved.

TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions

PubMed Central

2017-01-01

Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D) biomolecular structural data sets have been hindered by the geometric and biological complexity. To address this problem we introduce the element-specific persistent homology (ESPH) method. ESPH represents 3D complex geometry by one-dimensional (1D) topological invariants and retains important biological information via a multichannel image-like representation. This representation reveals hidden structure-function relationships in biomolecules. We further integrate ESPH and deep convolutional neural networks to construct a multichannel topological neural network (TopologyNet) for the predictions of protein-ligand binding affinities and protein stability changes upon mutation. To overcome the deep learning limitations from small and noisy training sets, we propose a multi-task multichannel topological convolutional neural network (MM-TCNN). We demonstrate that TopologyNet outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein folding free energy changes, and mutation induced membrane protein folding free energy changes. Availability: weilab.math.msu.edu/TDL/ PMID:28749969

A biologically plausible computational model for auditory object recognition.

PubMed

Larson, Eric; Billimoria, Cyrus P; Sen, Kamal

2009-01-01

Object recognition is a task of fundamental importance for sensory systems. Although this problem has been intensively investigated in the visual system, relatively little is known about the recognition of complex auditory objects. Recent work has shown that spike trains from individual sensory neurons can be used to discriminate between and recognize stimuli. Multiple groups have developed spike similarity or dissimilarity metrics to quantify the differences between spike trains. Using a nearest-neighbor approach the spike similarity metrics can be used to classify the stimuli into groups used to evoke the spike trains. The nearest prototype spike train to the tested spike train can then be used to identify the stimulus. However, how biological circuits might perform such computations remains unclear. Elucidating this question would facilitate the experimental search for such circuits in biological systems, as well as the design of artificial circuits that can perform such computations. Here we present a biologically plausible model for discrimination inspired by a spike distance metric using a network of integrate-and-fire model neurons coupled to a decision network. We then apply this model to the birdsong system in the context of song discrimination and recognition. We show that the model circuit is effective at recognizing individual songs, based on experimental input data from field L, the avian primary auditory cortex analog. We also compare the performance and robustness of this model to two alternative models of song discrimination: a model based on coincidence detection and a model based on firing rate.

Chemical and Biological Terrorism: Current Updates for Nurse Educators.

ERIC Educational Resources Information Center

Veenema, Tener Goodwin

2002-01-01

Describes eight topics related to chemical/biological terrorism for a standalone nursing course or integration into other courses: surveillance systems; identification, communication, and response; chemical agents; biological agents; recognition of covert exposure; patient decontamination and mass triage; availability and safety of therapies; and…

Learning by Sorting

ERIC Educational Resources Information Center

Lovrencic, Michael; Vena, Laurie

2014-01-01

A kinesthetic technique for learning to recognize elements and compounds is presented in this article. The current common pedagogy appears to merge recognition and implementation into one naming method. A separate recognition skill is critical to students being able to correctly name and write the formulas of compounds. This article focuses on…

Investigating the Influence of Biological Sex on the Behavioral and Neural Basis of Face Recognition

PubMed Central

2017-01-01

Abstract There is interest in understanding the influence of biological factors, like sex, on the organization of brain function. We investigated the influence of biological sex on the behavioral and neural basis of face recognition in healthy, young adults. In behavior, there were no sex differences on the male Cambridge Face Memory Test (CFMT)+ or the female CFMT+ (that we created) and no own-gender bias (OGB) in either group. We evaluated the functional topography of ventral stream organization by measuring the magnitude and functional neural size of 16 individually defined face-, two object-, and two place-related regions bilaterally. There were no sex differences in any of these measures of neural function in any of the regions of interest (ROIs) or in group level comparisons. These findings reveal that men and women have similar category-selective topographic organization in the ventral visual pathway. Next, in a separate task, we measured activation within the 16 face-processing ROIs specifically during recognition of target male and female faces. There were no sex differences in the magnitude of the neural responses in any face-processing region. Furthermore, there was no OGB in the neural responses of either the male or female participants. Our findings suggest that face recognition behavior, including the OGB, is not inherently sexually dimorphic. Face recognition is an essential skill for navigating human social interactions, which is reflected equally in the behavior and neural architecture of men and women. PMID:28497111

Investigating the Influence of Biological Sex on the Behavioral and Neural Basis of Face Recognition.

PubMed

Scherf, K Suzanne; Elbich, Daniel B; Motta-Mena, Natalie V

2017-01-01

There is interest in understanding the influence of biological factors, like sex, on the organization of brain function. We investigated the influence of biological sex on the behavioral and neural basis of face recognition in healthy, young adults. In behavior, there were no sex differences on the male Cambridge Face Memory Test (CFMT)+ or the female CFMT+ (that we created) and no own-gender bias (OGB) in either group. We evaluated the functional topography of ventral stream organization by measuring the magnitude and functional neural size of 16 individually defined face-, two object-, and two place-related regions bilaterally. There were no sex differences in any of these measures of neural function in any of the regions of interest (ROIs) or in group level comparisons. These findings reveal that men and women have similar category-selective topographic organization in the ventral visual pathway. Next, in a separate task, we measured activation within the 16 face-processing ROIs specifically during recognition of target male and female faces. There were no sex differences in the magnitude of the neural responses in any face-processing region. Furthermore, there was no OGB in the neural responses of either the male or female participants. Our findings suggest that face recognition behavior, including the OGB, is not inherently sexually dimorphic. Face recognition is an essential skill for navigating human social interactions, which is reflected equally in the behavior and neural architecture of men and women.

The Metals in the Biological Periodic System of the Elements: Concepts and Conjectures

PubMed Central

Maret, Wolfgang

2016-01-01

A significant number of chemical elements are either essential for life with known functions, or present in organisms with poorly defined functional outcomes. We do not know all the essential elements with certainty and we know even less about the functions of apparently non-essential elements. In this article, I discuss a basis for a biological periodic system of the elements and that biochemistry should include the elements that are traditionally part of inorganic chemistry and not only those that are in the purview of organic chemistry. A biological periodic system of the elements needs to specify what “essential” means and to which biological species it refers. It represents a snapshot of our present knowledge and is expected to undergo further modifications in the future. An integrated approach of biometal sciences called metallomics is required to understand the interactions of metal ions, the biological functions that their chemical structures acquire in the biological system, and how their usage is fine-tuned in biological species and in populations of species with genetic variations (the variome). PMID:26742035

Application of biomolecular recognition via magnetic nanoparticle in nanobiotechnology

NASA Astrophysics Data System (ADS)

Shen, Wei-Zheng; Cetinel, Sibel; Montemagno, Carlo

2018-05-01

The marriage of biomolecular recognition and magnetic nanoparticle creates tremendous opportunities in the development of advanced technology both in academic research and in industrial sectors. In this paper, we review current progress on the magnetic nanoparticle-biomolecule hybrid systems, particularly employing the recognition pairs of DNA-DNA, DNA-protein, protein-protein, and protein-inorganics in several nanobiotechnology application areas, including molecular biology, diagnostics, medical treatment, industrial biocatalysts, and environmental separations.

Automatic Recognition of Indoor Navigation Elements from Kinect Point Clouds

NASA Astrophysics Data System (ADS)

Zeng, L.; Kang, Z.

2017-09-01

This paper realizes automatically the navigating elements defined by indoorGML data standard - door, stairway and wall. The data used is indoor 3D point cloud collected by Kinect v2 launched in 2011 through the means of ORB-SLAM. By contrast, it is cheaper and more convenient than lidar, but the point clouds also have the problem of noise, registration error and large data volume. Hence, we adopt a shape descriptor - histogram of distances between two randomly chosen points, proposed by Osada and merges with other descriptor - in conjunction with random forest classifier to recognize the navigation elements (door, stairway and wall) from Kinect point clouds. This research acquires navigation elements and their 3-d location information from each single data frame through segmentation of point clouds, boundary extraction, feature calculation and classification. Finally, this paper utilizes the acquired navigation elements and their information to generate the state data of the indoor navigation module automatically. The experimental results demonstrate a high recognition accuracy of the proposed method.

Auditory perception of a human walker.

PubMed

Cottrell, David; Campbell, Megan E J

2014-01-01

When one hears footsteps in the hall, one is able to instantly recognise it as a person: this is an everyday example of auditory biological motion perception. Despite the familiarity of this experience, research into this phenomenon is in its infancy compared with visual biological motion perception. Here, two experiments explored sensitivity to, and recognition of, auditory stimuli of biological and nonbiological origin. We hypothesised that the cadence of a walker gives rise to a temporal pattern of impact sounds that facilitates the recognition of human motion from auditory stimuli alone. First a series of detection tasks compared sensitivity with three carefully matched impact sounds: footsteps, a ball bouncing, and drumbeats. Unexpectedly, participants were no more sensitive to footsteps than to impact sounds of nonbiological origin. In the second experiment participants made discriminations between pairs of the same stimuli, in a series of recognition tasks in which the temporal pattern of impact sounds was manipulated to be either that of a walker or the pattern more typical of the source event (a ball bouncing or a drumbeat). Under these conditions, there was evidence that both temporal and nontemporal cues were important in recognising theses stimuli. It is proposed that the interval between footsteps, which reflects a walker's cadence, is a cue for the recognition of the sounds of a human walking.

Electrochemical Biosensors - Sensor Principles and Architectures

PubMed Central

Grieshaber, Dorothee; MacKenzie, Robert; Vörös, Janos; Reimhult, Erik

2008-01-01

Quantification of biological or biochemical processes are of utmost importance for medical, biological and biotechnological applications. However, converting the biological information to an easily processed electronic signal is challenging due to the complexity of connecting an electronic device directly to a biological environment. Electrochemical biosensors provide an attractive means to analyze the content of a biological sample due to the direct conversion of a biological event to an electronic signal. Over the past decades several sensing concepts and related devices have been developed. In this review, the most common traditional techniques, such as cyclic voltammetry, chronoamperometry, chronopotentiometry, impedance spectroscopy, and various field-effect transistor based methods are presented along with selected promising novel approaches, such as nanowire or magnetic nanoparticle-based biosensing. Additional measurement techniques, which have been shown useful in combination with electrochemical detection, are also summarized, such as the electrochemical versions of surface plasmon resonance, optical waveguide lightmode spectroscopy, ellipsometry, quartz crystal microbalance, and scanning probe microscopy. The signal transduction and the general performance of electrochemical sensors are often determined by the surface architectures that connect the sensing element to the biological sample at the nanometer scale. The most common surface modification techniques, the various electrochemical transduction mechanisms, and the choice of the recognition receptor molecules all influence the ultimate sensitivity of the sensor. New nanotechnology-based approaches, such as the use of engineered ion-channels in lipid bilayers, the encapsulation of enzymes into vesicles, polymersomes, or polyelectrolyte capsules provide additional possibilities for signal amplification. In particular, this review highlights the importance of the precise control over the delicate interplay between surface nano-architectures, surface functionalization and the chosen sensor transducer principle, as well as the usefulness of complementary characterization tools to interpret and to optimize the sensor response. PMID:27879772

A Biological-Plausable Architecture for Shape Recognition

DTIC Science & Technology

2006-06-30

between curves. Information Processing Letters, 64, 1997. [4] Irving Biederman . Recognition-by-components: A theory of human image understanding...Psychological Review, 94(2):115–147, 1987 . 43 [5] C. Cadieu, M. Kouh, M. Riesenhuber, and T. Poggio. Shape representation in v4: Investi- gating position

Pattern Recognition by Retina-Like Devices.

ERIC Educational Resources Information Center

Weiman, Carl F. R.; Rothstein, Jerome

This study has investigated some pattern recognition capabilities of devices consisting of arrays of cooperating elements acting in parallel. The problem of recognizing straight lines in general position on the quadratic lattice has been completely solved by applying parallel acting algorithms to a special code for lines on the lattice. The…

Theory Z and American Education in an Advanced Industrial Society.

ERIC Educational Resources Information Center

Gappert, Gary

Suggesting that a major socioeconomic transformation is underway in American society, this paper discusses seven elements of an emergent post-affluent society: (1) the demographic effects of the "baby boom" generation; (2) the emergence and recognition of a post-affluent consciousness; (3) the recognition of the transcendental nature of…

Application of unsupervised pattern recognition approaches for exploration of rare earth elements in Se-Chahun iron ore, central Iran

NASA Astrophysics Data System (ADS)

Sarparandeh, Mohammadali; Hezarkhani, Ardeshir

2017-12-01

The use of efficient methods for data processing has always been of interest to researchers in the field of earth sciences. Pattern recognition techniques are appropriate methods for high-dimensional data such as geochemical data. Evaluation of the geochemical distribution of rare earth elements (REEs) requires the use of such methods. In particular, the multivariate nature of REE data makes them a good target for numerical analysis. The main subject of this paper is application of unsupervised pattern recognition approaches in evaluating geochemical distribution of REEs in the Kiruna type magnetite-apatite deposit of Se-Chahun. For this purpose, 42 bulk lithology samples were collected from the Se-Chahun iron ore deposit. In this study, 14 rare earth elements were measured with inductively coupled plasma mass spectrometry (ICP-MS). Pattern recognition makes it possible to evaluate the relations between the samples based on all these 14 features, simultaneously. In addition to providing easy solutions, discovery of the hidden information and relations of data samples is the advantage of these methods. Therefore, four clustering methods (unsupervised pattern recognition) - including a modified basic sequential algorithmic scheme (MBSAS), hierarchical (agglomerative) clustering, k-means clustering and self-organizing map (SOM) - were applied and results were evaluated using the silhouette criterion. Samples were clustered in four types. Finally, the results of this study were validated with geological facts and analysis results from, for example, scanning electron microscopy (SEM), X-ray diffraction (XRD), ICP-MS and optical mineralogy. The results of the k-means clustering and SOM methods have the best matches with reality, with experimental studies of samples and with field surveys. Since only the rare earth elements are used in this division, a good agreement of the results with lithology is considerable. It is concluded that the combination of the proposed methods and geological studies leads to finding some hidden information, and this approach has the best results compared to using only one of them.

Knowledge-based object recognition for different morphological classes of plants

NASA Astrophysics Data System (ADS)

Brendel, Thorsten; Schwanke, Joerg; Jensch, Peter F.; Megnet, Roland

1995-01-01

Micropropagation of plants is done by cutting juvenile plants and placing them into special container-boxes with nutrient-solution where the pieces can grow up and be cut again several times. To produce high amounts of biomass it is necessary to do plant micropropagation by a robotic syshoot. In this paper we describe parts of the vision syshoot that recognizes plants and their particular cutting points. Therefore, it is necessary to extract elements of the plants and relations between these elements (for example root, shoot, leaf). Different species vary in their morphological appearance, variation is also immanent in plants of the same species. Therefore, we introduce several morphological classes of plants from that we expect same recognition methods. As a result of our work we present rules which help users to create specific algorithms for object recognition of plant species.

In the Beginning Was the Familiar Voice Personally Familiar Voices in the Evolutionary and Contemporary Biology of Communication

PubMed Central

Sidtis, Diana; Kreiman, Jody

2011-01-01

The human voice is described in dialogic linguistics as an embodiment of self in a social context, contributing to expression, perception and mutual exchange of self, consciousness, inner life, and personhood. While these approaches are subjective and arise from phenomenological perspectives, scientific facts about personal vocal identity, and its role in biological development, support these views. It is our purpose to review studies of the biology of personal vocal identity -- the familiar voice pattern-- as providing an empirical foundation for the view that the human voice is an embodiment of self in the social context. Recent developments in the biology and evolution of communication are concordant with these notions, revealing that familiar voice recognition (also known as vocal identity recognition or individual vocal recognition) or contributed to survival in the earliest vocalizing species. Contemporary ethology documents the crucial role of familiar voices across animal species in signaling and perceiving internal states and personal identities. Neuropsychological studies of voice reveal multimodal cerebral associations arising across brain structures involved in memory, emotion, attention, and arousal in vocal perception and production, such that the voice represents the whole person. Although its roots are in evolutionary biology, human competence for processing layered social and personal meanings in the voice, as well as personal identity in a large repertory of familiar voice patterns, has achieved an immense sophistication. PMID:21710374

Perception of Biological Motion in Autism Spectrum Disorders

ERIC Educational Resources Information Center

Freitag, Christine M.; Konrad, Carsten; Haberlen, Melanie; Kleser, Christina; von Gontard, Alexander; Reith, Wolfgang; Troje, Nikolaus F.; Krick, Christoph

2008-01-01

In individuals with autism or autism-spectrum-disorder (ASD), conflicting results have been reported regarding the processing of biological motion tasks. As biological motion perception and recognition might be related to impaired imitation, gross motor skills and autism specific psychopathology in individuals with ASD, we performed a functional…

Biological control is more than just natural enemies

Treesearch

Dean E. Pearson

2005-01-01

The past decade has given rise to exciting new developments in the field of community ecology that have profound implications for biological control. The recognition that biological invasions offer unprecedented opportunities to investigate the nature of community assembly has swept invasive species studies to the forefront of popular ecology. Meanwhile,...

Analysis of chemical signals in red fire ants by gas chromatography and pattern recognition techniques

USDA-ARS?s Scientific Manuscript database

The combination of gas chromatography and pattern recognition (GC/PR) analysis is a powerful tool for investigating complicated biological problems. Clustering, mapping, discriminant development, etc. are necessary to analyze realistically large chromatographic data sets and to seek meaningful relat...

Label-free biosensing with functionalized nanopipette probes

PubMed Central

Umehara, Senkei; Karhanek, Miloslav; Davis, Ronald W.; Pourmand, Nader

2009-01-01

Nanopipette technology can uniquely identify biomolecules such as proteins based on differences in size, shape, and electrical charge. These differences are determined by the detection of changes in ionic current as the proteins interact with the nanopipette tip coated with probe molecules. Here we show that electrostatic, biotin-streptavidin, and antibody-antigen interactions on the nanopipette tip surface affect ionic current flowing through a 50-nm pore. Highly charged polymers interacting with the glass surface modulated the rectification property of the nanopipette electrode. Affinity-based binding between the probes tethered to the surface and their target proteins caused a change in the ionic current due to a partial blockade or an altered surface charge. These findings suggest that nanopipettes functionalized with appropriate molecular recognition elements can be used as nanosensors in biomedical and biological research. PMID:19264962

The B1 Protein Guides the Biosynthesis of a Lasso Peptide

NASA Astrophysics Data System (ADS)

Zhu, Shaozhou; Fage, Christopher D.; Hegemann, Julian D.; Mielcarek, Andreas; Yan, Dushan; Linne, Uwe; Marahiel, Mohamed A.

2016-10-01

Lasso peptides are a class of ribosomally synthesized and post-translationally modified peptides (RiPPs) with a unique lariat knot-like fold that endows them with extraordinary stability and biologically relevant activity. However, the biosynthetic mechanism of these fascinating molecules remains largely speculative. Generally, two enzymes (B for processing and C for cyclization) are required to assemble the unusual knot-like structure. Several subsets of lasso peptide gene clusters feature a “split” B protein on separate open reading frames (B1 and B2), suggesting distinct functions for the B protein in lasso peptide biosynthesis. Herein, we provide new insights into the role of the RiPP recognition element (RRE) PadeB1, characterizing its capacity to bind the paeninodin leader peptide and deliver its peptide substrate to PadeB2 for processing.

Commentary on the 1978 Kristiansand Conference on Nickel Toxicology

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

Sunderman, F.W. Jr.

1978-01-01

Abstracts of presentations at the 1978 Kristiansand Conference on Nickel Toxicity are presented. Major developments in the study of nickel toxicity are summarized. They include: the demonstration that nickel is an essential trace element; the discovery of the first nickel metalloenzyme; the discovery that ureases are also nickel enzymes; the improvement of analytical methods for the determination of nickel in biological material; the recognition of the need to monitor occupationl exposures to nickel; the observation that nickel carbonyl is a potent teratogen in rats; the finding that internal exposure to nickel by ingestion plays a role in exacerbation of nickelmore » eczema in man; and the observation that intrarenal injection of nickel subsulfide in rats induces marked polycythemia which appears to be mediated by enhanced renal synthesis and/or release of erythropoietin.« less

Perception of biological motion from size-invariant body representations.

PubMed

Lappe, Markus; Wittinghofer, Karin; de Lussanet, Marc H E

2015-01-01

The visual recognition of action is one of the socially most important and computationally demanding capacities of the human visual system. It combines visual shape recognition with complex non-rigid motion perception. Action presented as a point-light animation is a striking visual experience for anyone who sees it for the first time. Information about the shape and posture of the human body is sparse in point-light animations, but it is essential for action recognition. In the posturo-temporal filter model of biological motion perception posture information is picked up by visual neurons tuned to the form of the human body before body motion is calculated. We tested whether point-light stimuli are processed through posture recognition of the human body form by using a typical feature of form recognition, namely size invariance. We constructed a point-light stimulus that can only be perceived through a size-invariant mechanism. This stimulus changes rapidly in size from one image to the next. It thus disrupts continuity of early visuo-spatial properties but maintains continuity of the body posture representation. Despite this massive manipulation at the visuo-spatial level, size-changing point-light figures are spontaneously recognized by naive observers, and support discrimination of human body motion.

Auditory perception vs. recognition: representation of complex communication sounds in the mouse auditory cortical fields.

PubMed

Geissler, Diana B; Ehret, Günter

2004-02-01

Details of brain areas for acoustical Gestalt perception and the recognition of species-specific vocalizations are not known. Here we show how spectral properties and the recognition of the acoustical Gestalt of wriggling calls of mouse pups based on a temporal property are represented in auditory cortical fields and an association area (dorsal field) of the pups' mothers. We stimulated either with a call model releasing maternal behaviour at a high rate (call recognition) or with two models of low behavioural significance (perception without recognition). Brain activation was quantified using c-Fos immunocytochemistry, counting Fos-positive cells in electrophysiologically mapped auditory cortical fields and the dorsal field. A frequency-specific labelling in two primary auditory fields is related to call perception but not to the discrimination of the biological significance of the call models used. Labelling related to call recognition is present in the second auditory field (AII). A left hemisphere advantage of labelling in the dorsoposterior field seems to reflect an integration of call recognition with maternal responsiveness. The dorsal field is activated only in the left hemisphere. The spatial extent of Fos-positive cells within the auditory cortex and its fields is larger in the left than in the right hemisphere. Our data show that a left hemisphere advantage in processing of a species-specific vocalization up to recognition is present in mice. The differential representation of vocalizations of high vs. low biological significance, as seen only in higher-order and not in primary fields of the auditory cortex, is discussed in the context of perceptual strategies.

Nestedness across biological scales

PubMed Central

Marquitti, Flavia M. D.; Raimundo, Rafael L. G.; Sebastián-González, Esther; Coltri, Patricia P.; Perez, S. Ivan; Brandt, Débora Y. C.; Nunes, Kelly; Daura-Jorge, Fábio G.; Floeter, Sergio R.; Guimarães, Paulo R.

2017-01-01

Biological networks pervade nature. They describe systems throughout all levels of biological organization, from molecules regulating metabolism to species interactions that shape ecosystem dynamics. The network thinking revealed recurrent organizational patterns in complex biological systems, such as the formation of semi-independent groups of connected elements (modularity) and non-random distributions of interactions among elements. Other structural patterns, such as nestedness, have been primarily assessed in ecological networks formed by two non-overlapping sets of elements; information on its occurrence on other levels of organization is lacking. Nestedness occurs when interactions of less connected elements form proper subsets of the interactions of more connected elements. Only recently these properties began to be appreciated in one-mode networks (where all elements can interact) which describe a much wider variety of biological phenomena. Here, we compute nestedness in a diverse collection of one-mode networked systems from six different levels of biological organization depicting gene and protein interactions, complex phenotypes, animal societies, metapopulations, food webs and vertebrate metacommunities. Our findings suggest that nestedness emerge independently of interaction type or biological scale and reveal that disparate systems can share nested organization features characterized by inclusive subsets of interacting elements with decreasing connectedness. We primarily explore the implications of a nested structure for each of these studied systems, then theorize on how nested networks are assembled. We hypothesize that nestedness emerges across scales due to processes that, although system-dependent, may share a general compromise between two features: specificity (the number of interactions the elements of the system can have) and affinity (how these elements can be connected to each other). Our findings suggesting occurrence of nestedness throughout biological scales can stimulate the debate on how pervasive nestedness may be in nature, while the theoretical emergent principles can aid further research on commonalities of biological networks. PMID:28166284

Non-native, N-terminal Hsp70 Molecular Motor Recognition Elements in Transit Peptides Support Plastid Protein Translocation*

PubMed Central

Chotewutmontri, Prakitchai; Bruce, Barry D.

2015-01-01

Previously, we identified the N-terminal domain of transit peptides (TPs) as a major determinant for the translocation step in plastid protein import. Analysis of Arabidopsis TP dataset revealed that this domain has two overlapping characteristics, highly uncharged and Hsp70-interacting. To investigate these two properties, we replaced the N-terminal domains of the TP of the small subunit of ribulose-1,5-bisphosphate carboxylase/oxygenase and its reverse peptide with a series of unrelated peptides whose affinities to the chloroplast stromal Hsp70 have been determined. Bioinformatic analysis indicated that eight out of nine peptides in this series are not similar to the TP N terminus. Using in vivo and in vitro protein import assays, the majority of the precursors containing Hsp70-binding elements were targeted to plastids, whereas none of the chimeric precursors lacking an N-terminal Hsp70-binding element were targeted to the plastids. Moreover, a pulse-chase assay showed that two chimeric precursors with the most uncharged peptides failed to translocate into the stroma. The ability of multiple unrelated Hsp70-binding elements to support protein import verified that the majority of TPs utilize an N-terminal Hsp70-binding domain during translocation and expand the mechanistic view of the import process. This work also indicates that synthetic biology may be utilized to create de novo TPs that exceed the targeting activity of naturally occurring sequences. PMID:25645915

Concept Recognition in an Automatic Text-Processing System for the Life Sciences.

ERIC Educational Resources Information Center

Vleduts-Stokolov, Natasha

1987-01-01

Describes a system developed for the automatic recognition of biological concepts in titles of scientific articles; reports results of several pilot experiments which tested the system's performance; analyzes typical ambiguity problems encountered by the system; describes a disambiguation technique that was developed; and discusses future plans…

Foveational Complexity in Single Word Identification: Contralateral Visual Pathways Are Advantaged over Ipsilateral Pathways

ERIC Educational Resources Information Center

Obregon, Mateo; Shillcock, Richard

2012-01-01

Recognition of a single word is an elemental task in innumerable cognitive psychology experiments, but involves unexpected complexity. We test a controversial claim that the human fovea is vertically divided, with each half projecting to either the contralateral or ipsilateral hemisphere, thereby influencing foveal word recognition. We report a…

Bridging the gap: from biometrics to forensics.

PubMed

Jain, Anil K; Ross, Arun

2015-08-05

Biometric recognition, or simply biometrics, refers to automated recognition of individuals based on their behavioural and biological characteristics. The success of fingerprints in forensic science and law enforcement applications, coupled with growing concerns related to border control, financial fraud and cyber security, has generated a huge interest in using fingerprints, as well as other biological traits, for automated person recognition. It is, therefore, not surprising to see biometrics permeating various segments of our society. Applications include smartphone security, mobile payment, border crossing, national civil registry and access to restricted facilities. Despite these successful deployments in various fields, there are several existing challenges and new opportunities for person recognition using biometrics. In particular, when biometric data is acquired in an unconstrained environment or if the subject is uncooperative, the quality of the ensuing biometric data may not be amenable for automated person recognition. This is particularly true in crime-scene investigations, where the biological evidence gleaned from a scene may be of poor quality. In this article, we first discuss how biometrics evolved from forensic science and how its focus is shifting back to its origin in order to address some challenging problems. Next, we enumerate the similarities and differences between biometrics and forensics. We then present some applications where the principles of biometrics are being successfully leveraged into forensics in order to solve critical problems in the law enforcement domain. Finally, we discuss new collaborative opportunities for researchers in biometrics and forensics, in order to address hitherto unsolved problems that can benefit society at large. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Bridging the gap: from biometrics to forensics

PubMed Central

Jain, Anil K.; Ross, Arun

2015-01-01

Biometric recognition, or simply biometrics, refers to automated recognition of individuals based on their behavioural and biological characteristics. The success of fingerprints in forensic science and law enforcement applications, coupled with growing concerns related to border control, financial fraud and cyber security, has generated a huge interest in using fingerprints, as well as other biological traits, for automated person recognition. It is, therefore, not surprising to see biometrics permeating various segments of our society. Applications include smartphone security, mobile payment, border crossing, national civil registry and access to restricted facilities. Despite these successful deployments in various fields, there are several existing challenges and new opportunities for person recognition using biometrics. In particular, when biometric data is acquired in an unconstrained environment or if the subject is uncooperative, the quality of the ensuing biometric data may not be amenable for automated person recognition. This is particularly true in crime-scene investigations, where the biological evidence gleaned from a scene may be of poor quality. In this article, we first discuss how biometrics evolved from forensic science and how its focus is shifting back to its origin in order to address some challenging problems. Next, we enumerate the similarities and differences between biometrics and forensics. We then present some applications where the principles of biometrics are being successfully leveraged into forensics in order to solve critical problems in the law enforcement domain. Finally, we discuss new collaborative opportunities for researchers in biometrics and forensics, in order to address hitherto unsolved problems that can benefit society at large. PMID:26101280

Elements of an Employee Motivation Program

ERIC Educational Resources Information Center

Ward, Ernest H.

1974-01-01

Ten elements which should be present in an employee motivation program are discussed in the context of achieving increased acceptance of organizational goals. They are: participation, performance measurement, knowledge of results, recognition; attitude measurement, communication, publicity, work assignment, work research, and supervisor motivation…

Investigating biomolecular recognition at the cell surface using atomic force microscopy.

PubMed

Wang, Congzhou; Yadavalli, Vamsi K

2014-05-01

Probing the interaction forces that drive biomolecular recognition on cell surfaces is essential for understanding diverse biological processes. Force spectroscopy has been a widely used dynamic analytical technique, allowing measurement of such interactions at the molecular and cellular level. The capabilities of working under near physiological environments, combined with excellent force and lateral resolution make atomic force microscopy (AFM)-based force spectroscopy a powerful approach to measure biomolecular interaction forces not only on non-biological substrates, but also on soft, dynamic cell surfaces. Over the last few years, AFM-based force spectroscopy has provided biophysical insight into how biomolecules on cell surfaces interact with each other and induce relevant biological processes. In this review, we focus on describing the technique of force spectroscopy using the AFM, specifically in the context of probing cell surfaces. We summarize recent progress in understanding the recognition and interactions between macromolecules that may be found at cell surfaces from a force spectroscopy perspective. We further discuss the challenges and future prospects of the application of this versatile technique. Copyright © 2014 Elsevier Ltd. All rights reserved.

Using ruthenium polypyridyl functionalized ZnO mesocrystals and gold nanoparticle dotted graphene composite for biological recognition and electrochemiluminescence biosensing

NASA Astrophysics Data System (ADS)

Liu, Suli; Zhang, Jinxing; Tu, Wenwen; Bao, Jianchun; Dai, Zhihui

2014-01-01

Using ruthenium polypyridyl functionalized ZnO mesocrystals as bionanolabels, a universal biological recognition and biosensing platform based on gold nanoparticle (AuNP) dotted reduced graphene oxide (rGO) composite was developed. AuNP-rGO accelerated electron transfer between the detection probe and the electrode, and increased the surface area of the working electrode to load greater amounts of the capture antibodies. The large surface area of ZnO mesocrystals was beneficial for loading a high content ruthenium polypyridyl complex, leading to an enhanced electrochemiluminescence signal. Using α-fetoprotein (AFP) as a model, a simple and sensitive sandwich-type electrochemiluminescence biosensor with tripropylamine (TPrA) as a coreactant for detection of AFP was constructed. The designed biosensor provided a good linear range from 0.04 to 500 ng mL-1 with a low detection limit of 0.031 ng mL-1 at a S/N of 3 for AFP determination. The proposed biological recognition and biosensing platform extended the application of ruthenium polypyridyl functionalized ZnO mesocrystals, which provided a new promising prospect.

Comparative Study on Interaction of Form and Motion Processing Streams by Applying Two Different Classifiers in Mechanism for Recognition of Biological Movement

PubMed Central

2014-01-01

Research on psychophysics, neurophysiology, and functional imaging shows particular representation of biological movements which contains two pathways. The visual perception of biological movements formed through the visual system called dorsal and ventral processing streams. Ventral processing stream is associated with the form information extraction; on the other hand, dorsal processing stream provides motion information. Active basic model (ABM) as hierarchical representation of the human object had revealed novelty in form pathway due to applying Gabor based supervised object recognition method. It creates more biological plausibility along with similarity with original model. Fuzzy inference system is used for motion pattern information in motion pathway creating more robustness in recognition process. Besides, interaction of these paths is intriguing and many studies in various fields considered it. Here, the interaction of the pathways to get more appropriated results has been investigated. Extreme learning machine (ELM) has been implied for classification unit of this model, due to having the main properties of artificial neural networks, but crosses from the difficulty of training time substantially diminished in it. Here, there will be a comparison between two different configurations, interactions using synergetic neural network and ELM, in terms of accuracy and compatibility. PMID:25276860

Photoinduced Regeneration of an Aptamer-Based Electrochemical Sensor for Sensitively Detecting Adenosine Triphosphate.

PubMed

Zhang, Xiaoyu; Song, Chunxia; Yang, Ke; Hong, Wenwen; Lu, Ying; Yu, Ping; Mao, Lanqun

2018-04-17

Electrochemical aptasensors generally include three elements, that is, recognition element, signal-transformation element, and regeneration element. In this study, a new adenosine triphosphate (ATP) aptasensor is developed by combining three elements into one DNA oligonucleotide chain. In the DNA oligonucleotide chain, DNA aptamer is used as the recognition element, ferrocene group attached at the 3'-end of the aptamer is used as the signal-transformation element, and azobenzene moiety embedded into the DNA chain is used as the regeneration element. In addition to the similar analytical properties with the traditional ones, the aptasensor developed here is easily regenerated with UV-light irradiation. The current response recorded on the aptasensor increases with increasing the concentration of ATP in the incubation solution and is linear with the logarithm of ATP concentration in the range from 1 nM to 100 μM. The limit of detection is 0.5 nM (S/N = 3). The basal level of ATP in the rat brain cortex microdialysate is determined to be 21.33 ± 4.1 nM ( n = 3). After being challenged with ATP, the aptasensor could be readily regenerated by UV-light irradiation for more than seven cycles. The regeneration of the aptasensor is proposed to be regulated by conversing azobenzene from its trans to cis form under UV irradiation.

Liquid lens: advances in adaptive optics

NASA Astrophysics Data System (ADS)

Casey, Shawn Patrick

2010-12-01

'Liquid lens' technologies promise significant advancements in machine vision and optical communications systems. Adaptations for machine vision, human vision correction, and optical communications are used to exemplify the versatile nature of this technology. Utilization of liquid lens elements allows the cost effective implementation of optical velocity measurement. The project consists of a custom image processor, camera, and interface. The images are passed into customized pattern recognition and optical character recognition algorithms. A single camera would be used for both speed detection and object recognition.

Memristive Computational Architecture of an Echo State Network for Real-Time Speech Emotion Recognition

DTIC Science & Technology

2015-05-28

recognition is simpler and requires less computational resources compared to other inputs such as facial expressions . The Berlin database of Emotional ...Processing Magazine, IEEE, vol. 18, no. 1, pp. 32– 80, 2001. [15] K. R. Scherer, T. Johnstone, and G. Klasmeyer, “Vocal expression of emotion ...Network for Real-Time Speech- Emotion Recognition 5a. CONTRACT NUMBER IN-HOUSE 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 62788F 6. AUTHOR(S) Q

Indirect effects of host-specific biological control agents

Treesearch

Dean E. Pearson; Ragan M. Callaway

2003-01-01

Biological control is a crucial tool in the battle against biological invasions, but biocontrol agents can have a deleterious impact on native species. Recognition of risks associated with host shifting has increased the emphasis on host specificity of biocontrol agents for invasive weeds. However, recent studies indicate host-specific biocontrol agents can...

Conserving forest biological diversity: How the Montreal Process helps achieve sustainability

Treesearch

Mark Nelson; Guy Robertson; Kurt Riitters

2015-01-01

Forests support a variety of ecosystems, species and genes — collectively referred to as biological diversity — along with important processes that tie these all together. With the growing recognition that biological diversity contributes to human welfare in a number of important ways such as providing food, medicine and fiber (provisioning services...

The Coding of Biological Information: From Nucleotide Sequence to Protein Recognition

NASA Astrophysics Data System (ADS)

Štambuk, Nikola

The paper reviews the classic results of Swanson, Dayhoff, Grantham, Blalock and Root-Bernstein, which link genetic code nucleotide patterns to the protein structure, evolution and molecular recognition. Symbolic representation of the binary addresses defining particular nucleotide and amino acid properties is discussed, with consideration of: structure and metric of the code, direct correspondence between amino acid and nucleotide information, and molecular recognition of the interacting protein motifs coded by the complementary DNA and RNA strands.

View-Based Models of 3D Object Recognition and Class-Specific Invariance

DTIC Science & Technology

1994-04-01

underlie recognition of geon-like com- ponents (see Edelman, 1991 and Biederman , 1987 ). I(X -_ ta)II1y = (X - ta)TWTW(x -_ ta) (3) View-invariant features...Institute of Technology, 1993. neocortex. Biological Cybernetics, 1992. 14] I. Biederman . Recognition by components: a theory [20] B. Olshausen, C...Anderson, and D. Van Essen. A of human image understanding. Psychol. Review, neural model of visual attention and invariant pat- 94:115-147, 1987 . tern

Intelligent data processing of an ultrasonic sensor system for pattern recognition improvements

NASA Astrophysics Data System (ADS)

Na, Seung You; Park, Min-Sang; Hwang, Won-Gul; Kee, Chang-Doo

1999-05-01

Though conventional time-of-flight ultrasonic sensor systems are popular due to the advantages of low cost and simplicity, the usage of the sensors is rather narrowly restricted within object detection and distance readings. There is a strong need to enlarge the amount of environmental information for mobile applications to provide intelligent autonomy. Wide sectors of such neighboring object recognition problems can be satisfactorily handled with coarse vision data such as sonar maps instead of accurate laser or optic measurements. For the usage of object pattern recognition, ultrasonic senors have inherent shortcomings of poor directionality and specularity which result in low spatial resolution and indistinctiveness of object patterns. To resolve these problems an array of increased number of sensor elements has been used for large objects. In this paper we propose a method of sensor array system with improved recognition capability using electronic circuits accompanying the sensor array and neuro-fuzzy processing of data fusion. The circuit changes transmitter output voltages of array elements in several steps. Relying upon the known sensor characteristics, a set of different return signals from neighboring senors is manipulated to provide an enhanced pattern recognition in the aspects of inclination angle, size and shift as well as distance of objects. The results show improved resolution of the measurements for smaller targets.

Comparison of Methods of Detection of Exceptional Sequences in Prokaryotic Genomes.

PubMed

Rusinov, I S; Ershova, A S; Karyagina, A S; Spirin, S A; Alexeevski, A V

2018-02-01

Many proteins need recognition of specific DNA sequences for functioning. The number of recognition sites and their distribution along the DNA might be of biological importance. For example, the number of restriction sites is often reduced in prokaryotic and phage genomes to decrease the probability of DNA cleavage by restriction endonucleases. We call a sequence an exceptional one if its frequency in a genome significantly differs from one predicted by some mathematical model. An exceptional sequence could be either under- or over-represented, depending on its frequency in comparison with the predicted one. Exceptional sequences could be considered biologically meaningful, for example, as targets of DNA-binding proteins or as parts of abundant repetitive elements. Several methods to predict frequency of a short sequence in a genome, based on actual frequencies of certain its subsequences, are used. The most popular are methods based on Markov chain models. But any rigorous comparison of the methods has not previously been performed. We compared three methods for the prediction of short sequence frequencies: the maximum-order Markov chain model-based method, the method that uses geometric mean of extended Markovian estimates, and the method that utilizes frequencies of all subsequences including discontiguous ones. We applied them to restriction sites in complete genomes of 2500 prokaryotic species and demonstrated that the results depend greatly on the method used: lists of 5% of the most under-represented sites differed by up to 50%. The method designed by Burge and coauthors in 1992, which utilizes all subsequences of the sequence, showed a higher precision than the other two methods both on prokaryotic genomes and randomly generated sequences after computational imitation of selective pressure. We propose this method as the first choice for detection of exceptional sequences in prokaryotic genomes.

Neural networks and applications tutorial

NASA Astrophysics Data System (ADS)

Guyon, I.

1991-09-01

The importance of neural networks has grown dramatically during this decade. While only a few years ago they were primarily of academic interest, now dozens of companies and many universities are investigating the potential use of these systems and products are beginning to appear. The idea of building a machine whose architecture is inspired by that of the brain has roots which go far back in history. Nowadays, technological advances of computers and the availability of custom integrated circuits, permit simulations of hundreds or even thousands of neurons. In conjunction, the growing interest in learning machines, non-linear dynamics and parallel computation spurred renewed attention in artificial neural networks. Many tentative applications have been proposed, including decision systems (associative memories, classifiers, data compressors and optimizers), or parametric models for signal processing purposes (system identification, automatic control, noise canceling, etc.). While they do not always outperform standard methods, neural network approaches are already used in some real world applications for pattern recognition and signal processing tasks. The tutorial is divided into six lectures, that where presented at the Third Graduate Summer Course on Computational Physics (September 3-7, 1990) on Parallel Architectures and Applications, organized by the European Physical Society: (1) Introduction: machine learning and biological computation. (2) Adaptive artificial neurons (perceptron, ADALINE, sigmoid units, etc.): learning rules and implementations. (3) Neural network systems: architectures, learning algorithms. (4) Applications: pattern recognition, signal processing, etc. (5) Elements of learning theory: how to build networks which generalize. (6) A case study: a neural network for on-line recognition of handwritten alphanumeric characters.

Unification of automatic target tracking and automatic target recognition

NASA Astrophysics Data System (ADS)

Schachter, Bruce J.

2014-06-01

The subject being addressed is how an automatic target tracker (ATT) and an automatic target recognizer (ATR) can be fused together so tightly and so well that their distinctiveness becomes lost in the merger. This has historically not been the case outside of biology and a few academic papers. The biological model of ATT∪ATR arises from dynamic patterns of activity distributed across many neural circuits and structures (including retina). The information that the brain receives from the eyes is "old news" at the time that it receives it. The eyes and brain forecast a tracked object's future position, rather than relying on received retinal position. Anticipation of the next moment - building up a consistent perception - is accomplished under difficult conditions: motion (eyes, head, body, scene background, target) and processing limitations (neural noise, delays, eye jitter, distractions). Not only does the human vision system surmount these problems, but it has innate mechanisms to exploit motion in support of target detection and classification. Biological vision doesn't normally operate on snapshots. Feature extraction, detection and recognition are spatiotemporal. When vision is viewed as a spatiotemporal process, target detection, recognition, tracking, event detection and activity recognition, do not seem as distinct as they are in current ATT and ATR designs. They appear as similar mechanism taking place at varying time scales. A framework is provided for unifying ATT and ATR.

Impaired visual recognition of biological motion in schizophrenia.

PubMed

Kim, Jejoong; Doop, Mikisha L; Blake, Randolph; Park, Sohee

2005-09-15

Motion perception deficits have been suggested to be an important feature of schizophrenia but the behavioral consequences of such deficits are unknown. Biological motion refers to the movements generated by living beings. The human visual system rapidly and effortlessly detects and extracts socially relevant information from biological motion. A deficit in biological motion perception may have significant consequences for detecting and interpreting social information. Schizophrenia patients and matched healthy controls were tested on two visual tasks: recognition of human activity portrayed in point-light animations (biological motion task) and a perceptual control task involving detection of a grouped figure against the background noise (global-form task). Both tasks required detection of a global form against background noise but only the biological motion task required the extraction of motion-related information. Schizophrenia patients performed as well as the controls in the global-form task, but were significantly impaired on the biological motion task. In addition, deficits in biological motion perception correlated with impaired social functioning as measured by the Zigler social competence scale [Zigler, E., Levine, J. (1981). Premorbid competence in schizophrenia: what is being measured? Journal of Consulting and Clinical Psychology, 49, 96-105.]. The deficit in biological motion processing, which may be related to the previously documented deficit in global motion processing, could contribute to abnormal social functioning in schizophrenia.

Structural analysis of natural textures.

PubMed

Vilnrotter, F M; Nevatia, R; Price, K E

1986-01-01

Many textures can be described structurally, in terms of the individual textural elements and their spatial relationships. This paper describes a system to generate useful descriptions of natural textures in these terms. The basic approach is to determine an initial, partial description of the elements using edge features. This description controls the extraction of the texture elements. The elements are grouped by type, and spatial relationships between elements are computed. The descriptions are shown to be useful for recognition of the textures, and for reconstruction of periodic textures.

Optical sensing: recognition elements and devices

NASA Astrophysics Data System (ADS)

Gauglitz, Guenter G.

2012-09-01

The requirements in chemical and biochemical sensing with respect to recognition elements, avoiding non-specific interactions, and high loading of the surface for detection of low concentrations as well as optimized detection systems are discussed. Among the many detection principles the optical techniques are classified. Methods using labeled compounds like Total Internal Reflection Fluorescence (TIRF) and direct optical methods like micro reflectometry or refractometry are discussed in comparison. Reflectometric Interference Spectroscopy (RIfS) is presented as a robust simple method for biosensing. As applications, trace analysis of endocrine disruptors in water, hormones in food, detection of viruses and bacteria in food and clinical diagnostics are discussed.

Gender Recognition from Point-Light Walkers

ERIC Educational Resources Information Center

Pollick, Frank E.; Kay, Jim W.; Heim, Katrin; Stringer, Rebecca

2005-01-01

Point-light displays of human gait provide information sufficient to recognize the gender of a walker and are taken as evidence of the exquisite tuning of the visual system to biological motion. The authors revisit this topic with the goals of quantifying human efficiency at gender recognition. To achieve this, the authors first derive an ideal…

Template Recognition Mechanisms by Replicase Proteins Differ between Bipartite Positive-Strand Genomic RNAs of a Plant Virus▿

PubMed Central

Iwakawa, Hiro-oki; Mine, Akira; Hyodo, Kiwamu; An, Mengnan; Kaido, Masanori; Mise, Kazuyuki; Okuno, Tetsuro

2011-01-01

Recognition of RNA templates by viral replicase proteins is one of the key steps in the replication process of all RNA viruses. However, the mechanisms underlying this phenomenon, including primary RNA elements that are recognized by the viral replicase proteins, are not well understood. Here, we used aptamer pulldown assays with membrane fractionation and protein-RNA coimmunoprecipitation in a cell-free viral translation/replication system to investigate how viral replicase proteins recognize the bipartite genomic RNAs of the Red clover necrotic mosaic virus (RCNMV). RCNMV replicase proteins bound specifically to a Y-shaped RNA element (YRE) located in the 3′ untranslated region (UTR) of RNA2, which also interacted with the 480-kDa replicase complexes that contain viral and host proteins. The replicase-YRE interaction recruited RNA2 to the membrane fraction. Conversely, RNA1 fragments failed to interact with the replicase proteins supplied in trans. The results of protein-RNA coimmunoprecipitation assays suggest that RNA1 interacts with the replicase proteins coupled with their translation. Thus, the initial template recognition mechanisms employed by the replicase differ between RCNMV bipartite genomic RNAs and RNA elements are primary determinants of the differential replication mechanism. PMID:20980498

Image processing and recognition for biological images

PubMed Central

Uchida, Seiichi

2013-01-01

This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. As the main tasks of image processing, this paper introduces gray-level transformation, binarization, image filtering, image segmentation, visual object tracking, optical flow and image registration. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. This paper overviews its two main modules, that is, feature extraction module and classification module. Throughout the paper, it will be emphasized that bioimage is a very difficult target for even state-of-the-art image processing and pattern recognition techniques due to noises, deformations, etc. This paper is expected to be one tutorial guide to bridge biology and image processing researchers for their further collaboration to tackle such a difficult target. PMID:23560739

77 FR 43370 - TUV Rheinland of North America, Inc.; Application for Expansion of Recognition

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-24

... scope of recognition has three elements: (1) The type of products the NRTL may test, with each type... Assistant Secretary will make the final decision on granting the application and, in making this decision... notice of this final decision in the Federal Register. Authority and Signature David Michaels, Ph.D., MPH...

Characterization of edible seaweed harvested on the Galician coast (northwestern Spain) using pattern recognition techniques and major and trace element data.

PubMed

Romarís-Hortas, Vanessa; García-Sartal, Cristina; Barciela-Alonso, María Carmen; Moreda-Piñeiro, Antonio; Bermejo-Barrera, Pilar

2010-02-10

Major and trace elements in North Atlantic seaweed originating from Galicia (northwestern Spain) were determined by using inductively coupled plasma-optical emission spectrometry (ICP-OES) (Ba, Ca, Cu, K, Mg, Mn, Na, Sr, and Zn), inductively coupled plasma-mass spectrometry (ICP-MS) (Br and I) and hydride generation-atomic fluorescence spectrometry (HG-AFS) (As). Pattern recognition techniques were then used to classify the edible seaweed according to their type (red, brown, and green seaweed) and also their variety (Wakame, Fucus, Sea Spaghetti, Kombu, Dulse, Nori, and Sea Lettuce). Principal component analysis (PCA) and cluster analysis (CA) were used as exploratory techniques, and linear discriminant analysis (LDA) and soft independent modeling of class analogy (SIMCA) were used as classification procedures. In total, t12 elements were determined in a range of 35 edible seaweed samples (20 brown seaweed, 10 red seaweed, 4 green seaweed, and 1 canned seaweed). Natural groupings of the samples (brown, red, and green types) were observed using PCA and CA (squared Euclidean distance between objects and Ward method as clustering procedure). The application of LDA gave correct assignation percentages of 100% for brown, red, and green types at a significance level of 5%. However, a satisfactory classification (recognition and prediction) using SIMCA was obtained only for red seaweed (100% of cases correctly classified), whereas percentages of 89 and 80% were obtained for brown seaweed for recognition (training set) and prediction (testing set), respectively.

Biosensor technology: technology push versus market pull.

PubMed

Luong, John H T; Male, Keith B; Glennon, Jeremy D

2008-01-01

Biosensor technology is based on a specific biological recognition element in combination with a transducer for signal processing. Since its inception, biosensors have been expected to play a significant analytical role in medicine, agriculture, food safety, homeland security, environmental and industrial monitoring. However, the commercialization of biosensor technology has significantly lagged behind the research output as reflected by a plethora of publications and patenting activities. The rationale behind the slow and limited technology transfer could be attributed to cost considerations and some key technical barriers. Analytical chemistry has changed considerably, driven by automation, miniaturization, and system integration with high throughput for multiple tasks. Such requirements pose a great challenge in biosensor technology which is often designed to detect one single or a few target analytes. Successful biosensors must be versatile to support interchangeable biorecognition elements, and in addition miniaturization must be feasible to allow automation for parallel sensing with ease of operation at a competitive cost. A significant upfront investment in research and development is a prerequisite in the commercialization of biosensors. The progress in such endeavors is incremental with limited success, thus, the market entry for a new venture is very difficult unless a niche product can be developed with a considerable market volume.

Pattern reverberation in networks of excitable systems with connection delays

NASA Astrophysics Data System (ADS)

Lücken, Leonhard; Rosin, David P.; Worlitzer, Vasco M.; Yanchuk, Serhiy

2017-01-01

We consider the recurrent pulse-coupled networks of excitable elements with delayed connections, which are inspired by the biological neural networks. If the delays are tuned appropriately, the network can either stay in the steady resting state, or alternatively, exhibit a desired spiking pattern. It is shown that such a network can be used as a pattern-recognition system. More specifically, the application of the correct pattern as an external input to the network leads to a self-sustained reverberation of the encoded pattern. In terms of the coupling structure, the tolerance and the refractory time of the individual systems, we determine the conditions for the uniqueness of the sustained activity, i.e., for the functionality of the network as an unambiguous pattern detector. We point out the relation of the considered systems with cyclic polychronous groups and show how the assumed delay configurations may arise in a self-organized manner when a spike-time dependent plasticity of the connection delays is assumed. As excitable elements, we employ the simplistic coincidence detector models as well as the Hodgkin-Huxley neuron models. Moreover, the system is implemented experimentally on a Field-Programmable Gate Array.

The recognition signal hypothesis for the adaptive evolution of religion : a phylogenetic test with Christian denominations.

PubMed

Matthews, Luke J

2012-06-01

Recent research on the evolution of religion has focused on whether religion is an unselected by-product of evolutionary processes or if it is instead an adaptation by natural selection. Adaptive hypotheses for religion include direct fitness benefits from improved health and indirect fitness benefits mediated by costly signals and/or cultural group selection. Herein, I propose that religious denominations achieve indirect fitness gains for members through the use of ecologically arbitrary beliefs, rituals, and moral rules that function as recognition markers of cultural inheritance analogous to kin and species recognition of genetic inheritance in biology. This recognition signal hypotheses could act in concert with either costly signaling or cultural group selection to produce evolutionarily altruistic behaviors within denominations. Using a cultural phylogenetic analysis, I show that a large set of religious behaviors among extant Christian denominations supports the prediction of the recognition signal hypothesis that characters change more frequently near historical schisms. By incorporating demographic data into the model, I show that more-distinctive denominations, as measured through dissimilar characteristics, appear to be protected from intrusion by nonmembers in mixed-denomination households, and that they may be experiencing greater biological growth of their populations even in the present day.

INAA Application for Trace Element Determination in Biological Reference Material

NASA Astrophysics Data System (ADS)

Atmodjo, D. P. D.; Kurniawati, S.; Lestiani, D. D.; Adventini, N.

2017-06-01

Trace element determination in biological samples is often used in the study of health and toxicology. Determination change to its essentiality and toxicity of trace element require an accurate determination method, which implies that a good Quality Control (QC) procedure should be performed. In this study, QC for trace element determination in biological samples was applied by analyzing the Standard Reference Material (SRM) Bovine muscle 8414 NIST using Instrumental Neutron Activation Analysis (INAA). Three selected trace element such as Fe, Zn, and Se were determined. Accuracy of the elements showed as %recovery and precision as %coefficient of variance (%CV). The result showed that %recovery of Fe, Zn, and Se were in the range between 99.4-107%, 92.7-103%, and 91.9-112%, respectively, whereas %CV were 2.92, 3.70, and 5.37%, respectively. These results showed that INAA method is precise and accurate for trace element determination in biological matrices.

Novel Strategy for Discrimination of Transcription Factor Binding Motifs Employing Mathematical Neural Network

NASA Astrophysics Data System (ADS)

Sugimoto, Asuka; Sumi, Takuya; Kang, Jiyoung; Tateno, Masaru

2017-07-01

Recognition in biological macromolecular systems, such as DNA-protein recognition, is one of the most crucial problems to solve toward understanding the fundamental mechanisms of various biological processes. Since specific base sequences of genome DNA are discriminated by proteins, such as transcription factors (TFs), finding TF binding motifs (TFBMs) in whole genome DNA sequences is currently a central issue in interdisciplinary biophysical and information sciences. In the present study, a novel strategy to create a discriminant function for discrimination of TFBMs by constituting mathematical neural networks (NNs) is proposed, together with a method to determine the boundary of signals (TFBMs) and noise in the NN-score (output) space. This analysis also leads to the mathematical limitation of discrimination in the recognition of features representing TFBMs, in an information geometrical manifold. Thus, the present strategy enables the identification of the whole space of TFBMs, right up to the noise boundary.

Protein-targeted corona phase molecular recognition

PubMed Central

Bisker, Gili; Dong, Juyao; Park, Hoyoung D.; Iverson, Nicole M.; Ahn, Jiyoung; Nelson, Justin T.; Landry, Markita P.; Kruss, Sebastian; Strano, Michael S.

2016-01-01

Corona phase molecular recognition (CoPhMoRe) uses a heteropolymer adsorbed onto and templated by a nanoparticle surface to recognize a specific target analyte. This method has not yet been extended to macromolecular analytes, including proteins. Herein we develop a variant of a CoPhMoRe screening procedure of single-walled carbon nanotubes (SWCNT) and use it against a panel of human blood proteins, revealing a specific corona phase that recognizes fibrinogen with high selectivity. In response to fibrinogen binding, SWCNT fluorescence decreases by >80% at saturation. Sequential binding of the three fibrinogen nodules is suggested by selective fluorescence quenching by isolated sub-domains and validated by the quenching kinetics. The fibrinogen recognition also occurs in serum environment, at the clinically relevant fibrinogen concentrations in the human blood. These results open new avenues for synthetic, non-biological antibody analogues that recognize biological macromolecules, and hold great promise for medical and clinical applications. PMID:26742890

Blood perfusion construction for infrared face recognition based on bio-heat transfer.

PubMed

Xie, Zhihua; Liu, Guodong

2014-01-01

To improve the performance of infrared face recognition for time-lapse data, a new construction of blood perfusion is proposed based on bio-heat transfer. Firstly, by quantifying the blood perfusion based on Pennes equation, the thermal information is converted into blood perfusion rate, which is stable facial biological feature of face image. Then, the separability discriminant criterion in Discrete Cosine Transform (DCT) domain is applied to extract the discriminative features of blood perfusion information. Experimental results demonstrate that the features of blood perfusion are more concentrative and discriminative for recognition than those of thermal information. The infrared face recognition based on the proposed blood perfusion is robust and can achieve better recognition performance compared with other state-of-the-art approaches.

Dynamic nanoplatforms in biosensor and membrane constitutional systems.

PubMed

Mahon, Eugene; Aastrup, Teodor; Barboiu, Mihail

2012-01-01

Molecular recognition in biological systems occurs mainly at interfacial environments such as membrane surfaces, enzyme active sites, or the interior of the DNA double helix. At the cell membrane surface, carbohydrate-protein recognition principles apply to a range of specific non-covalent interactions including immune response, cell proliferation, adhesion and death, cell-cell interaction and communication. Protein-protein recognition meanwhile accounts for signalling processes and ion channel structure. In this chapter we aim to describe such constitutional dynamic interfaces for biosensing and membrane transport applications. Constitutionally adaptive interfaces may mimic the recognition capabilities intrinsic to natural recognition processes. We present some recent examples of 2D and 3D constructed sensors and membranes of this type and describe their sensing and transport capabilities.

Infrared differential-absorption Mueller matrix spectroscopy and neural network-based data fusion for biological aerosol standoff detection.

PubMed

Carrieri, Arthur H; Copper, Jack; Owens, David J; Roese, Erik S; Bottiger, Jerold R; Everly, Robert D; Hung, Kevin C

2010-01-20

An active spectrophotopolarimeter sensor and support system were developed for a military/civilian defense feasibility study concerning the identification and standoff detection of biological aerosols. Plumes of warfare agent surrogates gamma-irradiated Bacillus subtilis and chicken egg white albumen (analytes), Arizona road dust (terrestrial interferent), water mist (atmospheric interferent), and talcum powders (experiment controls) were dispersed inside windowless chambers and interrogated by multiple CO(2) laser beams spanning 9.1-12.0 microm wavelengths (lambda). Molecular vibration and vibration-rotation activities by the subject analyte are fundamentally strong within this "fingerprint" middle infrared spectral region. Distinct polarization-modulations of incident irradiance and backscatter radiance of tuned beams generate the Mueller matrix (M) of subject aerosol. Strings of all 15 normalized elements {M(ij)(lambda)/M(11)(lambda)}, which completely describe physical and geometric attributes of the aerosol particles, are input fields for training hybrid Kohonen self-organizing map feed-forward artificial neural networks (ANNs). The properly trained and validated ANN model performs pattern recognition and type-classification tasks via internal mappings. A typical ANN that mathematically clusters analyte, interferent, and control aerosols with nil overlap of species is illustrated, including sensitivity analysis of performance.

tRNA acceptor-stem and anticodon bases embed separate features of amino acid chemistry

PubMed Central

Carter, Charles W.; Wolfenden, Richard

2016-01-01

abstract The universal genetic code is a translation table by which nucleic acid sequences can be interpreted as polypeptides with a wide range of biological functions. That information is used by aminoacyl-tRNA synthetases to translate the code. Moreover, amino acid properties dictate protein folding. We recently reported that digital correlation techniques could identify patterns in tRNA identity elements that govern recognition by synthetases. Our analysis, and the functionality of truncated synthetases that cannot recognize the tRNA anticodon, support the conclusion that the tRNA acceptor stem houses an independent code for the same 20 amino acids that likely functioned earlier in the emergence of genetics. The acceptor-stem code, related to amino acid size, is distinct from a code in the anticodon that is related to amino acid polarity. Details of the acceptor-stem code suggest that it was useful in preserving key properties of stereochemically-encoded peptides that had developed the capacity to interact catalytically with RNA. The quantitative embedding of the chemical properties of amino acids into tRNA bases has implications for the origins of molecular biology. PMID:26595350

Bioanalytical and chemical sensors using living taste, olfactory, and neural cells and tissues: a short review.

PubMed

Wu, Chunsheng; Lillehoj, Peter B; Wang, Ping

2015-11-07

Biosensors utilizing living tissues and cells have recently gained significant attention as functional devices for chemical sensing and biochemical analysis. These devices integrate biological components (i.e. single cells, cell networks, tissues) with micro-electro-mechanical systems (MEMS)-based sensors and transducers. Various types of cells and tissues derived from natural and bioengineered sources have been used as recognition and sensing elements, which are generally characterized by high sensitivity and specificity. This review summarizes the state of the art in tissue- and cell-based biosensing platforms with an emphasis on those using taste, olfactory, and neural cells and tissues. Many of these devices employ unique integration strategies and sensing schemes based on sensitive transducers including microelectrode arrays (MEAs), field effect transistors (FETs), and light-addressable potentiometric sensors (LAPSs). Several groups have coupled these hybrid biosensors with microfluidics which offers added benefits of small sample volumes and enhanced automation. While this technology is currently limited to lab settings due to the limited stability of living biological components, further research to enhance their robustness will enable these devices to be employed in field and clinical settings.

Stabilization of RNA hairpins using non-nucleotide linkers and circularization.

PubMed

Kiliszek, Agnieszka; Blaszczyk, Leszek; Kierzek, Ryszard; Rypniewski, Wojciech

2017-06-02

An RNA hairpin is an essential structural element of RNA. Hairpins play crucial roles in gene expression and intermolecular recognition but are also involved in the pathogenesis of some congenital diseases. Structural studies of the hairpin motifs are impeded by their thermodynamic instability, as they tend to unfold to form duplexes, especially at high concentrations required for crystallography or nuclear magnetic resonance spectroscopy. We have elaborated techniques to stabilize the RNA hairpins by linking the free ends of the RNA strand at the base of the hairpin stem. One method involves stilbene diether or hexaethylene glycol linkers and circularization by T4 RNA ligase. Another method uses click chemistry to stitch the RNA ends with a triazole linker. Both techniques are efficient and easy to perform. They should be useful in making stable, biologically relevant RNA constructs for structural studies. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

The graph neural network model.

PubMed

Scarselli, Franco; Gori, Marco; Tsoi, Ah Chung; Hagenbuchner, Markus; Monfardini, Gabriele

2009-01-01

Many underlying relationships among data in several areas of science and engineering, e.g., computer vision, molecular chemistry, molecular biology, pattern recognition, and data mining, can be represented in terms of graphs. In this paper, we propose a new neural network model, called graph neural network (GNN) model, that extends existing neural network methods for processing the data represented in graph domains. This GNN model, which can directly process most of the practically useful types of graphs, e.g., acyclic, cyclic, directed, and undirected, implements a function tau(G,n) is an element of IR(m) that maps a graph G and one of its nodes n into an m-dimensional Euclidean space. A supervised learning algorithm is derived to estimate the parameters of the proposed GNN model. The computational cost of the proposed algorithm is also considered. Some experimental results are shown to validate the proposed learning algorithm, and to demonstrate its generalization capabilities.

Biosensing Technologies for Mycobacterium tuberculosis Detection: Status and New Developments

PubMed Central

Zhou, Lixia; He, Xiaoxiao; He, Dinggeng; Wang, Kemin; Qin, Dilan

2011-01-01

Biosensing technologies promise to improve Mycobacterium tuberculosis (M. tuberculosis) detection and management in clinical diagnosis, food analysis, bioprocess, and environmental monitoring. A variety of portable, rapid, and sensitive biosensors with immediate “on-the-spot” interpretation have been developed for M. tuberculosis detection based on different biological elements recognition systems and basic signal transducer principles. Here, we present a synopsis of current developments of biosensing technologies for M. tuberculosis detection, which are classified on the basis of basic signal transducer principles, including piezoelectric quartz crystal biosensors, electrochemical biosensors, and magnetoelastic biosensors. Special attention is paid to the methods for improving the framework and analytical parameters of the biosensors, including sensitivity and analysis time as well as automation of analysis procedures. Challenges and perspectives of biosensing technologies development for M. tuberculosis detection are also discussed in the final part of this paper. PMID:21437177

A Protein Nanopore-Based Approach for Bacteria Sensing

NASA Astrophysics Data System (ADS)

Apetrei, Aurelia; Ciuca, Andrei; Lee, Jong-kook; Seo, Chang Ho; Park, Yoonkyung; Luchian, Tudor

2016-11-01

We present herein a first proof of concept demonstrating the potential of a protein nanopore-based technique for real-time detection of selected Gram-negative bacteria ( Pseudomonas aeruginosa or Escherichia coli) at a concentration of 1.2 × 108 cfu/mL. The anionic charge on the bacterial outer membrane promotes the electrophoretically driven migration of bacteria towards a single α-hemolysin nanopore isolated in a lipid bilayer, clamped at a negative electric potential, and followed by capture at the nanopore's mouth, which we found to be described according to the classical Kramers' theory. By using a specific antimicrobial peptide as a putative molecular biorecognition element for the bacteria used herein, we suggest that the detection system can combine the natural sensitivity of the nanopore-based sensing techniques with selective biological recognition, in aqueous samples, and highlight the feasibility of the nanopore-based platform to provide portable, sensitive analysis and monitoring of bacterial pathogens.

Micropatterned arrays of porous silicon: toward sensory biointerfaces.

PubMed

Flavel, Benjamin S; Sweetman, Martin J; Shearer, Cameron J; Shapter, Joseph G; Voelcker, Nicolas H

2011-07-01

We describe the fabrication of arrays of porous silicon spots by means of photolithography where a positive photoresist serves as a mask during the anodization process. In particular, photoluminescent arrays and porous silicon spots suitable for further chemical modification and the attachment of human cells were created. The produced arrays of porous silicon were chemically modified by means of a thermal hydrosilylation reaction that facilitated immobilization of the fluorescent dye lissamine, and alternatively, the cell adhesion peptide arginine-glycine-aspartic acid-serine. The latter modification enabled the selective attachment of human lens epithelial cells on the peptide functionalized regions of the patterns. This type of surface patterning, using etched porous silicon arrays functionalized with biological recognition elements, presents a new format of interfacing porous silicon with mammalian cells. Porous silicon arrays with photoluminescent properties produced by this patterning strategy also have potential applications as platforms for in situ monitoring of cell behavior.

Fluorine and Fluorinated Motifs in the Design and Application of Bioisosteres for Drug Design.

PubMed

Meanwell, Nicholas A

2018-02-05

The electronic properties and relatively small size of fluorine endow it with considerable versatility as a bioisostere and it has found application as a substitute for lone pairs of electrons, the hydrogen atom, and the methyl group while also acting as a functional mimetic of the carbonyl, carbinol, and nitrile moieties. In this context, fluorine substitution can influence the potency, conformation, metabolism, membrane permeability, and P-gp recognition of a molecule and temper inhibition of the hERG channel by basic amines. However, as a consequence of the unique properties of fluorine, it features prominently in the design of higher order structural metaphors that are more esoteric in their conception and which reflect a more sophisticated molecular construction that broadens biological mimesis. In this Perspective, applications of fluorine in the construction of bioisosteric elements designed to enhance the in vitro and in vivo properties of a molecule are summarized.

75 FR 55617 - Advisory Committee for Biological Sciences; Notice of Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-13

...-- Innovation Experiments; Research Resources. PM: Presentation and Discussion--Science, Arts and Humanities Symposium; COV Reports; COV Updates; New Ideas; Recognition of Departing BIO AC Members. October 7, 2010... NATIONAL SCIENCE FOUNDATION Advisory Committee for Biological Sciences; Notice of Meeting In...

Detection and recognition of targets by using signal polarization properties

NASA Astrophysics Data System (ADS)

Ponomaryov, Volodymyr I.; Peralta-Fabi, Ricardo; Popov, Anatoly V.; Babakov, Mikhail F.

1999-08-01

The quality of radar target recognition can be enhanced by exploiting its polarization signatures. A specialized X-band polarimetric radar was used for target recognition in experimental investigations. The following polarization characteristics connected to the object geometrical properties were investigated: the amplitudes of the polarization matrix elements; an anisotropy coefficient; depolarization coefficient; asymmetry coefficient; the energy of a backscattering signal; object shape factor. A large quantity of polarimetric radar data was measured and processed to form a database of different object and different weather conditions. The histograms of polarization signatures were approximated by a Nakagami distribution, then used for real- time target recognition. The Neyman-Pearson criterion was used for the target detection, and the criterion of the maximum of a posterior probability was used for recognition problem. Some results of experimental verification of pattern recognition and detection of objects with different electrophysical and geometrical characteristics urban in clutter are presented in this paper.

Movement Contributes to Infants' Recognition of the Human Form

ERIC Educational Resources Information Center

Christie, Tamara; Slaughter, Virginia

2010-01-01

Three experiments demonstrate that biological movement facilitates young infants' recognition of the whole human form. A body discrimination task was used in which 6-, 9-, and 12-month-old infants were habituated to typical human bodies and then shown scrambled human bodies at the test. Recovery of interest to the scrambled bodies was observed in…

An Approach to Object Recognition: Aligning Pictorial Descriptions.

DTIC Science & Technology

1986-12-01

PERFORMING 0RGANIZATION NAMIE ANDORS IS551. PROGRAM ELEMENT. PROJECT. TASK Artificial Inteligence Laboratory AREKA A WORK UNIT NUMBERS ( 545 Technology... ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 931 December, 1986 AN APPROACH TO OBJECT RECOGNITION: ALIGNING PICTORIAL DESCRIPTIONS Shimon Ullman...within the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. Support for the A.I. Laboratory’s artificial intelligence

Engineering of an Extremely Thermostable Alpha/Beta Barrel Scaffold to Serve as a High Affinity Molecular Recognition Element for Use in Sensor Applications

DTIC Science & Technology

2015-12-23

papers submitted or published that acknowledge ARO support from the start of the project to the date of this printing. List the papers, including...1. Koide, S. & Sidhu, S.S. The importance of being tyrosine: lessons in molecular recognition from minimalist synthetic binding proteins. ACS

Bio-Mimetic Sensors Based on Molecularly Imprinted Membranes

PubMed Central

Algieri, Catia; Drioli, Enrico; Guzzo, Laura; Donato, Laura

2014-01-01

An important challenge for scientific research is the production of artificial systems able to mimic the recognition mechanisms occurring at the molecular level in living systems. A valid contribution in this direction resulted from the development of molecular imprinting. By means of this technology, selective molecular recognition sites are introduced in a polymer, thus conferring it bio-mimetic properties. The potential applications of these systems include affinity separations, medical diagnostics, drug delivery, catalysis, etc. Recently, bio-sensing systems using molecularly imprinted membranes, a special form of imprinted polymers, have received the attention of scientists in various fields. In these systems imprinted membranes are used as bio-mimetic recognition elements which are integrated with a transducer component. The direct and rapid determination of an interaction between the recognition element and the target analyte (template) was an encouraging factor for the development of such systems as alternatives to traditional bio-assay methods. Due to their high stability, sensitivity and specificity, bio-mimetic sensors-based membranes are used for environmental, food, and clinical uses. This review deals with the development of molecularly imprinted polymers and their different preparation methods. Referring to the last decades, the application of these membranes as bio-mimetic sensor devices will be also reported. PMID:25196110

A survey of visual preprocessing and shape representation techniques

NASA Technical Reports Server (NTRS)

Olshausen, Bruno A.

1988-01-01

Many recent theories and methods proposed for visual preprocessing and shape representation are summarized. The survey brings together research from the fields of biology, psychology, computer science, electrical engineering, and most recently, neural networks. It was motivated by the need to preprocess images for a sparse distributed memory (SDM), but the techniques presented may also prove useful for applying other associative memories to visual pattern recognition. The material of this survey is divided into three sections: an overview of biological visual processing; methods of preprocessing (extracting parts of shape, texture, motion, and depth); and shape representation and recognition (form invariance, primitives and structural descriptions, and theories of attention).

Face Recognition in Humans and Machines

NASA Astrophysics Data System (ADS)

O'Toole, Alice; Tistarelli, Massimo

The study of human face recognition by psychologists and neuroscientists has run parallel to the development of automatic face recognition technologies by computer scientists and engineers. In both cases, there are analogous steps of data acquisition, image processing, and the formation of representations that can support the complex and diverse tasks we accomplish with faces. These processes can be understood and compared in the context of their neural and computational implementations. In this chapter, we present the essential elements of face recognition by humans and machines, taking a perspective that spans psychological, neural, and computational approaches. From the human side, we overview the methods and techniques used in the neurobiology of face recognition, the underlying neural architecture of the system, the role of visual attention, and the nature of the representations that emerges. From the computational side, we discuss face recognition technologies and the strategies they use to overcome challenges to robust operation over viewing parameters. Finally, we conclude the chapter with a look at some recent studies that compare human and machine performances at face recognition.

Analytical applications of aptamers

NASA Astrophysics Data System (ADS)

Tombelli, S.; Minunni, M.; Mascini, M.

2007-05-01

Aptamers are single stranded DNA or RNA ligands which can be selected for different targets starting from a library of molecules containing randomly created sequences. Aptamers have been selected to bind very different targets, from proteins to small organic dyes. Aptamers are proposed as alternatives to antibodies as biorecognition elements in analytical devices with ever increasing frequency. This in order to satisfy the demand for quick, cheap, simple and highly reproducible analytical devices, especially for protein detection in the medical field or for the detection of smaller molecules in environmental and food analysis. In our recent experience, DNA and RNA aptamers, specific for three different proteins (Tat, IgE and thrombin), have been exploited as bio-recognition elements to develop specific biosensors (aptasensors). These recognition elements have been coupled to piezoelectric quartz crystals and surface plasmon resonance (SPR) devices as transducers where the aptamers have been immobilized on the gold surface of the crystals electrodes or on SPR chips, respectively.

Versatile protein recognition by the encoded display of multiple chemical elements on a constant macrocyclic scaffold

NASA Astrophysics Data System (ADS)

Li, Yizhou; De Luca, Roberto; Cazzamalli, Samuele; Pretto, Francesca; Bajic, Davor; Scheuermann, Jörg; Neri, Dario

2018-03-01

In nature, specific antibodies can be generated as a result of an adaptive selection and expansion of lymphocytes with suitable protein binding properties. We attempted to mimic antibody-antigen recognition by displaying multiple chemical diversity elements on a defined macrocyclic scaffold. Encoding of the displayed combinations was achieved using distinctive DNA tags, resulting in a library size of 35,393,112. Specific binders could be isolated against a variety of proteins, including carbonic anhydrase IX, horseradish peroxidase, tankyrase 1, human serum albumin, alpha-1 acid glycoprotein, calmodulin, prostate-specific antigen and tumour necrosis factor. Similar to antibodies, the encoded display of multiple chemical elements on a constant scaffold enabled practical applications, such as fluorescence microscopy procedures or the selective in vivo delivery of payloads to tumours. Furthermore, the versatile structure of the scaffold facilitated the generation of protein-specific chemical probes, as illustrated by photo-crosslinking.

The Value of Humans in the Biological Exploration of Space

NASA Astrophysics Data System (ADS)

Cockell, C. S.

2004-06-01

Regardless of the discovery of life on Mars, or of "no apparent life" on Mars, the questions that follow will provide a rich future for biological exploration. Extraordinary pattern recognition skills, decadal assimilation of data and experience, and rapid sample acquisition are just three of the characteristics that make humans the best means we have to explore the biological potential of Mars and other planetary surfaces. I make the case that instead of seeing robots as in conflict, or even in support, of human exploration activity, from the point of view of scientific data gathering and analysis, we should view humans as the most powerful robots we have, thus removing the separation that dogs discussions on the exploration of space. The narrow environmental requirements of humans, although imposing constraints on the life support systems required, is more than compensated for by their capabilities in biological exploration. I support this view with an example of the "Christmas present effect," a simple demonstration of human data and pattern recognition capabilities.

Imaging and Force Recognition of Single Molecular Behaviors Using Atomic Force Microscopy

PubMed Central

Li, Mi; Dang, Dan; Liu, Lianqing; Xi, Ning; Wang, Yuechao

2017-01-01

The advent of atomic force microscopy (AFM) has provided a powerful tool for investigating the behaviors of single native biological molecules under physiological conditions. AFM can not only image the conformational changes of single biological molecules at work with sub-nanometer resolution, but also sense the specific interactions of individual molecular pair with piconewton force sensitivity. In the past decade, the performance of AFM has been greatly improved, which makes it widely used in biology to address diverse biomedical issues. Characterizing the behaviors of single molecules by AFM provides considerable novel insights into the underlying mechanisms guiding life activities, contributing much to cell and molecular biology. In this article, we review the recent developments of AFM studies in single-molecule assay. The related techniques involved in AFM single-molecule assay were firstly presented, and then the progress in several aspects (including molecular imaging, molecular mechanics, molecular recognition, and molecular activities on cell surface) was summarized. The challenges and future directions were also discussed. PMID:28117741

Visual object recognition for automatic micropropagation of plants

NASA Astrophysics Data System (ADS)

Brendel, Thorsten; Schwanke, Joerg; Jensch, Peter F.

1994-11-01

Micropropagation of plants is done by cutting juvenile plants and placing them into special container-boxes with nutrient-solution where the pieces can grow up and be cut again several times. To produce high amounts of biomass it is necessary to do plant micropropagation by a robotic system. In this paper we describe parts of the vision system that recognizes plants and their particular cutting points. Therefore, it is necessary to extract elements of the plants and relations between these elements (for example root, stem, leaf). Different species vary in their morphological appearance, variation is also immanent in plants of the same species. Therefore, we introduce several morphological classes of plants from that we expect same recognition methods.

Ease of identifying words degraded by visual noise.

PubMed

Barber, P; de la Mahotière, C

1982-08-01

A technique is described for investigating word recognition involving the superimposition of 'noise' on the visual target word. For this task a word is printed in the form of letters made up of separate elements; noise consists of additional elements which serve to reduce the ease whereby the words may be recognized, and a threshold-like measure can be obtained in terms of the amount of noise. A word frequency effect was obtained for the noise task, and for words presented tachistoscopically but in conventional typography. For the tachistoscope task, however, the frequency effect depended on the method of presentation. A second study showed no effect of inspection interval on performance on the noise task. A word-frequency effect was also found in a third experiment with tachistoscopic exposure of the noise task stimuli in undegraded form. The question of whether common processes are drawn on by tasks entailing different ways of varying ease of recognition is addressed, and the suitability of different tasks for word recognition research is discussed.

Identification of the RNA recognition element of the RBPMS family of RNA-binding proteins and their transcriptome-wide mRNA targets

PubMed Central

Farazi, Thalia A.; Leonhardt, Carl S.; Mukherjee, Neelanjan; Mihailovic, Aleksandra; Li, Song; Max, Klaas E.A.; Meyer, Cindy; Yamaji, Masashi; Cekan, Pavol; Jacobs, Nicholas C.; Gerstberger, Stefanie; Bognanni, Claudia; Larsson, Erik; Ohler, Uwe; Tuschl, Thomas

2014-01-01

Recent studies implicated the RNA-binding protein with multiple splicing (RBPMS) family of proteins in oocyte, retinal ganglion cell, heart, and gastrointestinal smooth muscle development. These RNA-binding proteins contain a single RNA recognition motif (RRM), and their targets and molecular function have not yet been identified. We defined transcriptome-wide RNA targets using photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation (PAR-CLIP) in HEK293 cells, revealing exonic mature and intronic pre-mRNA binding sites, in agreement with the nuclear and cytoplasmic localization of the proteins. Computational and biochemical approaches defined the RNA recognition element (RRE) as a tandem CAC trinucleotide motif separated by a variable spacer region. Similar to other mRNA-binding proteins, RBPMS family of proteins relocalized to cytoplasmic stress granules under oxidative stress conditions suggestive of a support function for mRNA localization in large and/or multinucleated cells where it is preferentially expressed. PMID:24860013

Bioactivation of particles

DOEpatents

Pinaud, Fabien [Berkeley, CA; King, David [San Francisco, CA; Weiss, Shimon [Los Angeles, CA

2011-08-16

Particles are bioactivated by attaching bioactivation peptides to the particle surface. The bioactivation peptides are peptide-based compounds that impart one or more biologically important functions to the particles. Each bioactivation peptide includes a molecular or surface recognition part that binds with the surface of the particle and one or more functional parts. The surface recognition part includes an amino-end and a carboxy-end and is composed of one or more hydrophobic spacers and one or more binding clusters. The functional part(s) is attached to the surface recognition part at the amino-end and/or said carboxy-end.

Biology Education in the United States: The Unfinished Century.

ERIC Educational Resources Information Center

Bybee, Rodger W.

2002-01-01

Adresses five themes basic to biology education: (1) increased recognition of advances in the science of learning; (2) implementation of scientific ideas and technological innovations; (3) incorporation of science- and technology-related issues; (4) elaboration of global perspectives; and (5) professional community and civil discourse. (MM)

[Roles of sialic acids in sperm maturation and capacitation and sperm-egg recognition].

PubMed

Feng, Ying; Wang, Lin; Wu, Yi-Lun; Liu, Hong-Hua; Ma, Fang

2016-10-01

Sialic acids are a subset of nine-carbon alpha-keto aldonic acids involved in various biological functions. Sialic acid on the sperm surface is closely related to sperm maturation and capacitation and sperm-egg recognition, which makes sperm negatively charged to avoid accumulation and covers some antigenic determinants there to increase the survival rate of sperm in the female reproductive tract. The loss of sialic acids is an important factor mediating sperm capacitation. Moreover, the sialic acid at the extremity of the protein polymer is involved in signal identification in sperm-egg recognition. Here, we review the current understanding of sialic acids in sperm maturation and capacitation and sperm-egg recognition.

Image processing and recognition for biological images.

PubMed

Uchida, Seiichi

2013-05-01

This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. As the main tasks of image processing, this paper introduces gray-level transformation, binarization, image filtering, image segmentation, visual object tracking, optical flow and image registration. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. This paper overviews its two main modules, that is, feature extraction module and classification module. Throughout the paper, it will be emphasized that bioimage is a very difficult target for even state-of-the-art image processing and pattern recognition techniques due to noises, deformations, etc. This paper is expected to be one tutorial guide to bridge biology and image processing researchers for their further collaboration to tackle such a difficult target. © 2013 The Author Development, Growth & Differentiation © 2013 Japanese Society of Developmental Biologists.

Organization of inorganic nanomaterials via programmable DNA self-assembly and peptide molecular recognition.

PubMed

Carter, Joshua D; LaBean, Thomas H

2011-03-22

An interesting alternative to top-down nanofabrication is to imitate biology, where nanoscale materials frequently integrate organic molecules for self-assembly and molecular recognition with ordered, inorganic minerals to achieve mechanical, sensory, or other advantageous functions. Using biological systems as inspiration, researchers have sought to mimic the nanoscale composite materials produced in nature. Here, we describe a combination of self-assembly, molecular recognition, and templating, relying on an oligonucleotide covalently conjugated to a high-affinity gold-binding peptide. After integration of the peptide-coupled DNA into a self-assembling superstructure, the templated peptides recognize and bind gold nanoparticles. In addition to providing new ways of building functional multinanoparticle systems, this work provides experimental proof that a single peptide molecule is sufficient for immobilization of a nanoparticle. This molecular construction strategy, combining DNA assembly and peptide recognition, can be thought of as programmable, granular, artificial biomineralization. We also describe the important observation that the addition of 1-2% Tween 20 surfactant to the solution during gold particle binding allows the gold nanoparticles to remain soluble within the magnesium-containing DNA assembly buffer under conditions that usually lead to the aggregation and precipitation of the nanoparticles.

Perspective: Watching low-frequency vibrations of water in biomolecular recognition by THz spectroscopy.

PubMed

Xu, Yao; Havenith, Martina

2015-11-07

Terahertz (THz) spectroscopy has turned out to be a powerful tool which is able to shed new light on the role of water in biomolecular processes. The low frequency spectrum of the solvated biomolecule in combination with MD simulations provides deep insights into the collective hydrogen bond dynamics on the sub-ps time scale. The absorption spectrum between 1 THz and 10 THz of solvated biomolecules is sensitive to changes in the fast fluctuations of the water network. Systematic studies on mutants of antifreeze proteins indicate a direct correlation between biological activity and a retardation of the (sub)-ps hydration dynamics at the protein binding site, i.e., a "hydration funnel." Kinetic THz absorption studies probe the temporal changes of THz absorption during a biological process, and give access to the kinetics of the coupled protein-hydration dynamics. When combined with simulations, the observed results can be explained in terms of a two-tier model involving a local binding and a long range influence on the hydration bond dynamics of the water around the binding site that highlights the significance of the changes in the hydration dynamics at recognition site for biomolecular recognition. Water is shown to assist molecular recognition processes.

Perspective: Watching low-frequency vibrations of water in biomolecular recognition by THz spectroscopy

NASA Astrophysics Data System (ADS)

Xu, Yao; Havenith, Martina

2015-11-01

Terahertz (THz) spectroscopy has turned out to be a powerful tool which is able to shed new light on the role of water in biomolecular processes. The low frequency spectrum of the solvated biomolecule in combination with MD simulations provides deep insights into the collective hydrogen bond dynamics on the sub-ps time scale. The absorption spectrum between 1 THz and 10 THz of solvated biomolecules is sensitive to changes in the fast fluctuations of the water network. Systematic studies on mutants of antifreeze proteins indicate a direct correlation between biological activity and a retardation of the (sub)-ps hydration dynamics at the protein binding site, i.e., a "hydration funnel." Kinetic THz absorption studies probe the temporal changes of THz absorption during a biological process, and give access to the kinetics of the coupled protein-hydration dynamics. When combined with simulations, the observed results can be explained in terms of a two-tier model involving a local binding and a long range influence on the hydration bond dynamics of the water around the binding site that highlights the significance of the changes in the hydration dynamics at recognition site for biomolecular recognition. Water is shown to assist molecular recognition processes.

Molecular imprinting at walls of silica nanotubes for TNT recognition.

PubMed

Xie, Chenggen; Liu, Bianhua; Wang, Zhenyang; Gao, Daming; Guan, Guijian; Zhang, Zhongping

2008-01-15

This paper reports the molecular imprinting at the walls of highly uniform silica nanotubes for the recognition of 2,4,6-trinitrotoluene (TNT). It has been demonstrated that TNT templates were efficiently imprinted into the matrix of silica through the strong acid-base pairing interaction between TNT and 3-aminopropyltriethoxysilane (APTS). TNT-imprinted silica nanotubes were synthesized by the gelation reaction between APTS and tetraethylorthosilicate (TEOS), selectively occurring at the porous walls of APTS-modified alumina membranes. The removal of the original TNT templates leaves the imprinted cavities with covalently anchored amine groups at the cavity walls. A high density of recognition sites with molecular selectivity to the TNT analyte was created at the wall of silica nanotubes. Furthermore, most of these recognition sites are situated at the inside and outside surfaces of tubular walls and in the proximity of the two surfaces due to the ultrathin wall thickness of only 15 nm, providing a better site accessibility and lower mass-transfer resistance. Therefore, greater capacity and faster kinetics of uptaking target species were achieved. The silica nanotube reported herein is an ideal form of material for imprinting various organic or biological molecules toward applications in chemical/biological sensors and bioassay.

Group Recommendation in Social Networks

DTIC Science & Technology

2011-01-01

APPROVAL SHEET Title of Thesis: Group recognition in social networks Name of Candidate: Nagapradeep Chinnam Master of...2011 4. TITLE AND SUBTITLE Group recognition in social networks 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d...for public release; distribution unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Recent years have seen an exponential growth in the use of social

Preparation and Characterization of Biofunctionalized Inorganic Substrates.

PubMed

Dugger, Jason W; Webb, Lauren J

2015-09-29

Integrating the function of biological molecules into traditional inorganic materials and substrates couples biologically relevant function to synthetic devices and generates new materials and capabilities by combining biological and inorganic functions. At this so-called "bio/abio interface," basic biological functions such as ligand binding and catalysis can be co-opted to detect analytes with exceptional sensitivity or to generate useful molecules with chiral specificity under entirely benign reaction conditions. Proteins function in dynamic, complex, and crowded environments (the living cell) and are therefore appropriate for integrating into multistep, multiscale, multimaterial devices such as integrated circuits and heterogeneous catalysts. However, the goal of reproducing the highly specific activities of biomolecules in the perturbed chemical and electrostatic environment at an inorganic interface while maintaining their native conformations is challenging to achieve. Moreover, characterizing protein structure and function at a surface is often difficult, particularly if one wishes to compare the activity of the protein to that of the dilute, aqueous solution phase. Our laboratory has developed a general strategy to address this challenge by taking advantage of the structural and chemical properties of alkanethiol self-assembled monolayers (SAMs) on gold surfaces that are functionalized with covalently tethered peptides. These surface-bound peptides then act as the chemical recognition element for a target protein, generating a biomimetic surface in which protein orientation, structure, density, and function are controlled and variable. Herein we discuss current research and future directions related to generating a chemically tunable biofunctionalization strategy that has potential to successfully incorporate the highly specialized functions of proteins onto inorganic substrates.

Elastic Face, An Anatomy-Based Biometrics Beyond Visible Cue

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

Tsap, L V; Zhang, Y; Kundu, S J

2004-03-29

This paper describes a face recognition method that is designed based on the consideration of anatomical and biomechanical characteristics of facial tissues. Elastic strain pattern inferred from face expression can reveal an individual's biometric signature associated with the underlying anatomical structure, and thus has the potential for face recognition. A method based on the continuum mechanics in finite element formulation is employed to compute the strain pattern. Experiments show very promising results. The proposed method is quite different from other face recognition methods and both its advantages and limitations, as well as future research for improvement are discussed.

Thermodynamic Modeling of Donor Splice Site Recognition in pre-mRNA

NASA Astrophysics Data System (ADS)

Aalberts, Daniel P.; Garland, Jeffrey A.

2004-03-01

When eukaryotic genes are edited by the spliceosome, the first step in intron recognition is the binding of a U1 snRNA with the donor (5') splice site. We model this interaction thermodynamically to identify splice sites. Applied to a set of 65 annotated genes, our Finding with Binding method achieves a significant separation between real and false sites. Analyzing binding patterns allows us to discard a large number of decoy sites. Our results improve statistics-based methods for donor site recognition, demonstrating the promise of physical modeling to find functional elements in the genome.

Thermodynamic modeling of donor splice site recognition in pre-mRNA

NASA Astrophysics Data System (ADS)

Garland, Jeffrey A.; Aalberts, Daniel P.

2004-04-01

When eukaryotic genes are edited by the spliceosome, the first step in intron recognition is the binding of a U1 small nuclear RNA with the donor ( 5' ) splice site. We model this interaction thermodynamically to identify splice sites. Applied to a set of 65 annotated genes, our “finding with binding” method achieves a significant separation between real and false sites. Analyzing binding patterns allows us to discard a large number of decoy sites. Our results improve statistics-based methods for donor site recognition, demonstrating the promise of physical modeling to find functional elements in the genome.

Understanding and Controlling Living/Inorganic Interfaces to Enable Reconfigurable Switchable Materials

DTIC Science & Technology

2018-03-01

of environmental conditions and surface treatment on binding affinity. 15. SUBJECT TERMS bacterial adhesion, genetically engineered proteins for...mannose binding both experimentally and in molecular dynamics simulation ............................................................ 6 Fig. 3 COMSOL...Research Laboratory (ARL) strengths (e.g., molecular biology/synthetic biology, biomolecular recognition, materials characterization and polymer science

Student Engagement with Feedback

ERIC Educational Resources Information Center

Scott, Jon; Shields, Cathy; Gardner, James; Hancock, Alysoun; Nutt, Alex

2011-01-01

This report considers Biological Sciences students' perceptions of feedback, compared with those of the University as a whole, this includes what forms of feedback were considered most useful and how feedback used. Compared with data from previous studies, Biological Sciences students gave much greater recognition to oral feedback, placing it on a…

Water-Soluble Nanoparticle Receptors Supramolecularly Coded for Acidic Peptides.

PubMed

Fa, Shixin; Zhao, Yan

2018-01-02

Sequence-specific recognition of peptides is of enormous importance to many chemical and biological applications, but has been difficult to achieve due to the minute differences in the side chains of amino acids. Acidic peptides are known to play important roles in cell growth and gene expression. In this work, we report molecularly imprinted micelles coded with molecular recognition information for the acidic and hydrophobic side chains of acidic peptides. The imprinted receptors could distinguish acidic amino acids from other polar and nonpolar amino acids, with dissociation constants of tens of nanomolar for biologically active peptides containing up to 18 amino acids. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Integrating and evaluating sex and gender in health research.

PubMed

Day, Suzanne; Mason, Robin; Lagosky, Stephanie; Rochon, Paula A

2016-10-10

Both sex (biological factors) and gender (socio-cultural factors) shape health. To produce the best possible health research evidence, it is essential to integrate sex and gender considerations throughout the research process. Despite growing recognition of the importance of these factors, progress towards sex and gender integration as standard practice has been both slow and uneven in health research. In this commentary, we examine the challenges of integrating sex and gender from the research perspective, as well as strategies that can be used by researchers, funders and journal editors to address these challenges. Barriers to the integration of sex and gender in health research include problems with inconsistent terminology, difficulties in applying the concepts of sex and gender, failure to recognise the impact of sex and gender, and challenges with data collection and datasets. We analyse these barriers as strategic points of intervention for improving the integration of sex and gender at all stages of the research process. To assess the relative success of these strategies in any given study, researchers, funders and journal editors would benefit from a tool to evaluate the quality of sex and gender integration in order to establish benchmarks in research excellence. These assessment tools are needed now amidst growing institutional recognition that both sex and gender are necessary elements for advancing the quality and utility of health research evidence.

Center for Neural Engineering: applications of pulse-coupled neural networks

NASA Astrophysics Data System (ADS)

Malkani, Mohan; Bodruzzaman, Mohammad; Johnson, John L.; Davis, Joel

1999-03-01

Pulsed-Coupled Neural Network (PCNN) is an oscillatory model neural network where grouping of cells and grouping among the groups that form the output time series (number of cells that fires in each input presentation also called `icon'). This is based on the synchronicity of oscillations. Recent work by Johnson and others demonstrated the functional capabilities of networks containing such elements for invariant feature extraction using intensity maps. PCNN thus presents itself as a more biologically plausible model with solid functional potential. This paper will present the summary of several projects and their results where we successfully applied PCNN. In project one, the PCNN was applied for object recognition and classification through a robotic vision system. The features (icons) generated by the PCNN were then fed into a feedforward neural network for classification. In project two, we developed techniques for sensory data fusion. The PCNN algorithm was implemented and tested on a B14 mobile robot. The PCNN-based features were extracted from the images taken from the robot vision system and used in conjunction with the map generated by data fusion of the sonar and wheel encoder data for the navigation of the mobile robot. In our third project, we applied the PCNN for speaker recognition. The spectrogram image of speech signals are fed into the PCNN to produce invariant feature icons which are then fed into a feedforward neural network for speaker identification.

Trace Element Analysis of Biological Samples.

ERIC Educational Resources Information Center

Veillon, Claude

1986-01-01

Reviews background of atomic absorption spectrometry techniques. Discusses problems encountered and precautions to be taken in determining trace elements in the parts-per-billion concentration range and below. Concentrates on determining chromium in biological samples by graphite furnace atomic absorption. Considers other elements, matrices, and…

Object recognition with hierarchical discriminant saliency networks.

PubMed

Han, Sunhyoung; Vasconcelos, Nuno

2014-01-01

The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and computer vision literatures. This demonstrates benefits for all the functional enhancements of the HDSN, the class tuning inherent to discriminant saliency, and saliency layers based on templates of increasing target selectivity and invariance. Altogether, these experiments suggest that there are non-trivial benefits in integrating attention and recognition.

Anion Recognition in Water: Recent Advances from a Supramolecular and Macromolecular Perspective

PubMed Central

Langton, Matthew J.

2015-01-01

Abstract The recognition of anions in water remains a key challenge in modern supramolecular chemistry, and is essential if proposed applications in biological, medical, and environmental arenas that typically require aqueous conditions are to be achieved. However, synthetic anion receptors that operate in water have, in general, been the exception rather than the norm to date. Nevertheless, a significant step change towards routinely conducting anion recognition in water has been achieved in the past few years, and this Review highlights these approaches, with particular focus on controlling and using the hydrophobic effect, as well as more exotic interactions such as C−H hydrogen bonding and halogen bonding. We also look beyond the field of small‐molecule recognition into the macromolecular domain, covering recent advances in anion recognition based on biomolecules, polymers, and nanoparticles. PMID:26612067

Neuroanatomical substrates involved in unrelated false facial recognition.

PubMed

Ronzon-Gonzalez, Eliane; Hernandez-Castillo, Carlos R; Pasaye, Erick H; Vaca-Palomares, Israel; Fernandez-Ruiz, Juan

2017-11-22

Identifying faces is a process central for social interaction and a relevant factor in eyewitness theory. False recognition is a critical mistake during an eyewitness's identification scenario because it can lead to a wrongful conviction. Previous studies have described neural areas related to false facial recognition using the standard Deese/Roediger-McDermott (DRM) paradigm, triggering related false recognition. Nonetheless, misidentification of faces without trying to elicit false memories (unrelated false recognition) in a police lineup could involve different cognitive processes, and distinct neural areas. To delve into the neural circuitry of unrelated false recognition, we evaluated the memory and response confidence of participants while watching faces photographs in an fMRI task. Functional activations of unrelated false recognition were identified by contrasting the activation on this condition vs. the activations related to recognition (hits) and correct rejections. The results identified the right precentral and cingulate gyri as areas with distinctive activations during false recognition events suggesting a conflict resulting in a dysfunction during memory retrieval. High confidence suggested that about 50% of misidentifications may be related to an unconscious process. These findings add to our understanding of the construction of facial memories and its biological basis, and the fallibility of the eyewitness testimony.

A biologically inspired neural network model to transformation invariant object recognition

NASA Astrophysics Data System (ADS)

Iftekharuddin, Khan M.; Li, Yaqin; Siddiqui, Faraz

2007-09-01

Transformation invariant image recognition has been an active research area due to its widespread applications in a variety of fields such as military operations, robotics, medical practices, geographic scene analysis, and many others. The primary goal for this research is detection of objects in the presence of image transformations such as changes in resolution, rotation, translation, scale and occlusion. We investigate a biologically-inspired neural network (NN) model for such transformation-invariant object recognition. In a classical training-testing setup for NN, the performance is largely dependent on the range of transformation or orientation involved in training. However, an even more serious dilemma is that there may not be enough training data available for successful learning or even no training data at all. To alleviate this problem, a biologically inspired reinforcement learning (RL) approach is proposed. In this paper, the RL approach is explored for object recognition with different types of transformations such as changes in scale, size, resolution and rotation. The RL is implemented in an adaptive critic design (ACD) framework, which approximates the neuro-dynamic programming of an action network and a critic network, respectively. Two ACD algorithms such as Heuristic Dynamic Programming (HDP) and Dual Heuristic dynamic Programming (DHP) are investigated to obtain transformation invariant object recognition. The two learning algorithms are evaluated statistically using simulated transformations in images as well as with a large-scale UMIST face database with pose variations. In the face database authentication case, the 90° out-of-plane rotation of faces from 20 different subjects in the UMIST database is used. Our simulations show promising results for both designs for transformation-invariant object recognition and authentication of faces. Comparing the two algorithms, DHP outperforms HDP in learning capability, as DHP takes fewer steps to perform a successful recognition task in general. Further, the residual critic error in DHP is generally smaller than that of HDP, and DHP achieves a 100% success rate more frequently than HDP for individual objects/subjects. On the other hand, HDP is more robust than the DHP as far as success rate across the database is concerned when applied in a stochastic and uncertain environment, and the computational time involved in DHP is more.

Isolation of a peptide from Ph.D.-C7C phage display library for detection of Cry1Ab.

PubMed

Wang, Yun; Wang, Qian; Wu, Ai-Hua; Hao, Zhen-Ping; Liu, Xian-Jin

2017-12-15

Traditional ELISA methods of using animal immunity yield antibodies for detection Cry toxin. Not only is this incredibly harmful to the animals, but is also time-intensive. Here we developed a simple method to yield the recognition element. Using a critical selection strategy and immunoassay we confirmed a clone from the Ph.D-C7C phage library, which has displayed the most interesting Cry1Ab-binding characteristics examined in this study (Fig. 1). The current study indicates that isolating peptide is an alternative method for the preparation of a recognition element, and that the developed assay is a potentially useful tool for detecting Cry1Ab. Copyright © 2017. Published by Elsevier Inc.

Demonstration of Removal, Separation, and Recovery of Heavy Metals from Industrial Wastestreams Using Molecular Recognition Technology (MRT)

DTIC Science & Technology

2002-11-01

Treatment Plant”, TM-2123-ENV, April 1995. 3. Ford, K.H., 1996, “ Heavy Metal Adsorption/ Biosorption Studies for Zero Discharge Industrial Wastewater...SEPARATION, AND RECOVERY OF HEAVY METALS FROM INDUSTRIAL WASTESTREAMS USING MOLECULAR RECOGNITION TECHNOLOGY (MRT) Final Report by Dr. Katherine...GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER DEMONSTRATION OF REMOVAL, SEPARATION, AND RECOVERY OF HEAVY METALS FROM INDUSTRIAL WASTEWATERS USING

DYNAMIC PATTERN RECOGNITION BY MEANS OF THRESHOLD NETS,

DTIC Science & Technology

A method is expounded for the recognition of visual patterns. A circuit diagram of a device is described which is based on a multilayer threshold ...structure synthesized in accordance with the proposed method. Coded signals received each time an image is displayed are transmitted to the threshold ...circuit which distinguishes the signs, and from there to the layers of threshold resolving elements. The image at each layer is made to correspond

Remote detection and recognition of bio-aerosols by laser-induced fluorescense lidar: practical implementation and field tests

NASA Astrophysics Data System (ADS)

Boreysho, Anatoly; Savin, Andrey; Morozov, Alexey; Konyaev, Maxim; Konovalov, Konstantin

2007-06-01

Recognition of aerosol clouds material at some significant distance is now a key requirement for the wide range of applications. The elastic backscatter lidar have demonstrated high capabilities in aerosol remote detection, cloud real-time mapping at very long distances for low-concentration natural aerosols as well as artificial ones [1]. However, recognition ability is required to make them more relevant. Laser-induced fluorescence (LIF) looks very promising with respect to the recognition problem. New approach based on mobile lidar complex [2] equipped by spectrally-and range-resolved LIF-sensor is described as well as some results of field tests. The LIF-sensor consists of four-harmonics Nd:YAG laser equipped by an output expander to provide final beam divergence <1 mrad, 500-mm aspheric Cassegrain-type multi-wavelength receiving telescope, set of single-element receivers for measurement of the elastic backscatter radiation, and multi-element receiver with monochromator for spectrally-resolved LIF measurements. The system is equipped by 2-axis scanning mirror and variable-FOV video-camera collimated with the lidar scanning direction. The LIF-lidar is mounted on a truck-based platform (20-feet container) as a part of multi-purpose mobile lidar complex and adjusted for field conditions.

Klein bottle logophysics: a unified principle for non-linear systems, cosmology, geophysics, biology, biomechanics and perception

NASA Astrophysics Data System (ADS)

Lucio Rapoport, Diego

2013-04-01

We present a unified principle for science that surmounts dualism, in terms of torsion fields and the non-orientable surfaces, notably the Klein Bottle and its logic, the Möbius strip and the projective plane. We apply it to the complex numbers and cosmology, to non-linear systems integrating the issue of hyperbolic divergences with the change of orientability, to the biomechanics of vision and the mammal heart, to the morphogenesis of crustal shapes on Earth in connection to the wavefronts of gravitation, elasticity and electromagnetism, to pattern recognition of artificial images and visual recognition, to neurology and the topographic maps of the sensorium, to perception, in particular of music. We develop it in terms of the fundamental 2:1 resonance inherent to the Möbius strip and the Klein Bottle, the minimal surfaces representation of the wavefronts, and the non-dual Klein Bottle logic inherent to pattern recognition, to the harmonic functions and vector fields that lay at the basis of geophysics and physics at large. We discuss the relation between the topographic maps of the sensorium, and the issue of turning inside-out of the visual world as a general principle for cognition, topological chemistry, cell biology and biological morphogenesis in particular in embryology

Computational and theoretical approaches for studies of a lipid recognition protein on biological membranes

PubMed Central

Yamamoto, Eiji

2017-01-01

Many cellular functions, including cell signaling and related events, are regulated by the association of peripheral membrane proteins (PMPs) with biological membranes containing anionic lipids, e.g., phosphatidylinositol phosphate (PIP). This association is often mediated by lipid recognition modules present in many PMPs. Here, I summarize computational and theoretical approaches to investigate the molecular details of the interactions and dynamics of a lipid recognition module, the pleckstrin homology (PH) domain, on biological membranes. Multiscale molecular dynamics simulations using combinations of atomistic and coarse-grained models yielded results comparable to those of actual experiments and could be used to elucidate the molecular mechanisms of the formation of protein/lipid complexes on membrane surfaces, which are often difficult to obtain using experimental techniques. Simulations revealed some modes of membrane localization and interactions of PH domains with membranes in addition to the canonical binding mode. In the last part of this review, I address the dynamics of PH domains on the membrane surface. Local PIP clusters formed around the proteins exhibit anomalous fluctuations. This dynamic change in protein-lipid interactions cause temporally fluctuating diffusivity of proteins, i.e., the short-term diffusivity of the bound protein changes substantially with time, and may in turn contribute to the formation/dissolution of protein complexes in membranes. PMID:29159013

The influence of developmental environment on courtship song in cactophilic Drosophila.

PubMed

Iglesias, Patricia P; Soto, Eduardo M; Soto, Ignacio M; Colines, Betina; Hasson, Esteban

2018-04-15

Closely related species often differ in the signals involved in sexual communication and mate recognition. Determining the factors influencing signal quality (i.e. signal's content and conspicuousness) provides an important insight into the potential pathways by which these interspecific differences evolve. Host specificity could bias the direction of the evolution of sexual communication and the mate recognition system, favouring sensory channels that work best in the different host conditions. In this study, we focus on the cactophilic sibling species Drosophila buzzatii and D. koepferae that have diverged not only in the sensory channel used for sexual communication and mate recognition but also in the cactus species that use as primary hosts. We evaluate the role of the developmental environment in generating courtship song variation using an isofemale line design. Our results show that host environment during development induces changes in the courtship song of D. koepferae males, but not in D. buzzatii males. Moreover, we report for the first time that host rearing environment affects the conspicuousness of courtship song (i.e. song volume). Our results are mainly discussed in the context of the sensory drive hypothesis. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Recognition Imaging of Acetylated Chromatin Using a DNA Aptamer

PubMed Central

Lin, Liyun; Fu, Qiang; Williams, Berea A.R.; Azzaz, Abdelhamid M.; Shogren-Knaak, Michael A.; Chaput, John C.; Lindsay, Stuart

2009-01-01

Histone acetylation plays an important role in the regulation of gene expression. A DNA aptamer generated by in vitro selection to be highly specific for histone H4 protein acetylated at lysine 16 was used as a recognition element for atomic force microscopy-based recognition imaging of synthetic nucleosomal arrays with precisely controlled acetylation. The aptamer proved to be reasonably specific at recognizing acetylated histones, with recognition efficiencies of 60% on-target and 12% off-target. Though this selectivity is much poorer than the >2000:1 equilibrium specificity of the aptamer, it is a large improvement on the performance of a ChIP-quality antibody, which is not selective at all in this application, and it should permit high-fidelity recognition with repeated imaging. The ability to image the precise location of posttranslational modifications may permit nanometer-scale investigation of their effect on chromatin structure. PMID:19751687

A Complete OCR System for Tamil Magazine Documents

NASA Astrophysics Data System (ADS)

Kokku, Aparna; Chakravarthy, Srinivasa

We present a complete optical character recognition (OCR) system for Tamil magazines/documents. All the standard elements of OCR process like de-skewing, preprocessing, segmentation, character recognition, and reconstruction are implemented. Experience with OCR problems teaches that for most subtasks of OCR, there is no single technique that gives perfect results for every type of document image. We exploit the ability of neural networks to learn from experience in solving the problems of segmentation and character recognition. Text segmentation of Tamil newsprint poses a new challenge owing to its italic-like font type; problems that arise in recognition of touching and close characters are discussed. Character recognition efficiency varied from 94 to 97% for this type of font. The grouping of blocks into logical units and the determination of reading order within each logical unit helped us in reconstructing automatically the document image in an editable format.

Biological origins of color categorization.

PubMed

Skelton, Alice E; Catchpole, Gemma; Abbott, Joshua T; Bosten, Jenny M; Franklin, Anna

2017-05-23

The biological basis of the commonality in color lexicons across languages has been hotly debated for decades. Prior evidence that infants categorize color could provide support for the hypothesis that color categorization systems are not purely constructed by communication and culture. Here, we investigate the relationship between infants' categorization of color and the commonality across color lexicons, and the potential biological origin of infant color categories. We systematically mapped infants' categorical recognition memory for hue onto a stimulus array used previously to document the color lexicons of 110 nonindustrialized languages. Following familiarization to a given hue, infants' response to a novel hue indicated that their recognition memory parses the hue continuum into red, yellow, green, blue, and purple categories. Infants' categorical distinctions aligned with common distinctions in color lexicons and are organized around hues that are commonly central to lexical categories across languages. The boundaries between infants' categorical distinctions also aligned, relative to the adaptation point, with the cardinal axes that describe the early stages of color representation in retinogeniculate pathways, indicating that infant color categorization may be partly organized by biological mechanisms of color vision. The findings suggest that color categorization in language and thought is partially biologically constrained and have implications for broader debate on how biology, culture, and communication interact in human cognition.

Biological origins of color categorization

PubMed Central

Catchpole, Gemma; Abbott, Joshua T.; Bosten, Jenny M.; Franklin, Anna

2017-01-01

The biological basis of the commonality in color lexicons across languages has been hotly debated for decades. Prior evidence that infants categorize color could provide support for the hypothesis that color categorization systems are not purely constructed by communication and culture. Here, we investigate the relationship between infants’ categorization of color and the commonality across color lexicons, and the potential biological origin of infant color categories. We systematically mapped infants’ categorical recognition memory for hue onto a stimulus array used previously to document the color lexicons of 110 nonindustrialized languages. Following familiarization to a given hue, infants’ response to a novel hue indicated that their recognition memory parses the hue continuum into red, yellow, green, blue, and purple categories. Infants’ categorical distinctions aligned with common distinctions in color lexicons and are organized around hues that are commonly central to lexical categories across languages. The boundaries between infants’ categorical distinctions also aligned, relative to the adaptation point, with the cardinal axes that describe the early stages of color representation in retinogeniculate pathways, indicating that infant color categorization may be partly organized by biological mechanisms of color vision. The findings suggest that color categorization in language and thought is partially biologically constrained and have implications for broader debate on how biology, culture, and communication interact in human cognition. PMID:28484022

A high-throughput screening approach to discovering good forms of biologically inspired visual representation.

PubMed

Pinto, Nicolas; Doukhan, David; DiCarlo, James J; Cox, David D

2009-11-01

While many models of biological object recognition share a common set of "broad-stroke" properties, the performance of any one model depends strongly on the choice of parameters in a particular instantiation of that model--e.g., the number of units per layer, the size of pooling kernels, exponents in normalization operations, etc. Since the number of such parameters (explicit or implicit) is typically large and the computational cost of evaluating one particular parameter set is high, the space of possible model instantiations goes largely unexplored. Thus, when a model fails to approach the abilities of biological visual systems, we are left uncertain whether this failure is because we are missing a fundamental idea or because the correct "parts" have not been tuned correctly, assembled at sufficient scale, or provided with enough training. Here, we present a high-throughput approach to the exploration of such parameter sets, leveraging recent advances in stream processing hardware (high-end NVIDIA graphic cards and the PlayStation 3's IBM Cell Processor). In analogy to high-throughput screening approaches in molecular biology and genetics, we explored thousands of potential network architectures and parameter instantiations, screening those that show promising object recognition performance for further analysis. We show that this approach can yield significant, reproducible gains in performance across an array of basic object recognition tasks, consistently outperforming a variety of state-of-the-art purpose-built vision systems from the literature. As the scale of available computational power continues to expand, we argue that this approach has the potential to greatly accelerate progress in both artificial vision and our understanding of the computational underpinning of biological vision.

An expanded framework for biomolecular visualization in the classroom: Learning goals and competencies.

PubMed

Dries, Daniel R; Dean, Diane M; Listenberger, Laura L; Novak, Walter R P; Franzen, Margaret A; Craig, Paul A

2017-01-02

A thorough understanding of the molecular biosciences requires the ability to visualize and manipulate molecules in order to interpret results or to generate hypotheses. While many instructors in biochemistry and molecular biology use visual representations, few indicate that they explicitly teach visual literacy. One reason is the need for a list of core content and competencies to guide a more deliberate instruction in visual literacy. We offer here the second stage in the development of one such resource for biomolecular three-dimensional visual literacy. We present this work with the goal of building a community for online resource development and use. In the first stage, overarching themes were identified and submitted to the biosciences community for comment: atomic geometry; alternate renderings; construction/annotation; het group recognition; molecular dynamics; molecular interactions; monomer recognition; symmetry/asymmetry recognition; structure-function relationships; structural model skepticism; and topology and connectivity. Herein, the overarching themes have been expanded to include a 12th theme (macromolecular assemblies), 27 learning goals, and more than 200 corresponding objectives, many of which cut across multiple overarching themes. The learning goals and objectives offered here provide educators with a framework on which to map the use of molecular visualization in their classrooms. In addition, the framework may also be used by biochemistry and molecular biology educators to identify gaps in coverage and drive the creation of new activities to improve visual literacy. This work represents the first attempt, to our knowledge, to catalog a comprehensive list of explicit learning goals and objectives in visual literacy. © 2016 by The International Union of Biochemistry and Molecular Biology, 45(1):69-75, 2017. © 2016 The Authors Biochemistry and Molecular Biology Education published by Wiley Periodicals, Inc. on behalf of International Union of Biochemistry and Molecular Biology.

A High-Throughput Screening Approach to Discovering Good Forms of Biologically Inspired Visual Representation

PubMed Central

Pinto, Nicolas; Doukhan, David; DiCarlo, James J.; Cox, David D.

2009-01-01

While many models of biological object recognition share a common set of “broad-stroke” properties, the performance of any one model depends strongly on the choice of parameters in a particular instantiation of that model—e.g., the number of units per layer, the size of pooling kernels, exponents in normalization operations, etc. Since the number of such parameters (explicit or implicit) is typically large and the computational cost of evaluating one particular parameter set is high, the space of possible model instantiations goes largely unexplored. Thus, when a model fails to approach the abilities of biological visual systems, we are left uncertain whether this failure is because we are missing a fundamental idea or because the correct “parts” have not been tuned correctly, assembled at sufficient scale, or provided with enough training. Here, we present a high-throughput approach to the exploration of such parameter sets, leveraging recent advances in stream processing hardware (high-end NVIDIA graphic cards and the PlayStation 3's IBM Cell Processor). In analogy to high-throughput screening approaches in molecular biology and genetics, we explored thousands of potential network architectures and parameter instantiations, screening those that show promising object recognition performance for further analysis. We show that this approach can yield significant, reproducible gains in performance across an array of basic object recognition tasks, consistently outperforming a variety of state-of-the-art purpose-built vision systems from the literature. As the scale of available computational power continues to expand, we argue that this approach has the potential to greatly accelerate progress in both artificial vision and our understanding of the computational underpinning of biological vision. PMID:19956750

How a Hat May Affect 3-Month-Olds' Recognition of a Face: An Eye-Tracking Study

PubMed Central

Bulf, Hermann; Valenza, Eloisa; Turati, Chiara

2013-01-01

Recent studies have shown that infants’ face recognition rests on a robust face representation that is resilient to a variety of facial transformations such as rotations in depth, motion, occlusion or deprivation of inner/outer features. Here, we investigated whether 3-month-old infants’ ability to represent the invariant aspects of a face is affected by the presence of an external add-on element, i.e. a hat. Using a visual habituation task, three experiments were carried out in which face recognition was investigated by manipulating the presence/absence of a hat during face encoding (i.e. habituation phase) and face recognition (i.e. test phase). An eye-tracker system was used to record the time infants spent looking at face-relevant information compared to the hat. The results showed that infants’ face recognition was not affected by the presence of the external element when the type of the hat did not vary between the habituation and test phases, and when both the novel and the familiar face wore the same hat during the test phase (Experiment 1). Infants’ ability to recognize the invariant aspects of a face was preserved also when the hat was absent in the habituation phase and the same hat was shown only during the test phase (Experiment 2). Conversely, when the novel face identity competed with a novel hat, the hat triggered the infants’ attention, interfering with the recognition process and preventing the infants’ preference for the novel face during the test phase (Experiment 3). Findings from the current study shed light on how faces and objects are processed when they are simultaneously presented in the same visual scene, contributing to an understanding of how infants respond to the multiple and composite information available in their surrounding environment. PMID:24349378

How a hat may affect 3-month-olds' recognition of a face: an eye-tracking study.

PubMed

Bulf, Hermann; Valenza, Eloisa; Turati, Chiara

2013-01-01

Recent studies have shown that infants' face recognition rests on a robust face representation that is resilient to a variety of facial transformations such as rotations in depth, motion, occlusion or deprivation of inner/outer features. Here, we investigated whether 3-month-old infants' ability to represent the invariant aspects of a face is affected by the presence of an external add-on element, i.e. a hat. Using a visual habituation task, three experiments were carried out in which face recognition was investigated by manipulating the presence/absence of a hat during face encoding (i.e. habituation phase) and face recognition (i.e. test phase). An eye-tracker system was used to record the time infants spent looking at face-relevant information compared to the hat. The results showed that infants' face recognition was not affected by the presence of the external element when the type of the hat did not vary between the habituation and test phases, and when both the novel and the familiar face wore the same hat during the test phase (Experiment 1). Infants' ability to recognize the invariant aspects of a face was preserved also when the hat was absent in the habituation phase and the same hat was shown only during the test phase (Experiment 2). Conversely, when the novel face identity competed with a novel hat, the hat triggered the infants' attention, interfering with the recognition process and preventing the infants' preference for the novel face during the test phase (Experiment 3). Findings from the current study shed light on how faces and objects are processed when they are simultaneously presented in the same visual scene, contributing to an understanding of how infants respond to the multiple and composite information available in their surrounding environment.

Repeatability and reproducibility of intracellular molar concentration assessed by synchrotron-based x-ray fluorescence microscopy

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

Merolle, L., E-mail: lucia.merolle@elettra.eu; Gianoncelli, A.; Malucelli, E., E-mail: emil.malucelli@unibo.it

2016-01-28

Elemental analysis of biological sample can give information about content and distribution of elements essential for human life or trace elements whose absence is the cause of abnormal biological function or development. However, biological systems contain an ensemble of cells with heterogeneous chemistry and elemental content; therefore, accurate characterization of samples with high cellular heterogeneity may only be achieved by analyzing single cells. Powerful methods in molecular biology are abundant, among them X-Ray microscopy based on synchrotron light source has gaining increasing attention thanks to its extremely sensitivity. However, reproducibility and repeatability of these measurements is one of the majormore » obstacles in achieving a statistical significance in single cells population analysis. In this study, we compared the elemental content of human colon adenocarcinoma cells obtained by three distinct accesses to synchrotron radiation light.« less

Investigation of Carbohydrate Recognition via Computer Simulation

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

Johnson, Quentin R.; Lindsay, Richard J.; Petridis, Loukas

Carbohydrate recognition by proteins, such as lectins and other (bio)molecules, can be essential for many biological functions. Interest has arisen due to potential protein and drug design and future bioengineering applications. A quantitative measurement of carbohydrate-protein interaction is thus important for the full characterization of sugar recognition. Here, we focus on the aspect of utilizing computer simulations and biophysical models to evaluate the strength and specificity of carbohydrate recognition in this review. With increasing computational resources, better algorithms and refined modeling parameters, using state-of-the-art supercomputers to calculate the strength of the interaction between molecules has become increasingly mainstream. We reviewmore » the current state of this technique and its successful applications for studying protein-sugar interactions in recent years.« less

Investigation of Carbohydrate Recognition via Computer Simulation

DOE PAGES

Johnson, Quentin R.; Lindsay, Richard J.; Petridis, Loukas; ...

2015-04-28

Carbohydrate recognition by proteins, such as lectins and other (bio)molecules, can be essential for many biological functions. Interest has arisen due to potential protein and drug design and future bioengineering applications. A quantitative measurement of carbohydrate-protein interaction is thus important for the full characterization of sugar recognition. Here, we focus on the aspect of utilizing computer simulations and biophysical models to evaluate the strength and specificity of carbohydrate recognition in this review. With increasing computational resources, better algorithms and refined modeling parameters, using state-of-the-art supercomputers to calculate the strength of the interaction between molecules has become increasingly mainstream. We reviewmore » the current state of this technique and its successful applications for studying protein-sugar interactions in recent years.« less

Novel Platform Development Using an Assembly of Carbon Nanotube, Nanogold and Immobilized RNA Capture Element Towards Rapid, Selective Sensing of Bacteria

DTIC Science & Technology

2012-06-12

Doped Polyaniline/Carbon Nanotube Composite for Sensitive and Selective Detection of the Neurotransmitter Dopamine . Anal. Chem. 2007, 79, 2583–2587...biosensor with aptamers as bio-recognition element. Sensors 2010, 10, 5859–5871. Sensors 2012, 12 8144 14. Hernandez, F.J.; Ozalp, V.C. Graphene

Final report for CCQM-K107: total elements and selenomethionine in human serum

NASA Astrophysics Data System (ADS)

Goenaga Infante, Heidi

2016-01-01

Routine tests that measure the concentration of electrolytes in serum are needed for diagnosis and management of renal, endocrine, acid-base, water balance and other conditions such as screening D- and A-vitamin disorders, kidney insufficiency, bone diseases and leukaemia. The diagnostic concentration ranges for many such markers are narrow, requiring reference methods with small uncertainty. Serum concentration of total selenium (Se) is important in health studies but there is increasing interest in the speciation of selenium compounds in clinical samples such as serum and individual Se- Species are bio-indicators of Se status. The last CCQM IAWG key comparison for elements in the clinical area (CCQM-K14: Ca in human serum) was organized in 2003 and the previous key comparison (CCQM-K60) for Se and Se species used a wheat flour sample. Therefore, the CCQM IAWG agreed that CCQM-K107 and a parallel pilot study CCQM-P146 should be carried out. The candidate human serum sample used for both CCQM-K107 and P146 is of high complexity and contains approximately 1000-fold lower concentrations of selenium methionine (SeMet) than those encountered in the CCQM-K60 wheat flour. This significantly broadens the scope and degree of difficulty of earlier measurements in this field. A total of eleven institutes participated in CCQM-K107 (11 participants for total elements and 7 for SeMet). The performance of the majority of the K107 participants for all the measurands was very good, illustrating their ability to obtain accurate results for analytes such as electrolytes at mg kg-1 level, essential elements at µg kg-1 level and selenium species at µg kg-1 level in a complex biological fluid. The range of agreement between participants was within the interval of ± 0.1% for Ca and up to ± 1.8% for Fe. CMC claims based on total elements in this study may include other elements with similar core competencies (e.g. Se, Cu, Zn) in a wide range of biological materials (including liquids and solids) at a similar level of performance using the same measurement technique applied in CCQM-K107 provided that there are no additional factors (e.g. blank or dissolution issues). CMC claims based on SeMet measurements in this study may be applied to other biological matrices (e.g., tissues) provided that the concentration range is similar and due diligence is taken to ensure an appropriate extraction process is achieved and species specific spikes are available for quantitation by isotope dilution. Indeed, having accepted such conditions, application to quantitation of other organometallic species and other elements in similar matrices should be possible with the same level of performance. Main text To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/. The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Recognition- and reactivity-based fluorescent probes for studying transition metal signaling in living systems.

PubMed

Aron, Allegra T; Ramos-Torres, Karla M; Cotruvo, Joseph A; Chang, Christopher J

2015-08-18

Metals are essential for life, playing critical roles in all aspects of the central dogma of biology (e.g., the transcription and translation of nucleic acids and synthesis of proteins). Redox-inactive alkali, alkaline earth, and transition metals such as sodium, potassium, calcium, and zinc are widely recognized as dynamic signals, whereas redox-active transition metals such as copper and iron are traditionally thought of as sequestered by protein ligands, including as static enzyme cofactors, in part because of their potential to trigger oxidative stress and damage via Fenton chemistry. Metals in biology can be broadly categorized into two pools: static and labile. In the former, proteins and other macromolecules tightly bind metals; in the latter, metals are bound relatively weakly to cellular ligands, including proteins and low molecular weight ligands. Fluorescent probes can be useful tools for studying the roles of transition metals in their labile forms. Probes for imaging transition metal dynamics in living systems must meet several stringent criteria. In addition to exhibiting desirable photophysical properties and biocompatibility, they must be selective and show a fluorescence turn-on response to the metal of interest. To meet this challenge, we have pursued two general strategies for metal detection, termed "recognition" and "reactivity". Our design of transition metal probes makes use of a recognition-based approach for copper and nickel and a reactivity-based approach for cobalt and iron. This Account summarizes progress in our laboratory on both the development and application of fluorescent probes to identify and study the signaling roles of transition metals in biology. In conjunction with complementary methods for direct metal detection and genetic and/or pharmacological manipulations, fluorescent probes for transition metals have helped reveal a number of principles underlying transition metal dynamics. In this Account, we give three recent examples from our laboratory and collaborations in which applications of chemical probes reveal that labile copper contributes to various physiologies. The first example shows that copper is an endogenous regulator of neuronal activity, the second illustrates cellular prioritization of mitochondrial copper homeostasis, and the third identifies the "cuprosome" as a new copper storage compartment in Chlamydomonas reinhardtii green algae. Indeed, recognition- and reactivity-based fluorescent probes have helped to uncover new biological roles for labile transition metals, and the further development of fluorescent probes, including ones with varied Kd values and new reaction triggers and recognition receptors, will continue to reveal exciting and new biological roles for labile transition metals.

Cloud-based uniform ChIP-Seq processing tools for modENCODE and ENCODE.

PubMed

Trinh, Quang M; Jen, Fei-Yang Arthur; Zhou, Ziru; Chu, Kar Ming; Perry, Marc D; Kephart, Ellen T; Contrino, Sergio; Ruzanov, Peter; Stein, Lincoln D

2013-07-22

Funded by the National Institutes of Health (NIH), the aim of the Model Organism ENCyclopedia of DNA Elements (modENCODE) project is to provide the biological research community with a comprehensive encyclopedia of functional genomic elements for both model organisms C. elegans (worm) and D. melanogaster (fly). With a total size of just under 10 terabytes of data collected and released to the public, one of the challenges faced by researchers is to extract biologically meaningful knowledge from this large data set. While the basic quality control, pre-processing, and analysis of the data has already been performed by members of the modENCODE consortium, many researchers will wish to reinterpret the data set using modifications and enhancements of the original protocols, or combine modENCODE data with other data sets. Unfortunately this can be a time consuming and logistically challenging proposition. In recognition of this challenge, the modENCODE DCC has released uniform computing resources for analyzing modENCODE data on Galaxy (https://github.com/modENCODE-DCC/Galaxy), on the public Amazon Cloud (http://aws.amazon.com), and on the private Bionimbus Cloud for genomic research (http://www.bionimbus.org). In particular, we have released Galaxy workflows for interpreting ChIP-seq data which use the same quality control (QC) and peak calling standards adopted by the modENCODE and ENCODE communities. For convenience of use, we have created Amazon and Bionimbus Cloud machine images containing Galaxy along with all the modENCODE data, software and other dependencies. Using these resources provides a framework for running consistent and reproducible analyses on modENCODE data, ultimately allowing researchers to use more of their time using modENCODE data, and less time moving it around.

Cloud-based uniform ChIP-Seq processing tools for modENCODE and ENCODE

PubMed Central

2013-01-01

Background Funded by the National Institutes of Health (NIH), the aim of the Model Organism ENCyclopedia of DNA Elements (modENCODE) project is to provide the biological research community with a comprehensive encyclopedia of functional genomic elements for both model organisms C. elegans (worm) and D. melanogaster (fly). With a total size of just under 10 terabytes of data collected and released to the public, one of the challenges faced by researchers is to extract biologically meaningful knowledge from this large data set. While the basic quality control, pre-processing, and analysis of the data has already been performed by members of the modENCODE consortium, many researchers will wish to reinterpret the data set using modifications and enhancements of the original protocols, or combine modENCODE data with other data sets. Unfortunately this can be a time consuming and logistically challenging proposition. Results In recognition of this challenge, the modENCODE DCC has released uniform computing resources for analyzing modENCODE data on Galaxy (https://github.com/modENCODE-DCC/Galaxy), on the public Amazon Cloud (http://aws.amazon.com), and on the private Bionimbus Cloud for genomic research (http://www.bionimbus.org). In particular, we have released Galaxy workflows for interpreting ChIP-seq data which use the same quality control (QC) and peak calling standards adopted by the modENCODE and ENCODE communities. For convenience of use, we have created Amazon and Bionimbus Cloud machine images containing Galaxy along with all the modENCODE data, software and other dependencies. Conclusions Using these resources provides a framework for running consistent and reproducible analyses on modENCODE data, ultimately allowing researchers to use more of their time using modENCODE data, and less time moving it around. PMID:23875683

Method for the electro-addressable functionalization of electrode arrays

DOEpatents

Harper, Jason C.; Polsky, Ronen; Dirk, Shawn M.; Wheeler, David R.; Arango, Dulce C.; Brozik, Susan M.

2015-12-15

A method for preparing an electrochemical biosensor uses bias-assisted assembly of unreactive -onium molecules on an electrode array followed by post-assembly electro-addressable conversion of the unreactive group to a chemical or biological recognition group. Electro-addressable functionalization of electrode arrays enables the multi-target electrochemical sensing of biological and chemical analytes.

Introduction of the human AVPR1A gene substantially alters brain receptor expression patterns and enhances aspects of social behavior in transgenic mice

PubMed Central

Charles, Rhonda; Sakurai, Takeshi; Takahashi, Nagahide; Elder, Gregory A.; Gama Sosa, Miguel A.; Young, Larry J.; Buxbaum, Joseph D.

2014-01-01

Central arginine vasopressin receptor 1A (AVPR1A) modulates a wide range of behaviors, including stress management and territorial aggression, as well as social bonding and recognition. Inter- and intra-species variations in the expression pattern of AVPR1A in the brain and downstream differential behavioral phenotypes have been attributed to differences in the non-coding regions of the AVPR1A gene, including polymorphic elements within upstream regulatory areas. Gene association studies have suggested a link between AVPR1A polymorphisms and autism, and AVPR1A has emerged as a potential pharmacological target for treatment of social cognitive impairments and mood and anxiety disorders. To further investigate the genetic mechanism giving rise to species differences in AVPR1A expression patterns and associated social behaviors, and to create a preclinical mouse model useful for screening drugs targeting AVPR1A, we engineered and extensively characterized bacterial artificial chromosome (BAC) transgenic mice harboring the entire human AVPR1A locus with the surrounding regulatory elements. Compared with wild-type animals, the humanized mice displayed a more widely distributed ligand-AVPR1A binding pattern, which overlapped with that of primates. Furthermore, humanized AVPR1A mice displayed increased reciprocal social interactions compared with wild-type animals, but no differences in social approach and preference for social novelty were observed. Aspects of learning and memory, specifically novel object recognition and spatial relocation recognition, were unaffected. The biological alterations in humanized AVPR1A mice resulted in the rescue of the prepulse inhibition impairments that were observed in knockout mice, indicating conserved functionality. Although further behavioral paradigms and additional cohorts need to be examined in humanized AVPR1A mice, the results demonstrate that species-specific variations in the genomic content of regulatory regions surrounding the AVPR1A locus are responsible for differential receptor protein expression patterns across species and that they are likely to contribute to species-specific behavioral variation. The humanized AVPR1A mouse is a potential preclinical model for further understanding the regulation of receptor gene expression and the impact of variation in receptor expression on behaviors, and should be useful for screening drugs targeting human AVPR1A, taking advantage of the expression of human AVPR1A in human-relevant brain regions. PMID:24924430

Fundamentals of Enzyme-Based Sensors

NASA Astrophysics Data System (ADS)

Moreno-Bondi, María C.; Benito-Peña, Elena

One of the mayor outbreaks in the development of analytical measurement techniques was the introduction, in the mid-twentieth century, of bioprobes for the analysis of chemical and biochemical compounds in real samples. The first devices, developed in the 1950's and 1960's by Clark et al. were based on electrochemical measurements and allowed the determination of oxygen and glucose in tissues and blood samples. Later on, in the 1970's, optical transduction was coupled to enzymatically-catalyzed reactions3 and since those early days the field of application of optical biosensors has broaden up considerably. According to the definition proposed by the International Union of Pure and Applied Chemistry (IUPAC): "A biosensor is a self-contained integrated device which is capable of providing specific quantitative or semi-quantitative analytical information using a biological recognition element (biochemical receptor) which is in direct spatial contact with a transducer element. A biosensor should be clearly distinguished from a bioanalytical system, which requires additional processing steps, such as reagent addition. Furthermore, a biosensor should be distinguished from a bioprobe which is either disposable after one measurement, i.e. single use, or unable to continuously monitor the analyte concentration". The general scheme of a biosensor configuration is shown in Figure 1. Biosensors that include transducers based on integrated circuit microchips are known as biochips.

Emergy Evaluations of the Global Biogeochemical Cycles of Six Biologically Active Elements and Two Compounds

EPA Science Inventory

Estimates of the emergy carried by the flows of biologically active elements (BAE) and compounds are needed to accurately evaluate the near and far field effects of anthropogenic wastes. The transformities and specific emergies of these elements and of their different chemical sp...

In Vitro Selection of a Single-Stranded DNA Molecular Recognition Element against the Pesticide Fipronil and Sensitive Detection in River Water

PubMed Central

Sooter, Letha J.

2017-01-01

Fipronil is a commonly used insecticide that has been shown to have environmental and human health risks. The current standard methods of detection for fipronil and its metabolites, such as GC-MS, are time consuming and labor intensive. In this study, a variant of systematic evolution of ligands by exponential enrichment (SELEX), was utilized to identify the first single-stranded DNA (ssDNA) molecular recognition element (MRE) that binds to fipronil with high affinity (Kd = 48 ± 8 nM). The selected MRE displayed low cross binding activity on various environmentally relevant, structurally unrelated herbicides and pesticides, in addition to broad-spectrum binding activity on major metabolites of fipronil and a structurally similar pesticide in prepared river samples. Additionally, a proof-of-principle fluorescent detection assay was developed by using the selected ssDNA MRE as a signal-reporting element, with a limit of detection of 105 nM in a prepared river water sample. PMID:29283416

Recent advances in the development of extraction chromatographic materials for the isolation of radionuclides from biological and environmental samples.

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

Dietz, M. L.

1998-11-30

The determination of low levels of radionuclides in environmental and biological samples is often hampered by the complex and variable nature of the samples. One approach to circumventing this problem is to incorporate into the analytical scheme a separation and preconcentration step by which the species of interest can be isolated from the major constituents of the sample. Extraction chromatography (EXC), a form of liquid chromatography in which the stationary phase comprises an extractant or a solution of an extractant in an appropriate diluent coated onto an inert support, provides a simple and efficient means of performing a wide varietymore » of metal ion separations. Recent advances in extractant design, in particular the development of extractants capable of metal ion recognition or of strong complex formation even in acidic media, have substantially improved the utility of the method. For the preconcentration of actinides, for example, an EXC resin consisting of a liquid diphosphonic acid supported on a polymeric substrate has been shown to exhibit extraordinarily strong retention of these elements from acidic chloride media. This resin, together with other related materials, can provide the basis of a number of efficient and flexible schemes for the separation and preconcentration of radionuclides form a variety of samples for subsequent determination.« less

Recognition-driven chemical labeling of endogenous proteins in multi-molecular crowding in live cells.

PubMed

Amaike, Kazuma; Tamura, Tomonori; Hamachi, Itaru

2017-11-14

Endogenous protein labeling is one of the most invaluable methods for studying the bona fide functions of proteins in live cells. However, multi-molecular crowding conditions, such as those that occur in live cells, hamper the highly selective chemical labeling of a protein of interest (POI). We herein describe how the efficient coupling of molecular recognition with a chemical reaction is crucial for selective protein labeling. Recognition-driven protein labeling is carried out by a synthetic labeling reagent containing a protein (recognition) ligand, a reporter tag, and a reactive moiety. The molecular recognition of a POI can be used to greatly enhance the reaction kinetics and protein selectivity, even under live cell conditions. In this review, we also briefly discuss how such selective chemical labeling of an endogenous protein can have a variety of applications at the interface of chemistry and biology.

Method for fabrication and verification of conjugated nanoparticle-antibody tuning elements for multiplexed electrochemical biosensors.

PubMed

La Belle, Jeffrey T; Fairchild, Aaron; Demirok, Ugur K; Verma, Aman

2013-05-15

There is a critical need for more accurate, highly sensitive and specific assay for disease diagnosis and management. A novel, multiplexed, single sensor using rapid and label free electrochemical impedance spectroscopy tuning method has been developed. The key challenges while monitoring multiple targets is frequency overlap. Here we describe the methods to circumvent the overlap, tune by use of nanoparticle (NP) and discuss the various fabrication and characterization methods to develop this technique. First sensors were fabricated using printed circuit board (PCB) technology and nickel and gold layers were electrodeposited onto the PCB sensors. An off-chip conjugation of gold NP's to molecular recognition elements (with verification technique) is described as well. A standard covalent immobilization of the molecular recognition elements is also discussed with quality control techniques. Finally use and verification of sensitivity and specificity is also presented. By use of gold NP's of various sizes, we have demonstrated the possibility and shown little loss of sensitivity and specificity in the molecular recognition of inflammatory markers as "model" targets for our tuning system. By selection of other sized NP's or NP's of various materials, the tuning effect can be further exploited. The novel platform technology developed could be utilized in critical care, clinical management and at home health and disease management. Copyright © 2013 Elsevier Inc. All rights reserved.

Modularization of genetic elements promotes synthetic metabolic engineering.

PubMed

Qi, Hao; Li, Bing-Zhi; Zhang, Wen-Qian; Liu, Duo; Yuan, Ying-Jin

2015-11-15

In the context of emerging synthetic biology, metabolic engineering is moving to the next stage powered by new technologies. Systematical modularization of genetic elements makes it more convenient to engineer biological systems for chemical production or other desired purposes. In the past few years, progresses were made in engineering metabolic pathway using synthetic biology tools. Here, we spotlighted the topic of implementation of modularized genetic elements in metabolic engineering. First, we overviewed the principle developed for modularizing genetic elements and then discussed how the genetic modules advanced metabolic engineering studies. Next, we picked up some milestones of engineered metabolic pathway achieved in the past few years. Last, we discussed the rapid raised synthetic biology field of "building a genome" and the potential in metabolic engineering. Copyright © 2015 Elsevier Inc. All rights reserved.

Common themes and differences in SAM recognition among SAM riboswitches

PubMed Central

Price, Ian R.; Grigg, Jason C.; Ke, Ailong

2014-01-01

The recent discovery of short cis-acting RNA elements termed riboswitches has caused a paradigm shift in our understanding of genetic regulatory mechanisms. The three distinct superfamilies of S-adenosyl-L-methionine (SAM) riboswitches are the most commonly found riboswitch classes in nature. These RNAs represent three independent evolutionary solutions to achieve specific SAM recognition. This review summarizes research on 1) modes of gene regulatory mechanisms, 2) common themes and differences in ligand recognition, and 3) ligand-induced conformational dynamics among SAM riboswitch families. The body of work on the SAM riboswitch families constitutes a useful primer to the topic of gene regulatory RNAs as a whole. PMID:24863160

Plant recognition of Bradyrhizobium japonicum nod factors. Final report, September 15, 1992--March 14, 1997

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

Stacey, G.

1998-01-01

This grant had three objectives: (1) isolate and identify the unique nod factor metabolites made by different wild-type B. japonicum strains; (2) investigate the biological activity of these unique nod factors, especially as it relates to host range; and (3) initiate studies to define the mechanism of plant recognition of the nod factors. This report summarizes the results of this research.

Feature Vector Construction Method for IRIS Recognition

NASA Astrophysics Data System (ADS)

Odinokikh, G.; Fartukov, A.; Korobkin, M.; Yoo, J.

2017-05-01

One of the basic stages of iris recognition pipeline is iris feature vector construction procedure. The procedure represents the extraction of iris texture information relevant to its subsequent comparison. Thorough investigation of feature vectors obtained from iris showed that not all the vector elements are equally relevant. There are two characteristics which determine the vector element utility: fragility and discriminability. Conventional iris feature extraction methods consider the concept of fragility as the feature vector instability without respect to the nature of such instability appearance. This work separates sources of the instability into natural and encodinginduced which helps deeply investigate each source of instability independently. According to the separation concept, a novel approach of iris feature vector construction is proposed. The approach consists of two steps: iris feature extraction using Gabor filtering with optimal parameters and quantization with separated preliminary optimized fragility thresholds. The proposed method has been tested on two different datasets of iris images captured under changing environmental conditions. The testing results show that the proposed method surpasses all the methods considered as a prior art by recognition accuracy on both datasets.

Branched Pectic Galactan in Phloem-Sieve-Element Cell Walls: Implications for Cell Mechanics.

PubMed

Torode, Thomas A; O'Neill, Rachel; Marcus, Susan E; Cornuault, Valérie; Pose, Sara; Lauder, Rebecca P; Kračun, Stjepan K; Rydahl, Maja Gro; Andersen, Mathias C F; Willats, William G T; Braybrook, Siobhan A; Townsend, Belinda J; Clausen, Mads H; Knox, J Paul

2018-02-01

A major question in plant biology concerns the specification and functional differentiation of cell types. This is in the context of constraints imposed by networks of cell walls that both adhere cells and contribute to the form and function of developing organs. Here, we report the identification of a glycan epitope that is specific to phloem sieve element cell walls in several systems. A monoclonal antibody, designated LM26, binds to the cell wall of phloem sieve elements in stems of Arabidopsis ( Arabidopsis thaliana ), Miscanthus x giganteus , and notably sugar beet ( Beta vulgaris ) roots where phloem identification is an important factor for the study of phloem unloading of Suc. Using microarrays of synthetic oligosaccharides, the LM26 epitope has been identified as a β-1,6-galactosyl substitution of β-1,4-galactan requiring more than three backbone residues for optimized recognition. This branched galactan structure has previously been identified in garlic ( Allium sativum ) bulbs in which the LM26 epitope is widespread throughout most cell walls including those of phloem cells. Garlic bulb cell wall material has been used to confirm the association of the LM26 epitope with cell wall pectic rhamnogalacturonan-I polysaccharides. In the phloem tissues of grass stems, the LM26 epitope has a complementary pattern to that of the LM5 linear β-1,4-galactan epitope, which is detected only in companion cell walls. Mechanical probing of transverse sections of M x giganteus stems and leaves by atomic force microscopy indicates that phloem sieve element cell walls have a lower indentation modulus (indicative of higher elasticity) than companion cell walls. © 2018 The author(s). All Rights Reserved.

Biological forcing controls the chemistry of reef-building coral skeleton

NASA Astrophysics Data System (ADS)

Meibom, Anders; Mostefaoui, Smail; Cuif, Jean-Pierre; Dauphin, Yannicke; Houlbreque, Fanny; Dunbar, Robert; Constantz, Brent

2007-01-01

We present analyses of major elements C and Ca and trace elements N, S, Mg and Sr in a Porites sp. exoskeleton with a spatial resolution better than ˜150 nm. Trace element variations are evaluated directly against the ultra-structure of the skeleton and are ascribed to dynamic biological forcing. Individual growth layers in the bulk fibrous aragonite skeleton form on sub-daily timescales. Magnesium concentration variations are dramatically correlated with the growth layers, but are uncorrelated with Sr concentration variations. Observed (sub)seasonal relationships between water temperature and skeletal trace-element chemistry are secondary, mediated by sensitive biological processes to which classical thermodynamic formalism does not apply.

Cloning, expression, purification and preliminary crystallographic studies of the adenylate/uridylate-rich element-binding protein HuR complexed with its target RNA

PubMed Central

Iyaguchi, Daisuke; Yao, Min; Tanaka, Isao; Toyota, Eiko

2009-01-01

Adenylate/uridylate-rich elements (AREs), which are found in the 3′-untrans­lated region (UTR) of many mRNAs, influence the stability of cytoplasmic mRNA. HuR (human antigen R) binds to AREs and regulates various genes. In order to reveal the RNA-recognition mechanism of HuR protein, an RNA-binding region of human HuR containing two N-terminal RNA-recognition motif domains bound to an 11-­base RNA fragment has been crystallized. The crystals belonged to space group P212121, with unit-cell parameters a = 42.4, b = 44.9, c = 91.1 Å. X-­ray diffraction data were collected to 1.8 Å resolution. PMID:19255485

Biological toxicity of lanthanide elements on algae.

PubMed

Tai, Peidong; Zhao, Qing; Su, Dan; Li, Peijun; Stagnitti, Frank

2010-08-01

The biological toxicity of lanthanides on marine monocellular algae was investigated. The specific objective of this research was to establish the relationship between the abundance in the seawater of lanthanides and their biological toxicities on marine monocellular algae. The results showed that all single lanthanides had similar toxic effects on Skeletonema costatum. High concentrations of lanthanides (29.04+/-0.61 micromol L(-1)) resulted in 50% reduction in growth of algae compared to the controls (0 micromol L(-1)) after 96 h (96 h-EC50). The biological toxicity of 13 lanthanides on marine monocellular algae was unrelated with the abundance of different lanthanide elements in nature, and the "Harkins rule" was not appropriate for the lanthanides. A mixed solution that contained equivalent concentrations of each lanthanide element had the same inhibition effect on algae cells as each individual lanthanide element at the same total concentration. This phenomenon is unique compared to the groups of other elements in the periodic table. Hence, we speculate that the monocellular organisms might not be able to sufficiently differentiate between the almost chemically identical lanthanide elements. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Continued under-recognition of acute respiratory distress syndrome after the Berlin definition: what is the solution?

PubMed

Laffey, John G; Pham, Tài; Bellani, Giacomo

2017-02-01

Timely recognition of acute respiratory distress syndrome (ARDS) may allow for more prompt management and less exacerbation of lung injury. However, the absence of a diagnostic test for ARDS means that the diagnosis of ARDS requires clinician recognition in what is usually a complicated and evolving illness. We review data concerning the extent of recognition of ARDS in the era of the Berlin definition of ARDS. ARDS continues to be under-recognized - even in the era of the more recent 'Berlin' definition, and significant delay in its recognition is common. Factors contributing to under-recognition may include the complexity of ARDS biology, low specificity of the consensus (diagnostic) criteria, and concerns about reliable interpretation of the chest radiograph. Understandably, 'external' factors are also at play: ICU occupancy and higher patient to clinician ratio impair recognition of ARDS. Timely recognition of ARDS appears important, as it is associated with the use of higher PEEP, prone positioning and neuromuscular blockade which can lower mortality. Computer-aided decision tools seem diagnostically useful, and together with the integration of reliable biomarkers, may further enhance and speed recognition of this syndrome. Significant numbers of patients with ARDS are still unrecognized by clinicians in the era of the Berlin definition of ARDS, with potentially important consequences for patient management and outcome.

Applications of synchrotron μ-XRF to study the distribution of biologically important elements in different environmental matrices: a review.

PubMed

Majumdar, Sanghamitra; Peralta-Videa, Jose R; Castillo-Michel, Hiram; Hong, Jie; Rico, Cyren M; Gardea-Torresdey, Jorge L

2012-11-28

Environmental matrices including soils, sediments, and living organisms are reservoirs of several essential as well as non-essential elements. Accurate qualitative and quantitative information on the distribution and interaction of biologically significant elements is vital to understand the role of these elements in environmental and biological samples. Synchrotron micro-X-ray fluorescence (μ-SXRF) allows in situ mapping of biologically important elements at nanometer to sub-micrometer scale with high sensitivity, negligible sample damage and enable tuning of the incident energy as desired. Beamlines in the synchrotron facilities are rapidly increasing their analytical versatility in terms of focusing optics, detector technologies, incident energy, and sample environment. Although extremely competitive, it is now feasible to find stations offering complimentary techniques like micro-X-ray diffraction (μ-XRD) and micro-X-ray absorption spectroscopy (μ-XAS) that will allow a more complete characterization of complex matrices. This review includes the most recent literature on the emerging applications and challenges of μ-SXRF in studying the distribution of biologically important elements and manufactured nanoparticles in soils, sediments, plants, and microbes. The advantages of using μ-SXRF and complimentary techniques in contrast to conventional techniques used for the respective studies are discussed. Copyright © 2012 Elsevier B.V. All rights reserved.

Copper Capture in a Thioether-Functionalized Porous Polymer Applied to the Detection of Wilson’s Disease

PubMed Central

2016-01-01

Copper is an essential nutrient for life, but at the same time, hyperaccumulation of this redox-active metal in biological fluids and tissues is a hallmark of pathologies such as Wilson’s and Menkes diseases, various neurodegenerative diseases, and toxic environmental exposure. Diseases characterized by copper hyperaccumulation are currently challenging to identify due to costly diagnostic tools that involve extensive technical workup. Motivated to create simple yet highly selective and sensitive diagnostic tools, we have initiated a program to develop new materials that can enable monitoring of copper levels in biological fluid samples without complex and expensive instrumentation. Herein, we report the design, synthesis, and properties of PAF-1-SMe, a robust three-dimensional porous aromatic framework (PAF) densely functionalized with thioether groups for selective capture and concentration of copper from biofluids as well as aqueous samples. PAF-1-SMe exhibits a high selectivity for copper over other biologically relevant metals, with a saturation capacity reaching over 600 mg/g. Moreover, the combination of PAF-1-SMe as a material for capture and concentration of copper from biological samples with 8-hydroxyquinoline as a colorimetric indicator affords a method for identifying aberrant elevations of copper in urine samples from mice with Wilson’s disease and also tracing exogenously added copper in serum. This divide-and-conquer sensing strategy, where functional and robust porous materials serve as molecular recognition elements that can be used to capture and concentrate analytes in conjunction with molecular indicators for signal readouts, establishes a valuable starting point for the use of porous polymeric materials in noninvasive diagnostic applications. PMID:27285482

Grouping in object recognition: the role of a Gestalt law in letter identification.

PubMed

Pelli, Denis G; Majaj, Najib J; Raizman, Noah; Christian, Christopher J; Kim, Edward; Palomares, Melanie C

2009-02-01

The Gestalt psychologists reported a set of laws describing how vision groups elements to recognize objects. The Gestalt laws "prescribe for us what we are to recognize 'as one thing'" (Kohler, 1920). Were they right? Does object recognition involve grouping? Tests of the laws of grouping have been favourable, but mostly assessed only detection, not identification, of the compound object. The grouping of elements seen in the detection experiments with lattices and "snakes in the grass" is compelling, but falls far short of the vivid everyday experience of recognizing a familiar, meaningful, named thing, which mediates the ordinary identification of an object. Thus, after nearly a century, there is hardly any evidence that grouping plays a role in ordinary object recognition. To assess grouping in object recognition, we made letters out of grating patches and measured threshold contrast for identifying these letters in visual noise as a function of perturbation of grating orientation, phase, and offset. We define a new measure, "wiggle", to characterize the degree to which these various perturbations violate the Gestalt law of good continuation. We find that efficiency for letter identification is inversely proportional to wiggle and is wholly determined by wiggle, independent of how the wiggle was produced. Thus the effects of three different kinds of shape perturbation on letter identifiability are predicted by a single measure of goodness of continuation. This shows that letter identification obeys the Gestalt law of good continuation and may be the first confirmation of the original Gestalt claim that object recognition involves grouping.

Grouping in object recognition: The role of a Gestalt law in letter identification

PubMed Central

Pelli, Denis G.; Majaj, Najib J.; Raizman, Noah; Christian, Christopher J.; Kim, Edward; Palomares, Melanie C.

2009-01-01

The Gestalt psychologists reported a set of laws describing how vision groups elements to recognize objects. The Gestalt laws “prescribe for us what we are to recognize ‘as one thing’” (Köhler, 1920). Were they right? Does object recognition involve grouping? Tests of the laws of grouping have been favourable, but mostly assessed only detection, not identification, of the compound object. The grouping of elements seen in the detection experiments with lattices and “snakes in the grass” is compelling, but falls far short of the vivid everyday experience of recognizing a familiar, meaningful, named thing, which mediates the ordinary identification of an object. Thus, after nearly a century, there is hardly any evidence that grouping plays a role in ordinary object recognition. To assess grouping in object recognition, we made letters out of grating patches and measured threshold contrast for identifying these letters in visual noise as a function of perturbation of grating orientation, phase, and offset. We define a new measure, “wiggle”, to characterize the degree to which these various perturbations violate the Gestalt law of good continuation. We find that efficiency for letter identification is inversely proportional to wiggle and is wholly determined by wiggle, independent of how the wiggle was produced. Thus the effects of three different kinds of shape perturbation on letter identifiability are predicted by a single measure of goodness of continuation. This shows that letter identification obeys the Gestalt law of good continuation and may be the first confirmation of the original Gestalt claim that object recognition involves grouping. PMID:19424881

The role of the hippocampus in recognition memory.

PubMed

Bird, Chris M

2017-08-01

Many theories of declarative memory propose that it is supported by partially separable processes underpinned by different brain structures. The hippocampus plays a critical role in binding together item and contextual information together and processing the relationships between individual items. By contrast, the processing of individual items and their later recognition can be supported by extrahippocampal regions of the medial temporal lobes (MTL), particularly when recognition is based on feelings of familiarity without the retrieval of any associated information. These theories are domain-general in that "items" might be words, faces, objects, scenes, etc. However, there is mixed evidence that item recognition does not require the hippocampus, or that familiarity-based recognition can be supported by extrahippocampal regions. By contrast, there is compelling evidence that in humans, hippocampal damage does not affect recognition memory for unfamiliar faces, whilst recognition memory for several other stimulus classes is impaired. I propose that regions outside of the hippocampus can support recognition of unfamiliar faces because they are perceived as discrete items and have no prior conceptual associations. Conversely, extrahippocampal processes are inadequate for recognition of items which (a) have been previously experienced, (b) are conceptually meaningful, or (c) are perceived as being comprised of individual elements. This account reconciles findings from primate and human studies of recognition memory. Furthermore, it suggests that while the hippocampus is critical for binding and relational processing, these processes are required for item recognition memory in most situations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Incorporating Biological Mass Spectrometry into Undergraduate Teaching Labs, Part 2: Peptide Identification via Molecular Mass Determination

ERIC Educational Resources Information Center

Arnquist, Isaac J.; Beussman, Douglas J.

2009-01-01

Mass spectrometry has become a routine analytical tool in the undergraduate curriculum in the form of GC-MS. While relatively few undergraduate programs have incorporated biological mass spectrometry into their programs, the importance of these techniques, as demonstrated by their recognition with the 2002 Nobel Prize, will hopefully lead to…

Nature and Nurture by Definition Means Both: A Response to Males

ERIC Educational Resources Information Center

DeLisi, Matt; Wright, John Paul; Vaughn, Michael G.; Beaver, Kevin M.

2010-01-01

Recognition of the interplay between nature and nurture is decades old in fields such as psychiatry, but other fields in the social sciences continue to be hampered by the idea that social and biological variables compete for explanatory relevance. In a recent study of the adolescent brain and risk taking, Males critiqued biologically oriented…

Decoding Actions and Emotions in Deaf Children: Evidence from a Biological Motion Task

ERIC Educational Resources Information Center

Ludlow, Amanda Katherine; Heaton, Pamela; Deruelle, Christine

2013-01-01

This study aimed to explore the recognition of emotional and non-emotional biological movements in children with severe and profound deafness. Twenty-four deaf children, together with 24 control children matched on mental age and 24 control children matched on chronological age, were asked to identify a person's actions, subjective states,…

SRB-2: a promiscuous rainbow aptamer for live-cell RNA imaging.

PubMed

Sunbul, Murat; Jäschke, Andres

2018-06-21

The SRB-2 aptamer originally selected against sulforhodamine B is shown here to promiscuously bind to various dyes with different colors. Binding of SRB-2 to these dyes results in either fluorescence increase or decrease, making them attractive for fluorescence microscopy and biological assays. By systematically varying fluorophore structural elements and measuring dissociation constants, the principles of fluorophore recognition by SRB-2 were analyzed. The obtained structure-activity relationships allowed us to rationally design a novel, bright, orange fluorescent turn-on probe (TMR-DN) with low background fluorescence, enabling no-wash live-cell RNA imaging. This new probe improved the signal-to-background ratio of fluorescence images by one order of magnitude over best previously known probe for this aptamer. The utility of TMR-DN is demonstrated by imaging ribosomal and messenger RNAs, allowing the observation of distinct localization patterns in bacteria and mammalian cells. The SRB-2 / TMR-DN system is found to be orthogonal to the Spinach/DFHBI and MG/Malachite green aptamer/dye systems.

Biosynthesis of CdS nanoparticles: A fluorescent sensor for sulfate-reducing bacteria detection.

PubMed

Qi, Peng; Zhang, Dun; Zeng, Yan; Wan, Yi

2016-01-15

CdS nanoparticles were synthesized with an environmentally friendly method by taking advantage of the characteristic metabolic process of sulfate-reducing bacteria (SRB), and used as fluorescence labels for SRB detection. The presence of CdS nanoparticles was observed within and immediately surrounded bacterial cells, indicating CdS nanoparticles were synthesized both intracellularly and extracellularly. Moreover, fluorescent properties of microbial synthesized CdS nanoparticles were evaluated for SRB detection, and a linear relationship between fluorescence intensity and the logarithm of bacterial concentration was obtained in the range of from 1.0×10(2) to 1.0×10(7)cfu mL(-1). The proposed SRB detection method avoided the use of biological bio-recognition elements which are easy to lose their specific recognizing abilities, and the bacterial detection time was greatly shortened compared with the widely used MPN method which would take up to 15 days to accomplish the detection process. Copyright © 2015 Elsevier B.V. All rights reserved.

Exploring the impact of the side-chain length on peptide/RNA binding events.

PubMed

Sbicca, Lola; González, Alejandro López; Gresika, Alexandra; Di Giorgio, Audrey; Closa, Jordi Teixido; Tejedor, Roger Estrada; Andréola, Marie-Line; Azoulay, Stéphane; Patino, Nadia

2017-07-19

The impact of the amino-acid side-chain length on peptide-RNA binding events has been investigated using HIV-1 Tat derived peptides as ligands and the HIV-1 TAR RNA element as an RNA model. Our studies demonstrate that increasing the length of all peptide side-chains improves unexpectedly the binding affinity (K D ) but reduces the degree of compactness of the peptide-RNA complex. Overall, the side-chain length appears to modulate in an unpredictable way the ability of the peptide to compete with the cognate TAR RNA partner. Beyond the establishment of non-intuitive fundamental relationships, our results open up new perspectives in the design of effective RNA ligand competitors, since a large number of them have already been identified but few studies report on the modulation of the biological activity by modifying in the same way the length of all chains connecting RNA recognition motives to the central scaffold of a ligand.

Dissecting ant recognition systems in the age of genomics.

PubMed

Tsutsui, Neil D

2013-01-01

Hamilton is probably best known for his seminal work demonstrating the role of kin selection in social evolution. His work made it clear that, for individuals to direct their altruistic behaviours towards appropriate recipients (kin), mechanisms must exist for kin recognition. In the social insects, colonies are typically comprised of kin, and colony recognition cues are used as proxies for kinship cues. Recent years have brought rapid advances in our understanding of the genetic and molecular mechanisms that are used for this process. Here, I review some of the most notable advances, particularly the contributions from recent ant genome sequences and molecular biology.

Ligation site in proteins recognized in silico

PubMed Central

Brylinski, Michal; Konieczny, Leszek; Roterman, Irena

2006-01-01

Recognition of a ligation site in a protein molecule is important for identifying its biological activity. The model for in silico recognition of ligation sites in proteins is presented. The idealized hydrophobic core stabilizing protein structure is represented by a three-dimensional Gaussian function. The experimentally observed distribution of hydrophobicity compared with the theoretical distribution reveals differences. The area of high differences indicates the ligation site. Availability http://bioinformatics.cm-uj.krakow.pl/activesite PMID:17597871

Foundations for a syntatic pattern recognition system for genomic DNA sequences

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

Searles, D.B.

1993-03-01

The goal of the proposed work is the creation of a software system that will perform sophisticated pattern recognition and related functions at a level of abstraction and with expressive power beyond current general-purpose pattern-matching systems for biological sequences; and with a more uniform language, environment, and graphical user interface, and with greater flexibility, extensibility, embeddability, and ability to incorporate other algorithms, than current special-purpose analytic software.

Evaluating the developmental trajectory of the episodic buffer component of working memory and its relation to word recognition in children.

PubMed

Wang, Shinmin; Allen, Richard J; Lee, Jun Ren; Hsieh, Chia-En

2015-05-01

The creation of temporary bound representation of information from different sources is one of the key abilities attributed to the episodic buffer component of working memory. Whereas the role of working memory in word learning has received substantial attention, very little is known about the link between the development of word recognition skills and the ability to bind information in the episodic buffer of working memory and how it may develop with age. This study examined the performance of Grade 2 children (8 years old), Grade 3 children (9 years old), and young adults on a task designed to measure their ability to bind visual and auditory-verbal information in working memory. Children's performance on this task significantly correlated with their word recognition skills even when chronological age, memory for individual elements, and other possible reading-related factors were taken into account. In addition, clear developmental trajectories were observed, with improvements in the ability to hold temporary bound information in working memory between Grades 2 and 3, and between the child and adult groups, that were independent from memory for the individual elements. These findings suggest that the capacity to temporarily bind novel auditory-verbal information to visual form in working memory is linked to the development of word recognition in children and improves with age. Copyright © 2015 Elsevier Inc. All rights reserved.

Temporal lobe structures and facial emotion recognition in schizophrenia patients and nonpsychotic relatives.

PubMed

Goghari, Vina M; Macdonald, Angus W; Sponheim, Scott R

2011-11-01

Temporal lobe abnormalities and emotion recognition deficits are prominent features of schizophrenia and appear related to the diathesis of the disorder. This study investigated whether temporal lobe structural abnormalities were associated with facial emotion recognition deficits in schizophrenia and related to genetic liability for the disorder. Twenty-seven schizophrenia patients, 23 biological family members, and 36 controls participated. Several temporal lobe regions (fusiform, superior temporal, middle temporal, amygdala, and hippocampus) previously associated with face recognition in normative samples and found to be abnormal in schizophrenia were evaluated using volumetric analyses. Participants completed a facial emotion recognition task and an age recognition control task under time-limited and self-paced conditions. Temporal lobe volumes were tested for associations with task performance. Group status explained 23% of the variance in temporal lobe volume. Left fusiform gray matter volume was decreased by 11% in patients and 7% in relatives compared with controls. Schizophrenia patients additionally exhibited smaller hippocampal and middle temporal volumes. Patients were unable to improve facial emotion recognition performance with unlimited time to make a judgment but were able to improve age recognition performance. Patients additionally showed a relationship between reduced temporal lobe gray matter and poor facial emotion recognition. For the middle temporal lobe region, the relationship between greater volume and better task performance was specific to facial emotion recognition and not age recognition. Because schizophrenia patients exhibited a specific deficit in emotion recognition not attributable to a generalized impairment in face perception, impaired emotion recognition may serve as a target for interventions.

Handwritten-word spotting using biologically inspired features.

PubMed

van der Zant, Tijn; Schomaker, Lambert; Haak, Koen

2008-11-01

For quick access to new handwritten collections, current handwriting recognition methods are too cumbersome. They cannot deal with the lack of labeled data and would require extensive laboratory training for each individual script, style, language and collection. We propose a biologically inspired whole-word recognition method which is used to incrementally elicit word labels in a live, web-based annotation system, named Monk. Since human labor should be minimized given the massive amount of image data, it becomes important to rely on robust perceptual mechanisms in the machine. Recent computational models of the neuro-physiology of vision are applied to isolated word classification. A primate cortex-like mechanism allows to classify text-images that have a low frequency of occurrence. Typically these images are the most difficult to retrieve and often contain named entities and are regarded as the most important to people. Usually standard pattern-recognition technology cannot deal with these text-images if there are not enough labeled instances. The results of this retrieval system are compared to normalized word-image matching and appear to be very promising.

Biomimetic Strategies for Sensing Biological Species

PubMed Central

Hussain, Munawar; Wackerlig, Judith; Lieberzeit, Peter A.

2013-01-01

The starting point of modern biosensing was the application of actual biological species for recognition. Increasing understanding of the principles underlying such recognition (and biofunctionality in general), however, has triggered a dynamic field in chemistry and materials sciences that aims at joining the best of two worlds by combining concepts derived from nature with the processability of manmade materials, e.g., sensitivity and ruggedness. This review covers different biomimetic strategies leading to highly selective (bio)chemical sensors: the first section covers molecularly imprinted polymers (MIP) that attempt to generate a fully artificial, macromolecular mold of a species in order to detect it selectively. A different strategy comprises of devising polymer coatings to change the biocompatibility of surfaces that can also be used to immobilized natural receptors/ligands and thus stabilize them. Rationally speaking, this leads to self-assembled monolayers closely resembling cell membranes, sometimes also including bioreceptors. Finally, this review will highlight some approaches to generate artificial analogs of natural recognition materials and biomimetic approaches in nanotechnology. It mainly focuses on the literature published since 2005. PMID:25587400

Entity recognition in the biomedical domain using a hybrid approach.

PubMed

Basaldella, Marco; Furrer, Lenz; Tasso, Carlo; Rinaldi, Fabio

2017-11-09

This article describes a high-recall, high-precision approach for the extraction of biomedical entities from scientific articles. The approach uses a two-stage pipeline, combining a dictionary-based entity recognizer with a machine-learning classifier. First, the OGER entity recognizer, which has a bias towards high recall, annotates the terms that appear in selected domain ontologies. Subsequently, the Distiller framework uses this information as a feature for a machine learning algorithm to select the relevant entities only. For this step, we compare two different supervised machine-learning algorithms: Conditional Random Fields and Neural Networks. In an in-domain evaluation using the CRAFT corpus, we test the performance of the combined systems when recognizing chemicals, cell types, cellular components, biological processes, molecular functions, organisms, proteins, and biological sequences. Our best system combines dictionary-based candidate generation with Neural-Network-based filtering. It achieves an overall precision of 86% at a recall of 60% on the named entity recognition task, and a precision of 51% at a recall of 49% on the concept recognition task. These results are to our knowledge the best reported so far in this particular task.

Atom-scale depth localization of biologically important chemical elements in molecular layers.

PubMed

Schneck, Emanuel; Scoppola, Ernesto; Drnec, Jakub; Mocuta, Cristian; Felici, Roberto; Novikov, Dmitri; Fragneto, Giovanna; Daillant, Jean

2016-08-23

In nature, biomolecules are often organized as functional thin layers in interfacial architectures, the most prominent examples being biological membranes. Biomolecular layers play also important roles in context with biotechnological surfaces, for instance, when they are the result of adsorption processes. For the understanding of many biological or biotechnologically relevant phenomena, detailed structural insight into the involved biomolecular layers is required. Here, we use standing-wave X-ray fluorescence (SWXF) to localize chemical elements in solid-supported lipid and protein layers with near-Ångstrom precision. The technique complements traditional specular reflectometry experiments that merely yield the layers' global density profiles. While earlier work mostly focused on relatively heavy elements, typically metal ions, we show that it is also possible to determine the position of the comparatively light elements S and P, which are found in the most abundant classes of biomolecules and are therefore particularly important. With that, we overcome the need of artificial heavy atom labels, the main obstacle to a broader application of high-resolution SWXF in the fields of biology and soft matter. This work may thus constitute the basis for the label-free, element-specific structural investigation of complex biomolecular layers and biological surfaces.

Atom-scale depth localization of biologically important chemical elements in molecular layers

PubMed Central

Schneck, Emanuel; Scoppola, Ernesto; Drnec, Jakub; Mocuta, Cristian; Felici, Roberto; Novikov, Dmitri; Fragneto, Giovanna; Daillant, Jean

2016-01-01

In nature, biomolecules are often organized as functional thin layers in interfacial architectures, the most prominent examples being biological membranes. Biomolecular layers play also important roles in context with biotechnological surfaces, for instance, when they are the result of adsorption processes. For the understanding of many biological or biotechnologically relevant phenomena, detailed structural insight into the involved biomolecular layers is required. Here, we use standing-wave X-ray fluorescence (SWXF) to localize chemical elements in solid-supported lipid and protein layers with near-Ångstrom precision. The technique complements traditional specular reflectometry experiments that merely yield the layers’ global density profiles. While earlier work mostly focused on relatively heavy elements, typically metal ions, we show that it is also possible to determine the position of the comparatively light elements S and P, which are found in the most abundant classes of biomolecules and are therefore particularly important. With that, we overcome the need of artificial heavy atom labels, the main obstacle to a broader application of high-resolution SWXF in the fields of biology and soft matter. This work may thus constitute the basis for the label-free, element-specific structural investigation of complex biomolecular layers and biological surfaces. PMID:27503887

Environmental Light and Its Relationship with Electromagnetic Resonances of Biomolecular Interactions, as Predicted by the Resonant Recognition Model.

PubMed

Cosic, Irena; Cosic, Drasko; Lazar, Katarina

2016-06-29

The meaning and influence of light to biomolecular interactions, and consequently to health, has been analyzed using the Resonant Recognition Model (RRM). The RRM proposes that biological processes/interactions are based on electromagnetic resonances between interacting biomolecules at specific electromagnetic frequencies within the infra-red, visible and ultra-violet frequency ranges, where each interaction can be identified by the certain frequency critical for resonant activation of specific biological activities of proteins and DNA. We found that: (1) the various biological interactions could be grouped according to their resonant frequency into super families of these functions, enabling simpler analyses of these interactions and consequently analyses of influence of electromagnetic frequencies to health; (2) the RRM spectrum of all analyzed biological functions/interactions is the same as the spectrum of the sun light on the Earth, which is in accordance with fact that life is sustained by the sun light; (3) the water is transparent to RRM frequencies, enabling proteins and DNA to interact without loss of energy; (4) the spectrum of some artificial sources of light, as opposed to the sun light, do not cover the whole RRM spectrum, causing concerns for disturbance to some biological functions and consequently we speculate that it can influence health.

Environmental Light and Its Relationship with Electromagnetic Resonances of Biomolecular Interactions, as Predicted by the Resonant Recognition Model

PubMed Central

Cosic, Irena; Cosic, Drasko; Lazar, Katarina

2016-01-01

The meaning and influence of light to biomolecular interactions, and consequently to health, has been analyzed using the Resonant Recognition Model (RRM). The RRM proposes that biological processes/interactions are based on electromagnetic resonances between interacting biomolecules at specific electromagnetic frequencies within the infra-red, visible and ultra-violet frequency ranges, where each interaction can be identified by the certain frequency critical for resonant activation of specific biological activities of proteins and DNA. We found that: (1) the various biological interactions could be grouped according to their resonant frequency into super families of these functions, enabling simpler analyses of these interactions and consequently analyses of influence of electromagnetic frequencies to health; (2) the RRM spectrum of all analyzed biological functions/interactions is the same as the spectrum of the sun light on the Earth, which is in accordance with fact that life is sustained by the sun light; (3) the water is transparent to RRM frequencies, enabling proteins and DNA to interact without loss of energy; (4) the spectrum of some artificial sources of light, as opposed to the sun light, do not cover the whole RRM spectrum, causing concerns for disturbance to some biological functions and consequently we speculate that it can influence health. PMID:27367714

Imaging and elemental mapping of biological specimens with a dual-EDS dedicated scanning transmission electron microscope

PubMed Central

Wu, J.S.; Kim, A. M.; Bleher, R.; Myers, B.D.; Marvin, R. G.; Inada, H.; Nakamura, K.; Zhang, X.F.; Roth, E.; Li, S.Y.; Woodruff, T. K.; O'Halloran, T. V.; Dravid, Vinayak P.

2013-01-01

A dedicated analytical scanning transmission electron microscope (STEM) with dual energy dispersive spectroscopy (EDS) detectors has been designed for complementary high performance imaging as well as high sensitivity elemental analysis and mapping of biological structures. The performance of this new design, based on a Hitachi HD-2300A model, was evaluated using a variety of biological specimens. With three imaging detectors, both the surface and internal structure of cells can be examined simultaneously. The whole-cell elemental mapping, especially of heavier metal species that have low cross-section for electron energy loss spectroscopy (EELS), can be faithfully obtained. Optimization of STEM imaging conditions is applied to thick sections as well as thin sections of biological cells under low-dose conditions at room- and cryogenic temperatures. Such multimodal capabilities applied to soft/biological structures usher a new era for analytical studies in biological systems. PMID:23500508

DNA recognition by peptide nucleic acid-modified PCFs: from models to real samples

NASA Astrophysics Data System (ADS)

Selleri, S.; Coscelli, E.; Poli, F.; Passaro, D.; Cucinotta, A.; Lantano, C.; Corradini, R.; Marchelli, R.

2010-04-01

The increased concern, emerged in the last few years, on food products safety has stimulated the research on new techniques for traceability of raw food materials. DNA analysis is one of the most powerful tools for the certification of food quality, and it is presently performed through the polymerase chain reaction technique. Photonic crystal fibers, due to the presence of an array of air holes running along their length, can be exploited for performing DNA recognition by derivatizing hole surfaces and checking hybridization of complementary nucledotide chains in the sample. In this paper the application of a suspended core photonic crystal fiber in the recognition of DNA sequences is discussed. The fiber is characterized in terms of electromagnetic properties by means of a full-vector modal solver based on the finite element method. Then, the performances of the fiber in the recognition of mall synthetic oligonucleotides are discussed, together with a test of the possibility to extend this recognition to samples of DNA of applicative interest, such as olive leaves.

Recycling microcavity optical biosensors.

PubMed

Hunt, Heather K; Armani, Andrea M

2011-04-01

Optical biosensors have tremendous potential for commercial applications in medical diagnostics, environmental monitoring, and food safety evaluation. In these applications, sensor reuse is desirable to reduce costs. To achieve this, harsh, wet chemistry treatments are required to remove surface chemistry from the sensor, typically resulting in reduced sensor performance and increased noise due to recognition moiety and optical transducer degradation. In the present work, we suggest an alternative, dry-chemistry method, based on O₂ plasma treatment. This approach is compatible with typical fabrication of substrate-based optical transducers. This treatment completely removes the recognition moiety, allowing the transducer surface to be refreshed with new recognition elements and thus enabling the sensor to be recycled.

Bringing an Ecological Perspective to the Study of Aging and Recognition of Emotional Facial Expressions: Past, Current, and Future Methods

PubMed Central

Isaacowitz, Derek M.; Stanley, Jennifer Tehan

2011-01-01

Older adults perform worse on traditional tests of emotion recognition accuracy than do young adults. In this paper, we review descriptive research to date on age differences in emotion recognition from facial expressions, as well as the primary theoretical frameworks that have been offered to explain these patterns. We propose that this is an area of inquiry that would benefit from an ecological approach in which contextual elements are more explicitly considered and reflected in experimental methods. Use of dynamic displays and examination of specific cues to accuracy, for example, may reveal more nuanced age-related patterns and may suggest heretofore unexplored underlying mechanisms. PMID:22125354

Mechanisms underlying sexual and affiliative behaviors of mice: relation to generalized CNS arousal

PubMed Central

Shelley, Deborah N.; Choleris, Elena; Kavaliers, Martin

2006-01-01

The field of social neuroscience has grown dramatically in recent years and certain social responses have become amenable to mechanistic investigations. Toward that end, there has been remarkable progress in determining mechanisms for a simple sexual behavior, lordosis behavior. This work has proven that specific hormone-dependent biochemical reactions in specific parts of the mammalian brain regulate a biologically important behavior. On one hand, this sex behavior depends on underlying mechanisms of CNS arousal. On the other hand, it serves as a prototypical social behavior. The same sex hormones and the genes that encode their receptors as are involved in lordosis, also affect social recognition. Here we review evidence for a micronet of genes promoting social recognition in mice and discuss their biological roles. PMID:18985112

Hierarchical biointerfaces assembled by leukocyte-inspired particles for specifically recognizing cancer cells.

PubMed

Meng, Jingxin; Liu, Hongliang; Liu, Xueli; Yang, Gao; Zhang, Pengchao; Wang, Shutao; Jiang, Lei

2014-09-24

By mimicking certain biochemical and physical attributes of biological cells, bio-inspired particles have attracted great attention for potential biomedical applications based on cell-like biological functions. Inspired by leukocytes, hierarchical biointerfaces are designed and prepared based on specific molecules-modified leukocyte-inspired particles. These biointerfaces can efficiently recognize cancer cells from whole blood samples through the synergistic effect of molecular recognition and topographical interaction. Compared to flat, mono-micro or nano-biointerfaces, these micro/nano hierarchical biointerfaces are better able to promote specific recognition interactions, resulting in an enhanced cell-capture efficiency. It is anticipated that this study may provide promising guidance to develop new bio-inspired hierarchical biointerfaces for biomedical applications. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Rice MEL2, the RNA recognition motif (RRM) protein, binds in vitro to meiosis-expressed genes containing U-rich RNA consensus sequences in the 3'-UTR.

PubMed

Miyazaki, Saori; Sato, Yutaka; Asano, Tomoya; Nagamura, Yoshiaki; Nonomura, Ken-Ichi

2015-10-01

Post-transcriptional gene regulation by RNA recognition motif (RRM) proteins through binding to cis-elements in the 3'-untranslated region (3'-UTR) is widely used in eukaryotes to complete various biological processes. Rice MEIOSIS ARRESTED AT LEPTOTENE2 (MEL2) is the RRM protein that functions in the transition to meiosis in proper timing. The MEL2 RRM preferentially associated with the U-rich RNA consensus, UUAGUU[U/A][U/G][A/U/G]U, dependently on sequences and proportionally to MEL2 protein amounts in vitro. The consensus sequences were located in the putative looped structures of the RNA ligand. A genome-wide survey revealed a tendency of MEL2-binding consensus appearing in 3'-UTR of rice genes. Of 249 genes that conserved the consensus in their 3'-UTR, 13 genes spatiotemporally co-expressed with MEL2 in meiotic flowers, and included several genes whose function was supposed in meiosis; such as Replication protein A and OsMADS3. The proteome analysis revealed that the amounts of small ubiquitin-related modifier-like protein and eukaryotic translation initiation factor3-like protein were dramatically altered in mel2 mutant anthers. Taken together with transcriptome and gene ontology results, we propose that the rice MEL2 is involved in the translational regulation of key meiotic genes on 3'-UTRs to achieve the faithful transition of germ cells to meiosis.

Vehicle license plate recognition based on geometry restraints and multi-feature decision

NASA Astrophysics Data System (ADS)

Wu, Jianwei; Wang, Zongyue

2005-10-01

Vehicle license plate (VLP) recognition is of great importance to many traffic applications. Though researchers have paid much attention to VLP recognition there has not been a fully operational VLP recognition system yet for many reasons. This paper discusses a valid and practical method for vehicle license plate recognition based on geometry restraints and multi-feature decision including statistical and structural features. In general, the VLP recognition includes the following steps: the location of VLP, character segmentation, and character recognition. This paper discusses the three steps in detail. The characters of VLP are always declining caused by many factors, which makes it more difficult to recognize the characters of VLP, therefore geometry restraints such as the general ratio of length and width, the adjacent edges being perpendicular are used for incline correction. Image Moment has been proved to be invariant to translation, rotation and scaling therefore image moment is used as one feature for character recognition. Stroke is the basic element for writing and hence taking it as a feature is helpful to character recognition. Finally we take the image moment, the strokes and the numbers of each stroke for each character image and some other structural features and statistical features as the multi-feature to match each character image with sample character images so that each character image can be recognized by BP neural net. The proposed method combines statistical and structural features for VLP recognition, and the result shows its validity and efficiency.

Call recognition and individual identification of fish vocalizations based on automatic speech recognition: An example with the Lusitanian toadfish.

PubMed

Vieira, Manuel; Fonseca, Paulo J; Amorim, M Clara P; Teixeira, Carlos J C

2015-12-01

The study of acoustic communication in animals often requires not only the recognition of species specific acoustic signals but also the identification of individual subjects, all in a complex acoustic background. Moreover, when very long recordings are to be analyzed, automatic recognition and identification processes are invaluable tools to extract the relevant biological information. A pattern recognition methodology based on hidden Markov models is presented inspired by successful results obtained in the most widely known and complex acoustical communication signal: human speech. This methodology was applied here for the first time to the detection and recognition of fish acoustic signals, specifically in a stream of round-the-clock recordings of Lusitanian toadfish (Halobatrachus didactylus) in their natural estuarine habitat. The results show that this methodology is able not only to detect the mating sounds (boatwhistles) but also to identify individual male toadfish, reaching an identification rate of ca. 95%. Moreover this method also proved to be a powerful tool to assess signal durations in large data sets. However, the system failed in recognizing other sound types.

Multifarious Roles of Intrinsic Disorder in Proteins Illustrate Its Broad Impact on Plant Biology

PubMed Central

Sun, Xiaolin; Rikkerink, Erik H.A.; Jones, William T.; Uversky, Vladimir N.

2013-01-01

Intrinsically disordered proteins (IDPs) are highly abundant in eukaryotic proteomes. Plant IDPs play critical roles in plant biology and often act as integrators of signals from multiple plant regulatory and environmental inputs. Binding promiscuity and plasticity allow IDPs to interact with multiple partners in protein interaction networks and provide important functional advantages in molecular recognition through transient protein–protein interactions. Short interaction-prone segments within IDPs, termed molecular recognition features, represent potential binding sites that can undergo disorder-to-order transition upon binding to their partners. In this review, we summarize the evidence for the importance of IDPs in plant biology and evaluate the functions associated with intrinsic disorder in five different types of plant protein families experimentally confirmed as IDPs. Functional studies of these proteins illustrate the broad impact of disorder on many areas of plant biology, including abiotic stress, transcriptional regulation, light perception, and development. Based on the roles of disorder in the protein–protein interactions, we propose various modes of action for plant IDPs that may provide insight for future experimental approaches aimed at understanding the molecular basis of protein function within important plant pathways. PMID:23362206

A Critical Review on Clinical Application of Separation Techniques for Selective Recognition of Uracil and 5-Fluorouracil.

PubMed

Pandey, Khushaboo; Dubey, Rama Shankar; Prasad, Bhim Bali

2016-03-01

The most important objectives that are frequently found in bio-analytical chemistry involve applying tools to relevant medical/biological problems and refining these applications. Developing a reliable sample preparation step, for the medical and biological fields is another primary objective in analytical chemistry, in order to extract and isolate the analytes of interest from complex biological matrices. Since, main inborn errors of metabolism (IEM) diagnosable through uracil analysis and the therapeutic monitoring of toxic 5-fluoruracil (an important anti-cancerous drug) in dihydropyrimidine dehydrogenase deficient patients, require an ultra-sensitive, reproducible, selective, and accurate analytical techniques for their measurements. Therefore, keeping in view, the diagnostic value of uracil and 5-fluoruracil measurements, this article refines several analytical techniques involved in selective recognition and quantification of uracil and 5-fluoruracil from biological and pharmaceutical samples. The prospective study revealed that implementation of molecularly imprinted polymer as a solid-phase material for sample preparation and preconcentration of uracil and 5-fluoruracil had proven to be effective as it could obviates problems related to tedious separation techniques, owing to protein binding and drastic interferences, from the complex matrices in real samples such as blood plasma, serum samples.

Single-Stranded DNA Aptamers against Pathogens and Toxins: Identification and Biosensing Applications

PubMed Central

Hong, Ka Lok

2015-01-01

Molecular recognition elements (MREs) can be short sequences of single-stranded DNA, RNA, small peptides, or antibody fragments. They can bind to user-defined targets with high affinity and specificity. There has been an increasing interest in the identification and application of nucleic acid molecular recognition elements, commonly known as aptamers, since they were first described in 1990 by the Gold and Szostak laboratories. A large number of target specific nucleic acids MREs and their applications are currently in the literature. This review first describes the general methodologies used in identifying single-stranded DNA (ssDNA) aptamers. It then summarizes advancements in the identification and biosensing application of ssDNA aptamers specific for bacteria, viruses, their associated molecules, and selected chemical toxins. Lastly, an overview of the basic principles of ssDNA aptamer-based biosensors is discussed. PMID:26199940

Moving through the Stressed Genome: Emerging Regulatory Roles for Transposons in Plant Stress Response.

PubMed

Negi, Pooja; Rai, Archana N; Suprasanna, Penna

2016-01-01

The recognition of a positive correlation between organism genome size with its transposable element (TE) content, represents a key discovery of the field of genome biology. Considerable evidence accumulated since then suggests the involvement of TEs in genome structure, evolution and function. The global genome reorganization brought about by transposon activity might play an adaptive/regulatory role in the host response to environmental challenges, reminiscent of McClintock's original 'Controlling Element' hypothesis. This regulatory aspect of TEs is also garnering support in light of the recent evidences, which project TEs as "distributed genomic control modules." According to this view, TEs are capable of actively reprogramming host genes circuits and ultimately fine-tuning the host response to specific environmental stimuli. Moreover, the stress-induced changes in epigenetic status of TE activity may allow TEs to propagate their stress responsive elements to host genes; the resulting genome fluidity can permit phenotypic plasticity and adaptation to stress. Given their predominating presence in the plant genomes, nested organization in the genic regions and potential regulatory role in stress response, TEs hold unexplored potential for crop improvement programs. This review intends to present the current information about the roles played by TEs in plant genome organization, evolution, and function and highlight the regulatory mechanisms in plant stress responses. We will also briefly discuss the connection between TE activity, host epigenetic response and phenotypic plasticity as a critical link for traversing the translational bridge from a purely basic study of TEs, to the applied field of stress adaptation and crop improvement.

The Review of Nuclear Microscopy Techniques: An Approach for Nondestructive Trace Elemental Analysis and Mapping of Biological Materials.

PubMed

Mulware, Stephen Juma

2015-01-01

The properties of many biological materials often depend on the spatial distribution and concentration of the trace elements present in a matrix. Scientists have over the years tried various techniques including classical physical and chemical analyzing techniques each with relative level of accuracy. However, with the development of spatially sensitive submicron beams, the nuclear microprobe techniques using focused proton beams for the elemental analysis of biological materials have yielded significant success. In this paper, the basic principles of the commonly used microprobe techniques of STIM, RBS, and PIXE for trace elemental analysis are discussed. The details for sample preparation, the detection, and data collection and analysis are discussed. Finally, an application of the techniques to analysis of corn roots for elemental distribution and concentration is presented.

Origin of the biologically important elements.

PubMed

Trimble, V

1997-06-01

The chemical elements most widely distributed in terrestrial living creatures are the ones (apart from inert helium and neon) that are commonest in the Universe--hydrogen, oxygen, carbon, and nitrogen. A chemically different Universe would clearly have different biology, if any. We explore here the nuclear processes in stars, the early Universe, and elsewhere that have produced these common elements, and, while we are at it, also encounter the production of lithium, gold, uranium, and other elements of sociological, if not biological, importance. The relevant processes are, for the most part, well understood. Much less well understood is the overall history of chemical evolution of the Galaxy, from pure hydrogen and helium to the mix of elements we see today. One implication is that we cannot do a very good job of estimating how many stars and which ones might be orbited by habitable planets.

Novel salicylic acid-oriented thiourea-type receptors as colorimetric chemosensor: Synthesis, characterizations and selective naked-eye recognition properties

NASA Astrophysics Data System (ADS)

Li, Shaowei; Cao, Xiufang; Chen, Changshui; Ke, Shaoyong

2012-10-01

Based on the salicylic acid backbone, three highly sensitive and selective colorimetric chemosensors with an acylthiourea binding unit have been designed, synthesized and characterized. These chemosensors have been utilized for selective recognition of fluoride anions in dry DMSO solution by typical spectroscopic titration techniques. Furthermore, the obtained chemosensors AR1-3 have shown naked-eye sensitivity for detection of biologically important fluoride ion over other anions in solution.

Intelligent Scene Analysis and Recognition

DTIC Science & Technology

2010-03-30

Database, 1998, pp. 42–51. [9] I. Biederman , Aspects and extension of a theory of human image understanding, Z. Pylyshyn, Ed. Ablex Publishing Corporation...geometry in the visual system,” Biological Cybernetics, vol. 55, no. 6, pp. 367–375, 1987 . [30] W. T. Freeman and E. H. Adelson, “The design and use of...Computer Vision and Pattern Recognition, 2009, pp. 1980– 1987 . [47] M. Leordeanu and M. Hebert, “A spectral technique for correspondence problems using

Prototype Focal-Plane-Array Optoelectronic Image Processor

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi; Shaw, Timothy; Yu, Jeffrey

1995-01-01

Prototype very-large-scale integrated (VLSI) planar array of optoelectronic processing elements combines speed of optical input and output with flexibility of reconfiguration (programmability) of electronic processing medium. Basic concept of processor described in "Optical-Input, Optical-Output Morphological Processor" (NPO-18174). Performs binary operations on binary (black and white) images. Each processing element corresponds to one picture element of image and located at that picture element. Includes input-plane photodetector in form of parasitic phototransistor part of processing circuit. Output of each processing circuit used to modulate one picture element in output-plane liquid-crystal display device. Intended to implement morphological processing algorithms that transform image into set of features suitable for high-level processing; e.g., recognition.

The analytical calibration in (bio)imaging/mapping of the metallic elements in biological samples--definitions, nomenclature and strategies: state of the art.

PubMed

Jurowski, Kamil; Buszewski, Bogusław; Piekoszewski, Wojciech

2015-01-01

Nowadays, studies related to the distribution of metallic elements in biological samples are one of the most important issues. There are many articles dedicated to specific analytical atomic spectrometry techniques used for mapping/(bio)imaging the metallic elements in various kinds of biological samples. However, in such literature, there is a lack of articles dedicated to reviewing calibration strategies, and their problems, nomenclature, definitions, ways and methods used to obtain quantitative distribution maps. The aim of this article was to characterize the analytical calibration in the (bio)imaging/mapping of the metallic elements in biological samples including (1) nomenclature; (2) definitions, and (3) selected and sophisticated, examples of calibration strategies with analytical calibration procedures applied in the different analytical methods currently used to study an element's distribution in biological samples/materials such as LA ICP-MS, SIMS, EDS, XRF and others. The main emphasis was placed on the procedures and methodology of the analytical calibration strategy. Additionally, the aim of this work is to systematize the nomenclature for the calibration terms: analytical calibration, analytical calibration method, analytical calibration procedure and analytical calibration strategy. The authors also want to popularize the division of calibration methods that are different than those hitherto used. This article is the first work in literature that refers to and emphasizes many different and complex aspects of analytical calibration problems in studies related to (bio)imaging/mapping metallic elements in different kinds of biological samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Object Recognition and Localization: The Role of Tactile Sensors

PubMed Central

Aggarwal, Achint; Kirchner, Frank

2014-01-01

Tactile sensors, because of their intrinsic insensitivity to lighting conditions and water turbidity, provide promising opportunities for augmenting the capabilities of vision sensors in applications involving object recognition and localization. This paper presents two approaches for haptic object recognition and localization for ground and underwater environments. The first approach called Batch Ransac and Iterative Closest Point augmented Particle Filter (BRICPPF) is based on an innovative combination of particle filters, Iterative-Closest-Point algorithm, and a feature-based Random Sampling and Consensus (RANSAC) algorithm for database matching. It can handle a large database of 3D-objects of complex shapes and performs a complete six-degree-of-freedom localization of static objects. The algorithms are validated by experimentation in ground and underwater environments using real hardware. To our knowledge this is the first instance of haptic object recognition and localization in underwater environments. The second approach is biologically inspired, and provides a close integration between exploration and recognition. An edge following exploration strategy is developed that receives feedback from the current state of recognition. A recognition by parts approach is developed which uses the BRICPPF for object sub-part recognition. Object exploration is either directed to explore a part until it is successfully recognized, or is directed towards new parts to endorse the current recognition belief. This approach is validated by simulation experiments. PMID:24553087

"Multiple partial recognitions in dynamic equilibrium" in the binding sites of proteins form the molecular basis of promiscuous recognition of structurally diverse ligands.

PubMed

Kohda, Daisuke

2018-04-01

Promiscuous recognition of ligands by proteins is as important as strict recognition in numerous biological processes. In living cells, many short, linear amino acid motifs function as targeting signals in proteins to specify the final destination of the protein transport. In general, the target signal is defined by a consensus sequence containing wild-characters, and hence represented by diverse amino acid sequences. The classical lock-and-key or induced-fit/conformational selection mechanism may not cover all aspects of the promiscuous recognition. On the basis of our crystallographic and NMR studies on the mitochondrial Tom20 protein-presequence interaction, we proposed a new hypothetical mechanism based on "a rapid equilibrium of multiple states with partial recognitions". This dynamic, multiple recognition mode enables the Tom20 receptor to recognize diverse mitochondrial presequences with nearly equal affinities. The plant Tom20 is evolutionally unrelated to the animal Tom20 in our study, but is a functional homolog of the animal/fungal Tom20. NMR studies by another research group revealed that the presequence binding by the plant Tom20 was not fully explained by simple interaction modes, suggesting the presence of a similar dynamic, multiple recognition mode. Circumstantial evidence also suggested that similar dynamic mechanisms may be applicable to other promiscuous recognitions of signal peptides by the SRP54/Ffh and SecA proteins.

Trace elements at the intersection of marine biological and geochemical evolution

USGS Publications Warehouse

Robbins, Leslie J.; Lalonde, Stefan V.; Planavsky, Noah J.; Partin, Camille A.; Reinhard, Christopher T.; Kendall, Brian; Scott, Clinton T.; Hardisty, Dalton S.; Gill, Benjamin C.; Alessi, Daniel S.; Dupont, Christopher L.; Saito, Mak A.; Crowe, Sean A.; Poulton, Simon W.; Bekker, Andrey; Lyons, Timothy W.; Konhauser, Kurt O.

2016-01-01

Life requires a wide variety of bioessential trace elements to act as structural components and reactive centers in metalloenzymes. These requirements differ between organisms and have evolved over geological time, likely guided in some part by environmental conditions. Until recently, most of what was understood regarding trace element concentrations in the Precambrian oceans was inferred by extrapolation, geochemical modeling, and/or genomic studies. However, in the past decade, the increasing availability of trace element and isotopic data for sedimentary rocks of all ages has yielded new, and potentially more direct, insights into secular changes in seawater composition – and ultimately the evolution of the marine biosphere. Compiled records of many bioessential trace elements (including Ni, Mo, P, Zn, Co, Cr, Se, and I) provide new insight into how trace element abundance in Earth's ancient oceans may have been linked to biological evolution. Several of these trace elements display redox-sensitive behavior, while others are redox-sensitive but not bioessential (e.g., Cr, U). Their temporal trends in sedimentary archives provide useful constraints on changes in atmosphere-ocean redox conditions that are linked to biological evolution, for example, the activity of oxygen-producing, photosynthetic cyanobacteria. In this review, we summarize available Precambrian trace element proxy data, and discuss how temporal trends in the seawater concentrations of specific trace elements may be linked to the evolution of both simple and complex life. We also examine several biologically relevant and/or redox-sensitive trace elements that have yet to be fully examined in the sedimentary rock record (e.g., Cu, Cd, W) and suggest several directions for future studies.

Mobile element biology – new possibilities with high-throughput sequencing

PubMed Central

Xing, Jinchuan; Witherspoon, David J.; Jorde, Lynn B.

2014-01-01

Mobile elements compose more than half of the human genome, but until recently their large-scale detection was time-consuming and challenging. With the development of new high-throughput sequencing technologies, the complete spectrum of mobile element variation in humans can now be identified and analyzed. Thousands of new mobile element insertions have been discovered, yielding new insights into mobile element biology, evolution, and genomic variation. We review several high-throughput methods, with an emphasis on techniques that specifically target mobile element insertions in humans, and we highlight recent applications of these methods in evolutionary studies and in the analysis of somatic alterations in human cancers. PMID:23312846

In vitro selection of single-stranded DNA molecular recognition elements against S. aureus alpha toxin and sensitive detection in human serum.

PubMed

Hong, Ka L; Battistella, Luisa; Salva, Alysia D; Williams, Ryan M; Sooter, Letha J

2015-01-27

Alpha toxin is one of the major virulence factors secreted by Staphylococcus aureus, a bacterium that is responsible for a wide variety of infections in both community and hospital settings. Due to the prevalence of S. aureus related infections and the emergence of methicillin-resistant S. aureus, rapid and accurate diagnosis of S. aureus infections is crucial in benefiting patient health outcomes. In this study, a rigorous Systematic Evolution of Ligands by Exponential Enrichment (SELEX) variant previously developed by our laboratory was utilized to select a single-stranded DNA molecular recognition element (MRE) targeting alpha toxin with high affinity and specificity. At the end of the 12-round selection, the selected MRE had an equilibrium dissociation constant (Kd) of 93.7 ± 7.0 nM. Additionally, a modified sandwich enzyme-linked immunosorbent assay (ELISA) was developed by using the selected ssDNA MRE as the toxin-capturing element and a sensitive detection of 200 nM alpha toxin in undiluted human serum samples was achieved.

Effect of Total Quality Management on the Quality and Productivity of Human Resources

NASA Astrophysics Data System (ADS)

Siregar, I.; Nasution, A. A.; Sari, R. M.

2017-03-01

Human resources is the main factor in improving company performance not only in industrial products but also services. Therefore, all of the organization performers involved must work together to achieve product quality services expected by consumers. Educational institutions are the service industries which are educators and instructor involved in it. Quality of product and services produced depends on the education organization performers. This study did a survey of instructors in public and private universities in North Sumatra to obtain the factors that affect quality of human resources and productivity of human resources. Human resources quality is viewed by the elements of TQM. TQM elements that are discussed in this study are leadership, communication, training and education, support structure, measurement and reward and recognition. The results of this study showed a correlation numbers across the exogenous variables on endogenous variables relationships tend to be strong and be positive. In addition, elements of TQM are discussed except the support structure which has a direct influence on the quality of human resources. Variable leadership, reward and recognition and quality of human resources have a significant effect on productivity.

Biologically Inspired Model for Visual Cognition Achieving Unsupervised Episodic and Semantic Feature Learning.

PubMed

Qiao, Hong; Li, Yinlin; Li, Fengfu; Xi, Xuanyang; Wu, Wei

2016-10-01

Recently, many biologically inspired visual computational models have been proposed. The design of these models follows the related biological mechanisms and structures, and these models provide new solutions for visual recognition tasks. In this paper, based on the recent biological evidence, we propose a framework to mimic the active and dynamic learning and recognition process of the primate visual cortex. From principle point of view, the main contributions are that the framework can achieve unsupervised learning of episodic features (including key components and their spatial relations) and semantic features (semantic descriptions of the key components), which support higher level cognition of an object. From performance point of view, the advantages of the framework are as follows: 1) learning episodic features without supervision-for a class of objects without a prior knowledge, the key components, their spatial relations and cover regions can be learned automatically through a deep neural network (DNN); 2) learning semantic features based on episodic features-within the cover regions of the key components, the semantic geometrical values of these components can be computed based on contour detection; 3) forming the general knowledge of a class of objects-the general knowledge of a class of objects can be formed, mainly including the key components, their spatial relations and average semantic values, which is a concise description of the class; and 4) achieving higher level cognition and dynamic updating-for a test image, the model can achieve classification and subclass semantic descriptions. And the test samples with high confidence are selected to dynamically update the whole model. Experiments are conducted on face images, and a good performance is achieved in each layer of the DNN and the semantic description learning process. Furthermore, the model can be generalized to recognition tasks of other objects with learning ability.

Bacteriorhodopsin as a chemical and biological sensor

NASA Astrophysics Data System (ADS)

Heeg, Bauke; Needleman, Richard; Khizhnyak, Anatoliy; L'Esperance, Drew M.; Scott, Eddie; Markov, Vladimir B.; Trolinger, James D.

2003-08-01

Bacteriorhodopsin (bR) is a small protein containing the chromophore retinal, and resides in the membrane of the Halobacterium salinarium. When the retinal absorbs a photon, a cycle of structural changes is triggered resulting in a cross-membrane proton transfer, which is used to generate energy for the organism. Many studies have been conducted to elucidate the dynamical structure - optical property relations, and the overall mechanism of photo-induced proton transport in bR is now well understood. On the other hand, site selective mutagenesis allows engineering of the original ("wild-type") bR, such that the protein can be made sensitive to specific chemicals or biological structures that consequently induce changes in the proton-transport. As such, bR provides a unique molecular platform onto which various functional elements can be built: peptide receptors for molecular recognition of pathogens (e.g. viruses, cancer cells, spores, bacteria, bio-toxins), fluorescent tags (using the inherent optical transduction mechanism of bR), and chemical anchors for capturing target cells. In particular, the stability of bR in extreme environments (pH range of 1 - 11, temperatures up to 110 °C) allows for optical detection under a large range of environmental conditions. In this paper we present and discuss experimental data of several bR mutants and their potential as chemical and biological sensors. In particular, the optical changes associated with metal ligand binding are discussed for two mutants, 170C and 169C/96N, as well as the optical changes associated with streptavidin-coated beads bound to bR with strep II tags inserted in the E/F loop.

Quantification of 2D elemental distribution maps of intermediate-thick biological sections by low energy synchrotron μ-X-ray fluorescence spectrometry

NASA Astrophysics Data System (ADS)

Kump, P.; Vogel-Mikuš, K.

2018-05-01

Two fundamental-parameter (FP) based models for quantification of 2D elemental distribution maps of intermediate-thick biological samples by synchrotron low energy μ-X-ray fluorescence spectrometry (SR-μ-XRF) are presented and applied to the elemental analysis in experiments with monochromatic focused photon beam excitation at two low energy X-ray fluorescence beamlines—TwinMic, Elettra Sincrotrone Trieste, Italy, and ID21, ESRF, Grenoble, France. The models assume intermediate-thick biological samples composed of measured elements, the sources of the measurable spectral lines, and by the residual matrix, which affects the measured intensities through absorption. In the first model a fixed residual matrix of the sample is assumed, while in the second model the residual matrix is obtained by the iteration refinement of elemental concentrations and an adjusted residual matrix. The absorption of the incident focused beam in the biological sample at each scanned pixel position, determined from the output of a photodiode or a CCD camera, is applied as a control in the iteration procedure of quantification.

Switching of bacterial adhesion to a glycosylated surface by reversible reorientation of the carbohydrate ligand.

PubMed

Weber, Theresa; Chandrasekaran, Vijayanand; Stamer, Insa; Thygesen, Mikkel B; Terfort, Andreas; Lindhorst, Thisbe K

2014-12-22

The surface recognition in many biological systems is guided by the interaction of carbohydrate-specific proteins (lectins) with carbohydrate epitopes (ligands) located within the unordered glycoconjugate layer (glycocalyx) of cells. Thus, for recognition, the respective ligand has to reorient for a successful matching event. Herein, we present for the first time a model system, in which only the orientation of the ligand is altered in a controlled manner without changing the recognition quality of the ligand itself. The key for this orientational control is the embedding into an interfacial system and the use of a photoswitchable mechanical joint, such as azobenzene. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dealing with contaminated datasets: An approach to classifier training

NASA Astrophysics Data System (ADS)

Homenda, Wladyslaw; Jastrzebska, Agnieszka; Rybnik, Mariusz

2016-06-01

The paper presents a novel approach to classification reinforced with rejection mechanism. The method is based on a two-tier set of classifiers. First layer classifies elements, second layer separates native elements from foreign ones in each distinguished class. The key novelty presented here is rejection mechanism training scheme according to the philosophy "one-against-all-other-classes". Proposed method was tested in an empirical study of handwritten digits recognition.

Trace Elements in Ovaries: Measurement and Physiology.

PubMed

Ceko, Melanie J; O'Leary, Sean; Harris, Hugh H; Hummitzsch, Katja; Rodgers, Raymond J

2016-04-01

Traditionally, research in the field of trace element biology and human and animal health has largely depended on epidemiological methods to demonstrate involvement in biological processes. These studies were typically followed by trace element supplementation trials or attempts at identification of the biochemical pathways involved. With the discovery of biological molecules that contain the trace elements, such as matrix metalloproteinases containing zinc (Zn), cytochrome P450 enzymes containing iron (Fe), and selenoproteins containing selenium (Se), much of the current research focuses on these molecules, and, hence, only indirectly on trace elements themselves. This review focuses largely on two synchrotron-based x-ray techniques: X-ray absorption spectroscopy and x-ray fluorescence imaging that can be used to identify the in situ speciation and distribution of trace elements in tissues, using our recent studies of bovine ovaries, where the distribution of Fe, Se, Zn, and bromine were determined. It also discusses the value of other techniques, such as inductively coupled plasma mass spectrometry, used to garner information about the concentrations and elemental state of the trace elements. These applications to measure trace elemental distributions in bovine ovaries at high resolutions provide new insights into possible roles for trace elements in the ovary. © 2016 by the Society for the Study of Reproduction, Inc.

Specificity and multiplicity in the recognition of individuals: implications for the evolution of social behaviour.

PubMed

Wiley, R H

2013-02-01

Recognition of conspecifics occurs when individuals classify sets of conspecifics based on sensory input from them and associate these sets with different responses. Classification of conspecifics can vary in specificity (the number of individuals included in a set) and multiplicity (the number of sets differentiated). In other words, the information transmitted varies in complexity. Although recognition of conspecifics has been reported in a wide variety of organisms, few reports have addressed the specificity or multiplicity of this capability. This review discusses examples of these patterns, the mechanisms that can produce them, and the evolution of these mechanisms. Individual recognition is one end of a spectrum of specificity, and binary classification of conspecifics is one end of a spectrum of multiplicity. In some cases, recognition requires no more than simple forms of learning, such as habituation, yet results in individually specific recognition. In other cases, recognition of individuals involves complex associations of multiple cues with multiple previous experiences in particular contexts. Complex mechanisms for recognition are expected to evolve only when simpler mechanisms do not provide sufficient specificity and multiplicity to obtain the available advantages. In particular, the evolution of cooperation and deception is always promoted by specificity and multiplicity in recognition. Nevertheless, there is only one demonstration that recognition of specific individuals contributes to cooperation in animals other than primates. Human capacities for individual recognition probably have a central role in the evolution of complex forms of human cooperation and deception. Although relatively little studied, this capability probably rivals cognitive abilities for language. © 2012 The Author. Biological Reviews © 2012 Cambridge Philosophical Society.

Imaging and elemental mapping of biological specimens with a dual-EDS dedicated scanning transmission electron microscope.

PubMed

Wu, J S; Kim, A M; Bleher, R; Myers, B D; Marvin, R G; Inada, H; Nakamura, K; Zhang, X F; Roth, E; Li, S Y; Woodruff, T K; O'Halloran, T V; Dravid, Vinayak P

2013-05-01

A dedicated analytical scanning transmission electron microscope (STEM) with dual energy dispersive spectroscopy (EDS) detectors has been designed for complementary high performance imaging as well as high sensitivity elemental analysis and mapping of biological structures. The performance of this new design, based on a Hitachi HD-2300A model, was evaluated using a variety of biological specimens. With three imaging detectors, both the surface and internal structure of cells can be examined simultaneously. The whole-cell elemental mapping, especially of heavier metal species that have low cross-section for electron energy loss spectroscopy (EELS), can be faithfully obtained. Optimization of STEM imaging conditions is applied to thick sections as well as thin sections of biological cells under low-dose conditions at room and cryogenic temperatures. Such multimodal capabilities applied to soft/biological structures usher a new era for analytical studies in biological systems. Copyright © 2013 Elsevier B.V. All rights reserved.

Nucleobase recognition at alkaline pH and apparent pKa of single DNA bases immobilised within a biological nanopore.

PubMed

Franceschini, Lorenzo; Mikhailova, Ellina; Bayley, Hagan; Maglia, Giovanni

2012-02-01

The four DNA bases are recognized in immobilized DNA strands at high alkaline pH by nanopore current recordings. Ionic currents through the biological nanopores are also employed to measure the apparent pK(a) values of single nucleobases within the immobilised DNA strands. This journal is © The Royal Society of Chemistry 2012

Foundations for a syntatic pattern recognition system for genomic DNA sequences. [Annual] report, 1 December 1991--31 March 1993

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

Searles, D.B.

1993-03-01

The goal of the proposed work is the creation of a software system that will perform sophisticated pattern recognition and related functions at a level of abstraction and with expressive power beyond current general-purpose pattern-matching systems for biological sequences; and with a more uniform language, environment, and graphical user interface, and with greater flexibility, extensibility, embeddability, and ability to incorporate other algorithms, than current special-purpose analytic software.

Protein-protein interactions in the regulation of WRKY transcription factors.

PubMed

Chi, Yingjun; Yang, Yan; Zhou, Yuan; Zhou, Jie; Fan, Baofang; Yu, Jing-Quan; Chen, Zhixiang

2013-03-01

It has been almost 20 years since the first report of a WRKY transcription factor, SPF1, from sweet potato. Great progress has been made since then in establishing the diverse biological roles of WRKY transcription factors in plant growth, development, and responses to biotic and abiotic stress. Despite the functional diversity, almost all analyzed WRKY proteins recognize the TTGACC/T W-box sequences and, therefore, mechanisms other than mere recognition of the core W-box promoter elements are necessary to achieve the regulatory specificity of WRKY transcription factors. Research over the past several years has revealed that WRKY transcription factors physically interact with a wide range of proteins with roles in signaling, transcription, and chromatin remodeling. Studies of WRKY-interacting proteins have provided important insights into the regulation and mode of action of members of the important family of transcription factors. It has also emerged that the slightly varied WRKY domains and other protein motifs conserved within each of the seven WRKY subfamilies participate in protein-protein interactions and mediate complex functional interactions between WRKY proteins and between WRKY and other regulatory proteins in the modulation of important biological processes. In this review, we summarize studies of protein-protein interactions for WRKY transcription factors and discuss how the interacting partners contribute, at different levels, to the establishment of the complex regulatory and functional network of WRKY transcription factors.

Conformational and mechanical changes of DNA upon transcription factor binding detected by a QCM and transmission line model.

PubMed

de-Carvalho, Jorge; Rodrigues, Rogério M M; Tomé, Brigitte; Henriques, Sílvia F; Mira, Nuno P; Sá-Correia, Isabel; Ferreira, Guilherme N M

2014-04-21

A novel quartz crystal microbalance (QCM) analytical method is developed based on the transmission line model (TLM) algorithm to analyze the binding of transcription factors (TFs) to immobilized DNA oligoduplexes. The method is used to characterize the mechanical properties of biological films through the estimation of the film dynamic shear moduli, G and G, and the film thickness. Using the Saccharomyces cerevisiae transcription factor Haa1 (Haa1DBD) as a biological model two sensors were prepared by immobilizing DNA oligoduplexes, one containing the Haa1 recognition element (HRE(wt)) and another with a random sequence (HRE(neg)) used as a negative control. The immobilization of DNA oligoduplexes was followed in real time and we show that DNA strands initially adsorb with low or non-tilting, laying flat close to the surface, which then lift-off the surface leading to final film tilting angles of 62.9° and 46.7° for HRE(wt) and HRE(neg), respectively. Furthermore we show that the binding of Haa1DBD to HRE(wt) leads to a more ordered and compact film, and forces a 31.7° bending of the immobilized HRE(wt) oligoduplex. This work demonstrates the suitability of the QCM to monitor the specific binding of TFs to immobilized DNA sequences and provides an analytical methodology to study protein-DNA biophysics and kinetics.

Design and construction of a double inversion recombination switch for heritable sequential genetic memory.

PubMed

Ham, Timothy S; Lee, Sung K; Keasling, Jay D; Arkin, Adam P

2008-07-30

Inversion recombination elements present unique opportunities for computing and information encoding in biological systems. They provide distinct binary states that are encoded into the DNA sequence itself, allowing us to overcome limitations posed by other biological memory or logic gate systems. Further, it is in theory possible to create complex sequential logics by careful positioning of recombinase recognition sites in the sequence. In this work, we describe the design and synthesis of an inversion switch using the fim and hin inversion recombination systems to create a heritable sequential memory switch. We have integrated the two inversion systems in an overlapping manner, creating a switch that can have multiple states. The switch is capable of transitioning from state to state in a manner analogous to a finite state machine, while encoding the state information into DNA. This switch does not require protein expression to maintain its state, and "remembers" its state even upon cell death. We were able to demonstrate transition into three out of the five possible states showing the feasibility of such a switch. We demonstrate that a heritable memory system that encodes its state into DNA is possible, and that inversion recombination system could be a starting point for more complex memory circuits. Although the circuit did not fully behave as expected, we showed that a multi-state, temporal memory is achievable.

Design and Construction of a Double Inversion Recombination Switch for Heritable Sequential Genetic Memory

PubMed Central

Ham, Timothy S.; Lee, Sung K.; Keasling, Jay D.; Arkin, Adam P.

2008-01-01

Background Inversion recombination elements present unique opportunities for computing and information encoding in biological systems. They provide distinct binary states that are encoded into the DNA sequence itself, allowing us to overcome limitations posed by other biological memory or logic gate systems. Further, it is in theory possible to create complex sequential logics by careful positioning of recombinase recognition sites in the sequence. Methodology/Principal Findings In this work, we describe the design and synthesis of an inversion switch using the fim and hin inversion recombination systems to create a heritable sequential memory switch. We have integrated the two inversion systems in an overlapping manner, creating a switch that can have multiple states. The switch is capable of transitioning from state to state in a manner analogous to a finite state machine, while encoding the state information into DNA. This switch does not require protein expression to maintain its state, and “remembers” its state even upon cell death. We were able to demonstrate transition into three out of the five possible states showing the feasibility of such a switch. Conclusions/Significance We demonstrate that a heritable memory system that encodes its state into DNA is possible, and that inversion recombination system could be a starting point for more complex memory circuits. Although the circuit did not fully behave as expected, we showed that a multi-state, temporal memory is achievable. PMID:18665232

Design and interpretation of microRNA-reporter gene activity.

PubMed

Carroll, Adam P; Tooney, Paul A; Cairns, Murray J

2013-06-15

MicroRNAs (miRNAs) are small noncoding RNA molecules that act as sequence specificity guides to direct post-transcriptional gene silencing. In doing so, miRNAs regulate many critical developmental processes, including cellular proliferation, differentiation, migration, and apoptosis, as well as more specialized biological functions such as dendritic spine development and synaptogenesis. Interactions between miRNAs and their miRNA recognition elements occur via partial complementarity, rendering tremendous redundancy in targeting such that miRNAs are predicted to regulate 60% of the genome, with each miRNA estimated to regulate more than 200 genes. Because these predictions are prone to false positives and false negatives, there is an ever present need to provide material support to these assertions to firmly establish the biological function of specific miRNAs in both normal and pathophysiological contexts. Using schizophrenia-associated miR-181b as an example, we present detailed guidelines and novel insights for the rapid establishment of a streamlined miRNA-reporter gene assay and explore various design concepts for miRNA-reporter gene applications, including bidirectional miRNA modulation. In exemplifying this approach, we report seven novel miR-181b target sites for five schizophrenia candidate genes (DISC1, BDNF, ENKUR, GRIA1, and GRIK1) and dissect a number of vital concepts regarding future developments for miRNA-reporter gene assays and the interpretation of their results. Copyright © 2013 Elsevier Inc. All rights reserved.

Interactions between avidin and graphene for development of a biosensing platform.

PubMed

Macwan, Isaac; Khan, Md Daud Hossain; Aphale, Ashish; Singh, Shrishti; Liu, Juan; Hingorani, Manju; Patra, Prabir

2017-03-15

Fundamental understanding of interactions at the interface of biological molecules, such as proteins, and nanomaterials is crucial for developing various biocompatible hybrid materials and biosensing platforms. Biosensors comprising of graphene-based conductive nanomaterials offer the advantage of higher sensitivity and reliable diagnosis mainly due to their superior specific surface area and ballistic conductivity. Furthermore, conductive nanocomposite structures that immobilize proteins can synergize the properties of both transducers and molecular recognition elements improving the performance of the biosensing device. Here we report for the first time, using a combined molecular dynamics simulations and experimental approach, the interactions between avidin and graphene for the development of a sensing platform that can be used for the detection of biological macromolecules such as mismatch repair proteins through biotinylated DNA substrates. We find that the interactive forces between avidin and graphene are mainly hydrophobic, along with some van der Waals, electrostatic and hydrogen bonding interactions. Notably, the structure and function of the avidin molecule are largely preserved after its adsorption on the graphene surface. The MD results agree well with scanning electron microscopy (SEM) and electrochemical impedance spectroscopy (EIS) analysis of avidin immobilized on a graphenated polypyrrole (G-PPy) conductive nanocomposite confirming the adsorption of avidin on graphene nanoplatelets as observed from the Fourier-transform infrared spectroscopy (FTIR). Copyright © 2016 Elsevier B.V. All rights reserved.

Strategies of molecular imprinting-based fluorescence sensors for chemical and biological analysis.

PubMed

Yang, Qian; Li, Jinhua; Wang, Xiaoyan; Peng, Hailong; Xiong, Hua; Chen, Lingxin

2018-07-30

One pressing concern today is to construct sensors that can withstand various disturbances for highly selective and sensitive detecting trace analytes in complicated samples. Molecularly imprinted polymers (MIPs) with tailor-made binding sites are preferred to be recognition elements in sensors for effective targets detection, and fluorescence measurement assists in highly sensitive detection and user-friendly control. Accordingly, molecular imprinting-based fluorescence sensors (MI-FL sensors) have attracted great research interest in many fields such as chemical and biological analysis. Herein, we comprehensively review the recent advances in MI-FL sensors construction and applications, giving insights on sensing principles and signal transduction mechanisms, focusing on general construction strategies for intrinsically fluorescent or nonfluorescent analytes and improvement strategies in sensing performance, particularly in sensitivity. Construction strategies are well overviewed, mainly including the traditional indirect methods of competitive binding against pre-bound fluorescent indicators, employment of fluorescent functional monomers and embedding of fluorescence substances, and novel rational designs of hierarchical architecture (core-shell/hollow and mesoporous structures), post-imprinting modification, and ratiometric fluorescence detection. Furthermore, MI-FL sensor based microdevices are discussed, involving micromotors, test strips and microfluidics, which are more portable for rapid point-of-care detection and in-field diagnosing. Finally, the current challenges and future perspectives of MI-FL sensors are proposed. Copyright © 2018 Elsevier B.V. All rights reserved.

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

NASA Technical Reports Server (NTRS)

Huntsberger, Terry

2011-01-01

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

Molecular recognition of organic ammonium ions in solution using synthetic receptors

PubMed Central

Späth, Andreas

2010-01-01

Summary Ammonium ions are ubiquitous in chemistry and molecular biology. Considerable efforts have been undertaken to develop synthetic receptors for their selective molecular recognition. The type of host compounds for organic ammonium ion binding span a wide range from crown ethers to calixarenes to metal complexes. Typical intermolecular interactions are hydrogen bonds, electrostatic and cation–π interactions, hydrophobic interactions or reversible covalent bond formation. In this review we discuss the different classes of synthetic receptors for organic ammonium ion recognition and illustrate the scope and limitations of each class with selected examples from the recent literature. The molecular recognition of ammonium ions in amino acids is included and the enantioselective binding of chiral ammonium ions by synthetic receptors is also covered. In our conclusion we compare the strengths and weaknesses of the different types of ammonium ion receptors which may help to select the best approach for specific applications. PMID:20502608

Thin membrane sensor with biochemical switch

NASA Technical Reports Server (NTRS)

Worley, III, Jennings F. (Inventor); Case, George D. (Inventor)

1994-01-01

A modular biosensor system for chemical or biological agent detection utilizes electrochemical measurement of an ion current across a gate membrane triggered by the reaction of the target agent with a recognition protein conjugated to a channel blocker. The sensor system includes a bioresponse simulator or biochemical switch module which contains the recognition protein-channel blocker conjugate, and in which the detection reactions occur, and a transducer module which contains a gate membrane and a measuring electrode, and in which the presence of agent is sensed electrically. In the poised state, ion channels in the gate membrane are blocked by the recognition protein-channel blocker conjugate. Detection reactions remove the recognition protein-channel blocker conjugate from the ion channels, thus eliciting an ion current surge in the gate membrane which subsequently triggers an output alarm. Sufficiently large currents are generated that simple direct current electronics are adequate for the measurements. The biosensor has applications for environmental, medical, and industrial use.

Defining scaffold geometries for interacting with proteins: geometrical classification of secondary structure linking regions.

PubMed

Tran, Tran T; Kulis, Christina; Long, Steven M; Bryant, Darryn; Adams, Peter; Smythe, Mark L

2010-11-01

Medicinal chemists synthesize arrays of molecules by attaching functional groups to scaffolds. There is evidence suggesting that some scaffolds yield biologically active molecules more than others, these are termed privileged substructures. One role of the scaffold is to present its side-chains for molecular recognition, and biologically relevant scaffolds may present side-chains in biologically relevant geometries or shapes. Since drug discovery is primarily focused on the discovery of compounds that bind to proteinaceous targets, we have been deciphering the scaffold shapes that are used for binding proteins as they reflect biologically relevant shapes. To decipher the scaffold architecture that is important for binding protein surfaces, we have analyzed the scaffold architecture of protein loops, which are defined in this context as continuous four residue segments of a protein chain that are not part of an α-helix or β-strand secondary structure. Loops are an important molecular recognition motif of proteins. We have found that 39 clusters reflect the scaffold architecture of 89% of the 23,331 loops in the dataset, with average intra-cluster and inter-cluster RMSD of 0.47 and 1.91, respectively. These protein loop scaffolds all have distinct shapes. We have used these 39 clusters that reflect the scaffold architecture of protein loops as biological descriptors. This involved generation of a small dataset of scaffold-based peptidomimetics. We found that peptidomimetic scaffolds with reported biological activities matched loop scaffold geometries and those peptidomimetic scaffolds with no reported biologically activities did not. This preliminary evidence suggests that organic scaffolds with tight matches to the preferred loop scaffolds of proteins, implies the likelihood of the scaffold to be biologically relevant.

Defining scaffold geometries for interacting with proteins: geometrical classification of secondary structure linking regions

NASA Astrophysics Data System (ADS)

Tran, Tran T.; Kulis, Christina; Long, Steven M.; Bryant, Darryn; Adams, Peter; Smythe, Mark L.

2010-11-01

Medicinal chemists synthesize arrays of molecules by attaching functional groups to scaffolds. There is evidence suggesting that some scaffolds yield biologically active molecules more than others, these are termed privileged substructures. One role of the scaffold is to present its side-chains for molecular recognition, and biologically relevant scaffolds may present side-chains in biologically relevant geometries or shapes. Since drug discovery is primarily focused on the discovery of compounds that bind to proteinaceous targets, we have been deciphering the scaffold shapes that are used for binding proteins as they reflect biologically relevant shapes. To decipher the scaffold architecture that is important for binding protein surfaces, we have analyzed the scaffold architecture of protein loops, which are defined in this context as continuous four residue segments of a protein chain that are not part of an α-helix or β-strand secondary structure. Loops are an important molecular recognition motif of proteins. We have found that 39 clusters reflect the scaffold architecture of 89% of the 23,331 loops in the dataset, with average intra-cluster and inter-cluster RMSD of 0.47 and 1.91, respectively. These protein loop scaffolds all have distinct shapes. We have used these 39 clusters that reflect the scaffold architecture of protein loops as biological descriptors. This involved generation of a small dataset of scaffold-based peptidomimetics. We found that peptidomimetic scaffolds with reported biological activities matched loop scaffold geometries and those peptidomimetic scaffolds with no reported biologically activities did not. This preliminary evidence suggests that organic scaffolds with tight matches to the preferred loop scaffolds of proteins, implies the likelihood of the scaffold to be biologically relevant.

Characterizing episodic memory retrieval: electrophysiological evidence for diminished familiarity following unitization.

PubMed

Pilgrim, Lea K; Murray, Jamie G; Donaldson, David I

2012-08-01

Episodic memory relies on both recollection and familiarity; why these processes are differentially engaged during retrieval remains unclear. Traditionally, recollection has been considered necessary for tasks requiring associative retrieval, whereas familiarity supports recognition of items. Recently, however, familiarity has been shown to contribute to associative recognition if stimuli are "unitized" at encoding (a single representation is created from multiple elements)-the "benefit" of unitization. Here, we ask if there is also a "cost" of unitization; are the elements of unitized representations less accessible via familiarity? We manipulated unitization during encoding and used ERPs to index familiarity and recollection at retrieval. The data revealed a selective reduction in the neural correlate of familiarity for individual words originally encoded in unitized compared with nonunitized word pairs. This finding reveals a measurable cost of unitization, suggesting that the nature of to-be-remembered stimuli is critical in determining whether familiarity contributes to episodic memory.

Intra- and interpattern relations in letter recognition.

PubMed

Sanocki, T

1991-11-01

Strings of 4 unrelated letters were backward masked at varying durations to examine 3 major issues. (a) One issue concerned relational features. Letters with abnormal relations but normal elements were created by interchanging elements between large and small normal letters. Overall accuracy was higher for letters with normal relations, consistent with the idea that relational features are important in recognition. (b) Interpattern relations were examined by mixing large and small letters within strings. Relative to pure strings, accuracy was reduced, but only for small letters and only when in mixed strings. This effect can be attributed to attentional priority for larger forms over smaller forms, which also explains global precedence with hierarchical forms. (c) Forced-choice alternatives were manipulated in Experiments 2 and 3 to test feature integration theory. Relational information was found to be processed at least as early as feature presence or absence.

Fine grained recognition of masonry walls for built heritage assessment

NASA Astrophysics Data System (ADS)

Oses, N.; Dornaika, F.; Moujahid, A.

2015-01-01

This paper presents the ground work carried out to achieve automatic fine grained recognition of stone masonry. This is a necessary first step in the development of the analysis tool. The built heritage that will be assessed consists of stone masonry constructions and many of the features analysed can be characterized according to the geometry and arrangement of the stones. Much of the assessment is carried out through visual inspection. Thus, we apply image processing on digital images of the elements under inspection. The main contribution of the paper is the performance evaluation of the automatic categorization of masonry walls from a set of extracted straight line segments. The element chosen to perform this evaluation is the stone arrangement of masonry walls. The validity of the proposed framework is assessed on real images of masonry walls using machine learning paradigms. These include classifiers as well as automatic feature selection.

Delineation of geochemical anomalies based on stream sediment data utilizing fractal modeling and staged factor analysis

NASA Astrophysics Data System (ADS)

Afzal, Peyman; Mirzaei, Misagh; Yousefi, Mahyar; Adib, Ahmad; Khalajmasoumi, Masoumeh; Zarifi, Afshar Zia; Foster, Patrick; Yasrebi, Amir Bijan

2016-07-01

Recognition of significant geochemical signatures and separation of geochemical anomalies from background are critical issues in interpretation of stream sediment data to define exploration targets. In this paper, we used staged factor analysis in conjunction with the concentration-number (C-N) fractal model to generate exploration targets for prospecting Cr and Fe mineralization in Balvard area, SE Iran. The results show coexistence of derived multi-element geochemical signatures of the deposit-type sought and ultramafic-mafic rocks in the NE and northern parts of the study area indicating significant chromite and iron ore prospects. In this regard, application of staged factor analysis and fractal modeling resulted in recognition of significant multi-element signatures that have a high spatial association with host lithological units of the deposit-type sought, and therefore, the generated targets are reliable for further prospecting of the deposit in the study area.

The importance of trace element speciation in biomedical science.

PubMed

Templeton, Douglas M

2003-04-01

According to IUPAC terminology, trace element speciation reflects differences in chemical composition at multiple levels from nuclear and electronic structure to macromolecular complexation. In the medical sciences, all levels of composition are important in various circumstances, and each can affect the bioavailability, distribution, physiological function, toxicity, diagnostic utility, and therapeutic potential of an element. Here we discuss, with specific examples, three biological principles in the intimate relation between speciation and biological behavior: i) the kinetics of interconversion of species determines distribution within the organism, ii) speciation governs transport across various biological barriers, and iii) speciation can limit potentially undesirable interactions between physiologically essential elements. We will also describe differences in the speciation of iron in states of iron overload, to illustrate how speciation analysis can provide insight into cellular processes in human disease.

[Construction of a general AAV vector regulated by minimal and artificial hypoxic-responsive element].

PubMed

Nie, Xiao-wei; Sun, Li-jun; Hao, Yue-wen; Yang, Guang-xiao; Wang, Quan-ying

2011-03-01

To synthesize the minimal and artificial HRE, and to insert it into the anterior extremity of CMV promoter of a AAV plasmid, and then to construct the AAV regulated by hypoxic-responsive element which was introduced into 293 cell by method of Ca3(PO4)2 using three plasmids. Thus obtaining the adenoassociated virus vector regulated by hypoxic-responsive element was possibly used for gene therapy in ischemia angiocardiopathy and cerebrovascular disease. Artificially synthesize the 36 bp nucleotide sequences of four connection in series HIF-binding sites A/GCGTG(4×HBS)and a 35 bp nucleotide sequences spacing inserted into anterior extremity of CMV promoter TATA Box, then amplified by PCR. The cDNA fragment was confirmed to be right by DNA sequencing. Molecular biology routine method was used to construct a AAV vector regulated by minimal hypoxic-responsive element after the normal CMV promoter in AAV vector was replaced by the CMV promoter included minimal hypoxic-responsive element. Then, NT4-6His-PR39 fusogenic peptide was inserted into MCS of the plasmid, the recombinant AAV vector was obtained by three plasmid co-transfection in 293 cells, in which we can also investigate the expression of 6×His using immunochemistry in hypoxia environment. Artificial HRE was inserted into anterior extremity of CMV promoter and there was a correct spacing between the HRE and the TATA-box. The DNA sequencing and restriction enzyme digestion results indicated that the AAV regulated by hypoxic-responsive element was successfully constructed. Compared to the control group, the expressions of 6×His was significantly increased in the experimental groups in hypoxia environment, which confirmed that the AAV effectually regulated by the minimal HRE was inserted into anterior extremity of CMV promoter. The HRE is inserted into anterior extremity of CMV promoter to lack incision enzyme recognition site by PCR. And eukaryotic expression vector regulated by hypoxic-responsive is constructed. The AAV effectually regulated by the minimal HRE inserted into anterior extremity of CMV promoter. The vector is successfully constructed and it has important theoretical and practical value in the synteresis and therapy of ischemia angiocardiopathy and cerebrovascular disease.

Characterization of fiber-forming peptides and proteins by means of atomic force microscopy.

PubMed

Creasey, Rhiannon G; Gibson, Christopher T; Voelcker, Nicolas H

2012-05-01

The atomic force microscope (AFM) is widely used in biological sciences due to its ability to perform imaging experiments at high resolution in a physiological environment, without special sample preparation such as fixation or staining. AFM is unique, in that it allows single molecule information of mechanical properties and molecular recognition to be gathered. This review sets out to identify methodological applications of AFM for characterization of fiber-forming proteins and peptides. The basics of AFM operation are detailed, with in-depth information for any life scientist to get a grasp on AFM capabilities. It also briefly describes antibody recognition imaging and mapping of nanomechanical properties on biological samples. Subsequently, examples of AFM application to fiber-forming natural proteins, and fiber-forming synthetic peptides are given. Here, AFM is used primarily for structural characterization of fibers in combination with other techniques, such as circular dichroism and fluorescence spectroscopy. More recent developments in antibody recognition imaging to identify constituents of protein fibers formed in human disease are explored. This review, as a whole, seeks to encourage the life scientists dealing with protein aggregation phenomena to consider AFM as a part of their research toolkit, by highlighting the manifold capabilities of this technique.

Modulation of electronic structures of bases through DNA recognition of protein.

PubMed

Hagiwara, Yohsuke; Kino, Hiori; Tateno, Masaru

2010-04-21

The effects of environmental structures on the electronic states of functional regions in a fully solvated DNA·protein complex were investigated using combined ab initio quantum mechanics/molecular mechanics calculations. A complex of a transcriptional factor, PU.1, and the target DNA was used for the calculations. The effects of solvent on the energies of molecular orbitals (MOs) of some DNA bases strongly correlate with the magnitude of masking of the DNA bases from the solvent by the protein. In the complex, PU.1 causes a variation in the magnitude among DNA bases by means of directly recognizing the DNA bases through hydrogen bonds and inducing structural changes of the DNA structure from the canonical one. Thus, the strong correlation found in this study is the first evidence showing the close quantitative relationship between recognition modes of DNA bases and the energy levels of the corresponding MOs. Thus, it has been revealed that the electronic state of each base is highly regulated and organized by the DNA recognition of the protein. Other biological macromolecular systems can be expected to also possess similar modulation mechanisms, suggesting that this finding provides a novel basis for the understanding for the regulation functions of biological macromolecular systems.

From The Cover: Induction of antiviral immunity requires Toll-like receptor signaling in both stromal and dendritic cell compartments

NASA Astrophysics Data System (ADS)

Sato, Ayuko; Iwasaki, Akiko

2004-11-01

Pattern recognition by Toll-like receptors (TLRs) is known to be important for the induction of dendritic cell (DC) maturation. DCs, in turn, are critically important in the initiation of T cell responses. However, most viruses do not infect DCs. This recognition system poses a biological problem in ensuring that most viral infections be detected by pattern recognition receptors. Furthermore, it is unknown what, if any, is the contribution of TLRs expressed by cells that are infected by a virus, versus TLRs expressed by DCs, in the initiation of antiviral adaptive immunity. Here we address these issues using a physiologically relevant model of mucosal infection with herpes simplex virus type 2. We demonstrate that innate immune recognition of viral infection occurs in two distinct stages, one at the level of the infected epithelial cells and the other at the level of the noninfected DCs. Importantly, both TLR-mediated recognition events are required for the induction of effector T cells. Our results demonstrate that virally infected tissues instruct DCs to initiate the appropriate class of effector T cell responses and reveal the critical importance of the stromal cells in detecting infectious agents through their own pattern recognition receptors. mucosal immunity | pattern recognition | viral infection

Task-dependent modulation of the visual sensory thalamus assists visual-speech recognition.

PubMed

Díaz, Begoña; Blank, Helen; von Kriegstein, Katharina

2018-05-14

The cerebral cortex modulates early sensory processing via feed-back connections to sensory pathway nuclei. The functions of this top-down modulation for human behavior are poorly understood. Here, we show that top-down modulation of the visual sensory thalamus (the lateral geniculate body, LGN) is involved in visual-speech recognition. In two independent functional magnetic resonance imaging (fMRI) studies, LGN response increased when participants processed fast-varying features of articulatory movements required for visual-speech recognition, as compared to temporally more stable features required for face identification with the same stimulus material. The LGN response during the visual-speech task correlated positively with the visual-speech recognition scores across participants. In addition, the task-dependent modulation was present for speech movements and did not occur for control conditions involving non-speech biological movements. In face-to-face communication, visual speech recognition is used to enhance or even enable understanding what is said. Speech recognition is commonly explained in frameworks focusing on cerebral cortex areas. Our findings suggest that task-dependent modulation at subcortical sensory stages has an important role for communication: Together with similar findings in the auditory modality the findings imply that task-dependent modulation of the sensory thalami is a general mechanism to optimize speech recognition. Copyright © 2018. Published by Elsevier Inc.

Insights into Protein–Ligand Interactions: Mechanisms, Models, and Methods

PubMed Central

Du, Xing; Li, Yi; Xia, Yuan-Ling; Ai, Shi-Meng; Liang, Jing; Sang, Peng; Ji, Xing-Lai; Liu, Shu-Qun

2016-01-01

Molecular recognition, which is the process of biological macromolecules interacting with each other or various small molecules with a high specificity and affinity to form a specific complex, constitutes the basis of all processes in living organisms. Proteins, an important class of biological macromolecules, realize their functions through binding to themselves or other molecules. A detailed understanding of the protein–ligand interactions is therefore central to understanding biology at the molecular level. Moreover, knowledge of the mechanisms responsible for the protein-ligand recognition and binding will also facilitate the discovery, design, and development of drugs. In the present review, first, the physicochemical mechanisms underlying protein–ligand binding, including the binding kinetics, thermodynamic concepts and relationships, and binding driving forces, are introduced and rationalized. Next, three currently existing protein-ligand binding models—the “lock-and-key”, “induced fit”, and “conformational selection”—are described and their underlying thermodynamic mechanisms are discussed. Finally, the methods available for investigating protein–ligand binding affinity, including experimental and theoretical/computational approaches, are introduced, and their advantages, disadvantages, and challenges are discussed. PMID:26821017

Behavioural development of conspecific odour preferences in bank voles, Clethrionomys glareolus.

PubMed

Kruczek, Malgorzata; Golas, Aniela

2003-08-29

Biological odours of conspecifics are known to have strong influences on behavioural interaction in bank voles Clethrionomys glareolus. This experiment tested two hypotheses. (1) Olfactory cues from familiar and unfamiliar mature opposite-sex conspecifics differ in their attractiveness to males and females, and their behavioural reactions change with age. (2) A genetically based mechanism is involved in female recognition of kin.In a two-choice preference test, prepubertal males and females were more attracted to familiar than to unfamiliar odours of opposite-sex conspecifics, as manifested by more time spent sniffing familiar voles. As the young reached sexual maturity they shifted their odour preferences. Mature males and females preferred the novel odour of unrelated opposite-sex conspecifics to that of relatives. The results of experiments testing the second hypothesis indicate that females use a genetically based mechanism to recognise their kin. Young and mature females were able to recognise the odour of their biological but socially unknown fathers, and showed the same pattern of behaviour as females in previous experiments.The possible biological functions of kin recognition in bank voles are discussed.

Elemental mapping of biological samples using a scanning proton microprobe

NASA Astrophysics Data System (ADS)

Watt, F.; Grime, G. W.

1988-03-01

Elemental mapping using a scanning proton microprobe (SPM) can be a powerful technique for probing trace elements in biology, allowing complex interfaces to be studied in detail, identifying contamination and artefacts present in the specimen, and in certain circumstances obtaining indirect chemical information. Examples used to illustrate the advantages of the technique include the elemental mapping of growing pollen tubes, honey bee brain section, a mouse macrophage cell, human liver section exhibiting primary biliary cirrhosis, and the attack by a mildew fungus on a pea leaf.

Cross-modal working memory binding and word recognition skills: how specific is the link?

PubMed

Wang, Shinmin; Allen, Richard J

2018-04-01

Recent research has suggested that the creation of temporary bound representations of information from different sources within working memory uniquely relates to word recognition abilities in school-age children. However, it is unclear to what extent this link is attributable specifically to the binding ability for cross-modal information. This study examined the performance of Grade 3 (8-9 years old) children on binding tasks requiring either temporary association formation of two visual items (i.e., within-modal binding) or pairs of visually presented abstract shapes and auditorily presented nonwords (i.e., cross-modal binding). Children's word recognition skills were related to performance on the cross-modal binding task but not on the within-modal binding task. Further regression models showed that cross-modal binding memory was a significant predictor of word recognition when memory for its constituent elements, general abilities, and crucially, within-modal binding memory were taken into account. These findings may suggest a specific link between the ability to bind information across modalities within working memory and word recognition skills.

Global Conformational Selection and Local Induced Fit for the Recognition between Intrinsic Disordered p53 and CBP

PubMed Central

Yu, Qingfen; Ye, Wei; Wang, Wei; Chen, Hai-Feng

2013-01-01

The transactivation domain (TAD) of tumor suppressor p53 can bind with the nuclear coactivator binding domain (NCBD) of cyclic-AMP response element binding protein (CBP) and activate transcription. NMR experiments demonstrate that both apo-NCBD and TAD are intrinsic disordered and bound NCBD/TAD undergoes a transition to well folded. The recognition mechanism between intrinsic disordered proteins is still hotly debated. Molecular dynamics (MD) simulations in explicit solvent are used to study the recognition mechanism between intrinsic disordered TAD and NCBD. The average RMSD values between bound and corresponding apo states and Kolmogorov-Smirnov P test analysis indicate that TAD and NCBD may follow an induced fit mechanism. Quantitative analysis indicates there is also a global conformational selection. In summary, the recognition of TAD and NCBD might obey a local induced fit and global conformational selection. These conclusions are further supported by high-temperature unbinding kinetics and room temperature landscape analysis. These methods can be used to study the recognition mechanism of other intrinsic disordered proteins. PMID:23555731

Fish gelatin thin film standards for biological application of PIXE

NASA Astrophysics Data System (ADS)

Manuel, Jack E.; Rout, Bibhudutta; Szilasi, Szabolcs Z.; Bohara, Gyanendra; Deaton, James; Luyombya, Henry; Briski, Karen P.; Glass, Gary A.

2014-08-01

There exists a critical need to understand the flow and accumulation of metallic ions, both naturally occurring and those introduced to biological systems. In this paper the results of fabricating thin film elemental biological standards containing nearly any combination of trace elements in a protein matrix are presented. Because it is capable of high elemental sensitivity, particle induced X-ray emission spectrometry (PIXE) is an excellent candidate for in situ analysis of biological tissues. Additionally, the utilization of microbeam PIXE allows the determination of elemental concentrations in and around biological cells. However, obtaining elemental reference standards with the same matrix constituents as brain tissue is difficult. An excellent choice for simulating brain-like tissue is Norland® photoengraving glue which is derived from fish skin. Fish glue is water soluble, liquid at room temperature, and resistant to dilute acid. It can also be formed into a thin membrane which dries into a durable, self-supporting film. Elements of interest are introduced to the fish glue in precise volumetric additions of well quantified atomic absorption standard solutions. In this study GeoPIXE analysis package is used to quantify elements intrinsic to the fish glue as well as trace amounts of manganese added to the sample. Elastic (non-Rutherford) backscattered spectroscopy (EBS) and the 1.734 MeV proton-on-carbon 12C(p,p)12C resonance is used for a normalization scheme of the PIXE spectra to account for any discrepancies in X-ray production arising from thickness variation of the prepared standards. It is demonstrated that greater additions of the atomic absorption standard cause a viscosity reduction of the liquid fish glue resulting in thinner films but the film thickness can be monitored by using simultaneous PIXE and EBS proton data acquisition.

Introduction of the human AVPR1A gene substantially alters brain receptor expression patterns and enhances aspects of social behavior in transgenic mice.

PubMed

Charles, Rhonda; Sakurai, Takeshi; Takahashi, Nagahide; Elder, Gregory A; Gama Sosa, Miguel A; Young, Larry J; Buxbaum, Joseph D

2014-08-01

Central arginine vasopressin receptor 1A (AVPR1A) modulates a wide range of behaviors, including stress management and territorial aggression, as well as social bonding and recognition. Inter- and intra-species variations in the expression pattern of AVPR1A in the brain and downstream differential behavioral phenotypes have been attributed to differences in the non-coding regions of the AVPR1A gene, including polymorphic elements within upstream regulatory areas. Gene association studies have suggested a link between AVPR1A polymorphisms and autism, and AVPR1A has emerged as a potential pharmacological target for treatment of social cognitive impairments and mood and anxiety disorders. To further investigate the genetic mechanism giving rise to species differences in AVPR1A expression patterns and associated social behaviors, and to create a preclinical mouse model useful for screening drugs targeting AVPR1A, we engineered and extensively characterized bacterial artificial chromosome (BAC) transgenic mice harboring the entire human AVPR1A locus with the surrounding regulatory elements. Compared with wild-type animals, the humanized mice displayed a more widely distributed ligand-AVPR1A binding pattern, which overlapped with that of primates. Furthermore, humanized AVPR1A mice displayed increased reciprocal social interactions compared with wild-type animals, but no differences in social approach and preference for social novelty were observed. Aspects of learning and memory, specifically novel object recognition and spatial relocation recognition, were unaffected. The biological alterations in humanized AVPR1A mice resulted in the rescue of the prepulse inhibition impairments that were observed in knockout mice, indicating conserved functionality. Although further behavioral paradigms and additional cohorts need to be examined in humanized AVPR1A mice, the results demonstrate that species-specific variations in the genomic content of regulatory regions surrounding the AVPR1A locus are responsible for differential receptor protein expression patterns across species and that they are likely to contribute to species-specific behavioral variation. The humanized AVPR1A mouse is a potential preclinical model for further understanding the regulation of receptor gene expression and the impact of variation in receptor expression on behaviors, and should be useful for screening drugs targeting human AVPR1A, taking advantage of the expression of human AVPR1A in human-relevant brain regions. © 2014. Published by The Company of Biologists Ltd.

Machine learning based sample extraction for automatic speech recognition using dialectal Assamese speech.

PubMed

Agarwalla, Swapna; Sarma, Kandarpa Kumar

2016-06-01

Automatic Speaker Recognition (ASR) and related issues are continuously evolving as inseparable elements of Human Computer Interaction (HCI). With assimilation of emerging concepts like big data and Internet of Things (IoT) as extended elements of HCI, ASR techniques are found to be passing through a paradigm shift. Oflate, learning based techniques have started to receive greater attention from research communities related to ASR owing to the fact that former possess natural ability to mimic biological behavior and that way aids ASR modeling and processing. The current learning based ASR techniques are found to be evolving further with incorporation of big data, IoT like concepts. Here, in this paper, we report certain approaches based on machine learning (ML) used for extraction of relevant samples from big data space and apply them for ASR using certain soft computing techniques for Assamese speech with dialectal variations. A class of ML techniques comprising of the basic Artificial Neural Network (ANN) in feedforward (FF) and Deep Neural Network (DNN) forms using raw speech, extracted features and frequency domain forms are considered. The Multi Layer Perceptron (MLP) is configured with inputs in several forms to learn class information obtained using clustering and manual labeling. DNNs are also used to extract specific sentence types. Initially, from a large storage, relevant samples are selected and assimilated. Next, a few conventional methods are used for feature extraction of a few selected types. The features comprise of both spectral and prosodic types. These are applied to Recurrent Neural Network (RNN) and Fully Focused Time Delay Neural Network (FFTDNN) structures to evaluate their performance in recognizing mood, dialect, speaker and gender variations in dialectal Assamese speech. The system is tested under several background noise conditions by considering the recognition rates (obtained using confusion matrices and manually) and computation time. It is found that the proposed ML based sentence extraction techniques and the composite feature set used with RNN as classifier outperform all other approaches. By using ANN in FF form as feature extractor, the performance of the system is evaluated and a comparison is made. Experimental results show that the application of big data samples has enhanced the learning of the ASR system. Further, the ANN based sample and feature extraction techniques are found to be efficient enough to enable application of ML techniques in big data aspects as part of ASR systems. Copyright © 2015 Elsevier Ltd. All rights reserved.

The biology and evolution of transposable elements in parasites.

PubMed

Thomas, M Carmen; Macias, Francisco; Alonso, Carlos; López, Manuel C

2010-07-01

Transposable elements (TEs) are dynamic elements that can reshape host genomes by generating rearrangements with the potential to create or disrupt genes, to shuffle existing genes, and to modulate their patterns of expression. In the genomes of parasites that infect mammals several TEs have been identified that probably have been maintained throughout evolution due to their contribution to gene function and regulation of gene expression. This review addresses how TEs are organized, how they colonize the genomes of mammalian parasites, the functional role these elements play in parasite biology, and the interactions between these elements and the parasite genome. Copyright 2010 Elsevier Ltd. All rights reserved.

Functions of galectins as 'self/non-self'-recognition and effector factors.

PubMed

Vasta, Gerardo R; Feng, Chiguang; González-Montalbán, Nuria; Mancini, Justin; Yang, Lishi; Abernathy, Kelsey; Frost, Graeme; Palm, Cheyenne

2017-07-31

Carbohydrate structures on the cell surface encode complex information that through specific recognition by carbohydrate-binding proteins (lectins) modulates interactions between cells, cells and the extracellular matrix, or mediates recognition of potential microbial pathogens. Galectins are a family of ß-galactoside-binding lectins, which are evolutionary conserved and have been identified in most organisms, from fungi to invertebrates and vertebrates, including mammals. Since their discovery in the 1970s, their biological roles, initially understood as limited to recognition of endogenous carbohydrate ligands in embryogenesis and development, have expanded in recent years by the discovery of their roles in tissue repair and regulation of immune homeostasis. More recently, evidence has accumulated to support the notion that galectins can also bind glycans on the surface of potentially pathogenic microbes, and function as recognition and effector factors in innate immunity, thus establishing a new paradigm. Furthermore, some parasites 'subvert' the recognition roles of the vector/host galectins for successful attachment or invasion. These recent findings have revealed a striking functional diversification in this structurally conserved lectin family. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Simulation of Biomimetic Recognition between Polymers and Surfaces

NASA Astrophysics Data System (ADS)

Golumbfskie, Aaron J.; Pande, Vijay S.; Chakraborty, Arup K.

1999-10-01

Many biological processes, such as transmembrane signaling and pathogen-host interactions, are initiated by a protein recognizing a specific pattern of binding sites on part of a membrane or cell surface. By recognition, we imply that the polymer quickly finds and then adsorbs strongly on the pattern-matched region and not on others. The development of synthetic systems that can mimic such recognition between polymers and surfaces could have significant impact on advanced applications such as the development of sensors, molecular-scale separation processes, and synthetic viral inhibition agents. Attempting to affect recognition in synthetic systems by copying the detailed chemistries to which nature has been led over millenia of evolution does not seem practical for most applications. This leads us to the following question: Are there any universal strategies that can affect recognition between polymers and surfaces? Such generic strategies may be easier to implement in abiotic applications. We describe results that suggest that biomimetic recognition between synthetic polymers and surfaces is possible by exploiting certain generic strategies, and we elucidate the kinetic mechanisms by which this occurs. Our results suggest convenient model systems for experimental studies of dynamics in free energy landscapes characteristic of frustrated systems.

ElemeNT: a computational tool for detecting core promoter elements.

PubMed

Sloutskin, Anna; Danino, Yehuda M; Orenstein, Yaron; Zehavi, Yonathan; Doniger, Tirza; Shamir, Ron; Juven-Gershon, Tamar

2015-01-01

Core promoter elements play a pivotal role in the transcriptional output, yet they are often detected manually within sequences of interest. Here, we present 2 contributions to the detection and curation of core promoter elements within given sequences. First, the Elements Navigation Tool (ElemeNT) is a user-friendly web-based, interactive tool for prediction and display of putative core promoter elements and their biologically-relevant combinations. Second, the CORE database summarizes ElemeNT-predicted core promoter elements near CAGE and RNA-seq-defined Drosophila melanogaster transcription start sites (TSSs). ElemeNT's predictions are based on biologically-functional core promoter elements, and can be used to infer core promoter compositions. ElemeNT does not assume prior knowledge of the actual TSS position, and can therefore assist in annotation of any given sequence. These resources, freely accessible at http://lifefaculty.biu.ac.il/gershon-tamar/index.php/resources, facilitate the identification of core promoter elements as active contributors to gene expression.

A study of some nine-element decision rules. [for multispectral recognition of remote sensing

NASA Technical Reports Server (NTRS)

Richardson, W.

1974-01-01

A nine-element rule is one that makes a classification decision for each pixel based on data from that pixel and its eight immediate neighbors. Three such rules, all fast and simple to use, are defined and tested. All performed substantially better on field interiors than the best one-point rule. Qualitative results indicate that fine detail and contradictory testimony tend to be overlooked by the rules.

An Annotated Bibliography on Tactical Map Display Symbology

DTIC Science & Technology

1989-08-01

failure of attention to be focused on one element selectively in filtering tasks where only that one element was relevant to the discrimination. Failure of...The present study evaluates a class of models of human information processing made popular by Broadbent . A brief tachistoscopic display of one or two...213-219. Two experiments were performed to test Neisser’s two-stage model of recognition as applied to matching. Evidence of parallel processing was

Physical approaches to biomaterial design

PubMed Central

Mitragotri, Samir; Lahann, Joerg

2009-01-01

The development of biomaterials for drug delivery, tissue engineering and medical diagnostics has traditionally been based on new chemistries. However, there is growing recognition that the physical as well as the chemical properties of materials can regulate biological responses. Here, we review this transition with regard to selected physical properties including size, shape, mechanical properties, surface texture and compartmentalization. In each case, we present examples demonstrating the significance of these properties in biology. We also discuss synthesis methods and biological applications for designer biomaterials, which offer unique physical properties. PMID:19096389

Structural elements and organization of the ancestral translational machinery

NASA Technical Reports Server (NTRS)

Rein, R.; Srinivasan, S.; Mcdonald, J.; Raghunathan, G.; Shibata, M.

1987-01-01

The molecular mechanisms of the primitive translational apparatus are discussed in the framework of present-day protein biosynthesis. The structural necessities of an early adaptor and the multipoint recognition properties of such an adaptor are investigated on the basis of structure/function relationships found in a contemporary system and a molecular model of the contemporary transpeptidation complex. A model of the tRNA(Tyr)-tyrosyl tRNA synthetase complex including the positioning of the disordered region is proposed; the model is used to illustrate the required recognition properties of the ancestor aminoacyl synthetase.

Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition.

PubMed

Spoerer, Courtney J; McClure, Patrick; Kriegeskorte, Nikolaus

2017-01-01

Feedforward neural networks provide the dominant model of how the brain performs visual object recognition. However, these networks lack the lateral and feedback connections, and the resulting recurrent neuronal dynamics, of the ventral visual pathway in the human and non-human primate brain. Here we investigate recurrent convolutional neural networks with bottom-up (B), lateral (L), and top-down (T) connections. Combining these types of connections yields four architectures (B, BT, BL, and BLT), which we systematically test and compare. We hypothesized that recurrent dynamics might improve recognition performance in the challenging scenario of partial occlusion. We introduce two novel occluded object recognition tasks to test the efficacy of the models, digit clutter (where multiple target digits occlude one another) and digit debris (where target digits are occluded by digit fragments). We find that recurrent neural networks outperform feedforward control models (approximately matched in parametric complexity) at recognizing objects, both in the absence of occlusion and in all occlusion conditions. Recurrent networks were also found to be more robust to the inclusion of additive Gaussian noise. Recurrent neural networks are better in two respects: (1) they are more neurobiologically realistic than their feedforward counterparts; (2) they are better in terms of their ability to recognize objects, especially under challenging conditions. This work shows that computer vision can benefit from using recurrent convolutional architectures and suggests that the ubiquitous recurrent connections in biological brains are essential for task performance.

3D Object Recognition: Symmetry and Virtual Views

DTIC Science & Technology

1992-12-01

NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATIONI Artificial Intelligence Laboratory REPORT NUMBER 545 Technology Square AIM 1409 Cambridge... ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING A.I. Memo No. 1409 December 1992 C.B.C.L. Paper No. 76 3D Object...research done within the Center for Biological and Computational Learning in the Department of Brain and Cognitive Sciences, and at the Artificial

Biology and control of Eriophyid mites with a case study of Aceria sp. on New Mexico olive (Forestiera pubescens Nutt. var. pubescens)

Treesearch

Tessa R. Grasswitz

2012-01-01

The biology, recognition, and impact of eriophyid mites (with emphasis on species associated with trees and shrubs) are briefly reviewed. A case study of a leaf-curling eriophyid mite (Aceria sp.) attacking New Mexico olive (Forestiera pubescens Nutt. var. pubescens) is used to illustrate the complexities of developing control strategies for eriophyids in native plant...

Thin-Membrane Sensor With Biochemical Switch

NASA Technical Reports Server (NTRS)

Case, George D.; Worley, Jennings F.

1992-01-01

Modular sensor electrochemically detects chemical or biological agent, indicating presence of agent via gate-membrane-crossing ion current triggered by chemical reaction between agent and recognition protein conjugated to channel blocker. Used in such laboratory, industrial, or field applications as detection of bacterial toxins in food, military chemical agents in air, and pesticides or other contaminants in environment. Also used in biological screening for hepatitis, acquired immune-deficiency syndrome, and like.

Preliminary finite element analysis of locomotive crashworthy components

DOT National Transportation Integrated Search

2011-09-21

The Office of Research and Development of the Federal Railroad Administration (FRA) and the Volpe Center are continuing to evaluate new technologies for increasing the safety of passengers and operators in rail equipment. In recognition of the import...

20 CFR 408.1210 - What are the essential elements of an administration agreement?

Code of Federal Regulations, 2010 CFR

2010-04-01

... BENEFITS FOR CERTAIN WORLD WAR II VETERANS Federal Administration of State Recognition Payments § 408.1210... total number of checks we issue, and direct deposits we make, to recipients in that month, that are...

[Study of biological performance of Chinese materia medica with either a cold or hot property based on the three-element mathematical analysis model].

PubMed

Jin, Rui; Zhang, Bing; Liu, Xiao-Qing; Liu, Sen-Mao; Liu, Xin; Li, Lian-Zhen; Zhang, Qian; Xue, Chun-Miao

2011-07-01

The properties of Chinese materia medica are believed to be the summarization of the effects of biological performance on the various body states. Systemic discussion of chemical-factor elements, body-condition elements, biological-performance elements and their interrelationships is needed for research into the properties of Chinese materia medica. Following the practical characteristics of Chinese medicine, the three-element mathematical model was formed by introducing some mathematical concepts and methods and was used to study the cold or hot property of Chinese medicine, and to investigate the difference in biological performances of the two properties. By using the concept of different functionality of Chinese medicine on abnormal states and the idea of interaction in mathematics, the effects of chemical-factor elements and body-condition elements were normalized to the amount of biological performance which was represented by some important indicators. The three-element mathematical model was formed with scatter plots through four steps, including effect separation, intensity calculation, frequency statistics and relevance analysis. A comparison pharmacology experiment of administration of hot property medicines, Fuzi (Radix Aconiti Lateralis Preparata) and Rougui (Cortex Cinnamomi), and cold property medicines, Huangbai (Cortex Phellodendri) and Zhizi (Fructus Gardeniae) on normal and glucocorticoid-induced yang-deficiency and yin-deficiency states was designed. The results were analyzed by the mathematical model. The scatter plots were the main output of model analysis. The expression of cold property and hot property was able to be quantified by frequency distribution of biological indexes of administrations on yang-deficiency and yin-deficiency states in the "efficacy zone" and "toxicity zone" of the plots and by the relevance analysis. The ratios of biological indicator frequency in the "efficacy zone" of administrations on yang-deficiency state and yin-deficiency state were 7:3 for Fuzi, 3:3 for Rougui, 4:4 for Huangbai and 1:5 for Zhizi. The sums of the biological indicator frequency in the "toxicity zone" of administration on the two states were 4 for Fuzi, 0 for Rougui, 2 for Huangbai and 4 for Zhizi. The relevance analysis showed that the order from Fuzi, Rougui, Huangbai to Zhizi was proportional to the change from "be true of yang-deficiency state" to "be true of yin-deficiency state". The extent of the hot property decreased while that of the cold property increased in the order of Fuzi, Rougui, Huangbai and Zhizi. The stronger the efficacy of above medicines is, the more obvious the toxicity displayed. The three-element mathematical model employed in this study is effectively capable of explaining the different biological expressions between hot property medicines and cold property medicines. This suggests that it may provide a mathematical tool and theoretical basis for the modern interpretation of cold property and hot property of Chinese medicine, and provide new ideas for further studing into the essence of Chinese medicine property theory.

In vitro element release and biological aspects of base–metal alloys for metal-ceramic applications

PubMed Central

Holm, Charlotta; Morisbak, Else; Kalfoss, Torill; Dahl, Jon E.

2015-01-01

Abstract Objective: The aims of this study were to investigate the release of element from, and the biological response in vitro to, cobalt–chromium alloys and other base–metal alloys used for the fabrication of metal-ceramic restorations. Material and methods: Eighteen different alloys were investigated. Nine cobalt–chromium alloys, three nickel–chromium alloys, two cobalt–chromium–iron alloys, one palladium–silver alloy, one high-noble gold alloy, titanium grade II and one type III copper–aluminium alloy. Pure copper served as positive control. The specimens were prepared according to the ISO standards for biological and corrosion testing. Passive leaching of elements was measured by using Inductively Coupled Plasma – Mass Spectrometry (ICP-MS) after incubation in cell culture media, MEM, for 3 days. Corrosion testing was carried out in 0.9% sodium chloride (NaCl) and 1% lactic acid for 7 days, and the element release was measured by Inductively Coupled Plasma – Optical Emission Spectroscopy (ICP-OES). The biological response from the extract solutions was measured though MTT cytotoxicity testing and the Hen's egg test-chorio-allantoic membrane (HET-CAM) technique for irritationt. Results: The corrosion test showed similar element release from base-metal alloys compared to noble alloys such as gold. Apart from the high-copper alloy, all alloys expressed low element release in the immersion test, no cytotoxic effect in the MTT test, and were rated non-irritant in the HET-CAM test. Conclusions: Minimal biological response was observed for all the alloys tested, with the exception of the high-copper alloy. PMID:28642904

Trace elements during primordial plexiform network formation in human cerebral organoids

PubMed Central

Sartore, Rafaela C.; Cardoso, Simone C.; Lages, Yury V.M.; Paraguassu, Julia M.; Stelling, Mariana P.; Madeiro da Costa, Rodrigo F.; Guimaraes, Marilia Z.; Pérez, Carlos A.

2017-01-01

Systematic studies of micronutrients during brain formation are hindered by restrictions to animal models and adult post-mortem tissues. Recently, advances in stem cell biology have enabled recapitulation of the early stages of human telencephalon development in vitro. In the present work, we analyzed cerebral organoids derived from human pluripotent stem cells by synchrotron radiation X-ray fluorescence in order to measure biologically valuable micronutrients incorporated and distributed into the exogenously developing brain. Our findings indicate that elemental inclusion in organoids is consistent with human brain tissue and involves P, S, K, Ca, Fe and Zn. Occurrence of different concentration gradients also suggests active regulation of elemental transmembrane transport. Finally, the analysis of pairs of elements shows interesting elemental interaction patterns that change from 30 to 45 days of development, suggesting short- or long-term associations, such as storage in similar compartments or relevance for time-dependent biological processes. These findings shed light on which trace elements are important during human brain development and will support studies aimed to unravel the consequences of disrupted metal homeostasis for neurodevelopmental diseases, including those manifested in adulthood. PMID:28194309

Recognition- and Reactivity-Based Fluorescent Probes for Studying Transition Metal Signaling in Living Systems

PubMed Central

2015-01-01

Conspectus Metals are essential for life, playing critical roles in all aspects of the central dogma of biology (e.g., the transcription and translation of nucleic acids and synthesis of proteins). Redox-inactive alkali, alkaline earth, and transition metals such as sodium, potassium, calcium, and zinc are widely recognized as dynamic signals, whereas redox-active transition metals such as copper and iron are traditionally thought of as sequestered by protein ligands, including as static enzyme cofactors, in part because of their potential to trigger oxidative stress and damage via Fenton chemistry. Metals in biology can be broadly categorized into two pools: static and labile. In the former, proteins and other macromolecules tightly bind metals; in the latter, metals are bound relatively weakly to cellular ligands, including proteins and low molecular weight ligands. Fluorescent probes can be useful tools for studying the roles of transition metals in their labile forms. Probes for imaging transition metal dynamics in living systems must meet several stringent criteria. In addition to exhibiting desirable photophysical properties and biocompatibility, they must be selective and show a fluorescence turn-on response to the metal of interest. To meet this challenge, we have pursued two general strategies for metal detection, termed “recognition” and “reactivity”. Our design of transition metal probes makes use of a recognition-based approach for copper and nickel and a reactivity-based approach for cobalt and iron. This Account summarizes progress in our laboratory on both the development and application of fluorescent probes to identify and study the signaling roles of transition metals in biology. In conjunction with complementary methods for direct metal detection and genetic and/or pharmacological manipulations, fluorescent probes for transition metals have helped reveal a number of principles underlying transition metal dynamics. In this Account, we give three recent examples from our laboratory and collaborations in which applications of chemical probes reveal that labile copper contributes to various physiologies. The first example shows that copper is an endogenous regulator of neuronal activity, the second illustrates cellular prioritization of mitochondrial copper homeostasis, and the third identifies the “cuprosome” as a new copper storage compartment in Chlamydomonas reinhardtii green algae. Indeed, recognition- and reactivity-based fluorescent probes have helped to uncover new biological roles for labile transition metals, and the further development of fluorescent probes, including ones with varied Kd values and new reaction triggers and recognition receptors, will continue to reveal exciting and new biological roles for labile transition metals. PMID:26215055

HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition.

PubMed

Lagorce, Xavier; Orchard, Garrick; Galluppi, Francesco; Shi, Bertram E; Benosman, Ryad B

2017-07-01

This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.

A glimpse on biological activities of tellurium compounds.

PubMed

Cunha, Rodrigo L O R; Gouvea, Iuri E; Juliano, Luiz

2009-09-01

Tellurium is a rare element which has been regarded as a toxic, non-essential trace element and its biological role is not clearly established to date. Besides of that, the biological effects of elemental tellurium and some of its inorganic and organic derivatives have been studied, leading to a set of interesting and promising applications. As an example, it can be highlighted the uses of alkali-metal tellurites and tellurates in microbiology, the antioxidant effects of organotellurides and diorganoditellurides and the immunomodulatory effects of the non-toxic inorganic tellurane, named AS-101, and the plethora of its uses. Inasmuch, the nascent applications of organic telluranes (organotelluranes) as protease inhibitors and its applications in disease models are the most recent contribution to the scenario of the biological effects and applications of tellurium and its compounds discussed in this manuscript.

Theoretical Investigation of Optical Detection and Recognition of Single Biological Molecules Using Coherent Dynamics of Exciton-Plasmon Coupling

PubMed Central

Sadeghi, S. M.; Hood, B.; Patty, K. D.; Mao, C.-B.

2013-01-01

We use quantum coherence in a system consisting of one metallic nanorod and one semi-conductor quantum dot to investigate a plasmonic nanosensor capable of digital optical detection and recognition of single biological molecules. In such a sensor the adsorption of a specific molecule to the nanorod turns off the emission of the system when it interacts with an optical pulse having a certain intensity and temporal width. The proposed quantum sensors can count the number of molecules of the same type or differentiate between molecule types with digital optical signals that can be measured with high certainty. We show that these sensors are based on the ultrafast upheaval of coherent dynamics of the system and the removal of coherent blockage of energy transfer from the quantum dot to the nanorod once the adsorption process has occurred. PMID:24040424

Sialoglycans in protozoal diseases: their detection, modes of acquisition and emerging biological roles.

PubMed

Chava, Anil K; Bandyopadhyay, Sumi; Chatterjee, Mitali; Mandal, Chitra

2004-01-01

Protozoan parasites including Plasmodia, Leishmania, Trypanosoma, Entamoeba, Trichomonas and others cause diseases in humans and domestic livestock having far-reaching socio-economic implications. They show remarkable propensity to survive within hostile environments encountered during their life cycle, and the identification of molecules that enable them to survive in such milieu is a subject of intense research. Currently available knowledge of the parasite cell surface architecture and biochemistry indicates that sialic acid and its principle derivatives are major components of the glycocalyx and assist the parasite to interact with its external environment through functions ranging from parasite survival, infectivity and host-cell recognition. This review highlights the present state of knowledge with regard to parasite sialobiology with an emphasis on its mode(s) of acquisition and their emerging biological roles, notably as an anti-recognition molecule thereby aiding the pathogen to evade host defense mechanisms.

Scattering Removal for Finger-Vein Image Restoration

PubMed Central

Yang, Jinfeng; Zhang, Ben; Shi, Yihua

2012-01-01

Finger-vein recognition has received increased attention recently. However, the finger-vein images are always captured in poor quality. This certainly makes finger-vein feature representation unreliable, and further impairs the accuracy of finger-vein recognition. In this paper, we first give an analysis of the intrinsic factors causing finger-vein image degradation, and then propose a simple but effective image restoration method based on scattering removal. To give a proper description of finger-vein image degradation, a biological optical model (BOM) specific to finger-vein imaging is proposed according to the principle of light propagation in biological tissues. Based on BOM, the light scattering component is sensibly estimated and properly removed for finger-vein image restoration. Finally, experimental results demonstrate that the proposed method is powerful in enhancing the finger-vein image contrast and in improving the finger-vein image matching accuracy. PMID:22737028

Bioterrorism for the respiratory physician.

PubMed

Waterer, Grant W; Robertson, Hannah

2009-01-01

Terrorist attacks by definition are designed to cause fear and panic. There is no question that a terrorist attack using biological agents would present a grave threat to stability of the society in which they were released. Early recognition of such a bioterrorist attack is crucial to containing the damage they could cause. As many of the most likely bioterrorism agents present with pulmonary disease, respiratory physicians may be crucial in the initial recognition and diagnosis phase, and certainly would be drawn into treatment of affected individuals. This review focuses on the biological agents thought most likely to be used by terrorists that have predominantly respiratory presentations. The primary focus of this review is on anthrax, plague, tularaemia, ricin, and Staphylococcal enterotoxin B. The pathogenesis, clinical manifestations and treatment of these agents will be discussed as well as historical examples of their use. Other potential bioterrorism agents with respiratory manifestations will also be discussed briefly.

Common themes and differences in SAM recognition among SAM riboswitches.

PubMed

Price, Ian R; Grigg, Jason C; Ke, Ailong

2014-10-01

The recent discovery of short cis-acting RNA elements termed riboswitches has caused a paradigm shift in our understanding of genetic regulatory mechanisms. The three distinct superfamilies of S-adenosyl-l-methionine (SAM) riboswitches are the most commonly found riboswitch classes in nature. These RNAs represent three independent evolutionary solutions to achieve specific SAM recognition. This review summarizes research on 1) modes of gene regulatory mechanisms, 2) common themes and differences in ligand recognition, and 3) ligand-induced conformational dynamics among SAM riboswitch families. The body of work on the SAM riboswitch families constitutes a useful primer to the topic of gene regulatory RNAs as a whole. This article is part of a Special Issue entitled: Riboswitches. Copyright © 2014 Elsevier B.V. All rights reserved.

Validation of an entirely in vitro approach for rapid prototyping of DNA regulatory elements for synthetic biology

PubMed Central

Chappell, James; Jensen, Kirsten; Freemont, Paul S.

2013-01-01

A bottleneck in our capacity to rationally and predictably engineer biological systems is the limited number of well-characterized genetic elements from which to build. Current characterization methods are tied to measurements in living systems, the transformation and culturing of which are inherently time-consuming. To address this, we have validated a completely in vitro approach for the characterization of DNA regulatory elements using Escherichia coli extract cell-free systems. Importantly, we demonstrate that characterization in cell-free systems correlates and is reflective of performance in vivo for the most frequently used DNA regulatory elements. Moreover, we devise a rapid and completely in vitro method to generate DNA templates for cell-free systems, bypassing the need for DNA template generation and amplification from living cells. This in vitro approach is significantly quicker than current characterization methods and is amenable to high-throughput techniques, providing a valuable tool for rapidly prototyping libraries of DNA regulatory elements for synthetic biology. PMID:23371936

Development of bacterial display peptides for use in biosensing applications

NASA Astrophysics Data System (ADS)

Stratis-Cullum, Dimitra N.; Kogot, Joshua M.; Sellers, Michael S.; Hurley, Margaret M.; Sarkes, Deborah A.; Pennington, Joseph M.; Val-Addo, Irene; Adams, Bryn L.; Warner, Candice R.; Carney, James P.; Brown, Rebecca L.; Pellegrino, Paul M.

2012-06-01

Recent advances in synthetic library engineering continue to show promise for the rapid production of reagent technology in response to biological threats. A synthetic library of peptide mutants built off a bacterial host offers a convenient means to link the peptide sequence, (i.e., identity of individual library members) with the desired molecular recognition traits, but also allows for a relatively simple protocol, amenable to automation. An improved understanding of the mechanisms of recognition and control of synthetic reagent isolation and evolution remain critical to success. In this paper, we describe our approach to development of peptide affinity reagents based on peptide bacterial display technology with improved control of binding interactions for stringent evolution of reagent candidates, and tailored performance capabilities. There are four key elements to the peptide affinity reagent program including: (1) the diverse bacterial library technology, (2) advanced reagent screening amenable to laboratory automation and control, (3) iterative characterization and feedback on both affinity and specificity of the molecular interactions, and (3) integrated multiscale computational prescreening of candidate peptide ligands including in silico prediction of improved binding performance. Specific results on peptides binders to Protective Antigen (PA) protein of Bacillus anthracis and Staphylococcal Enterotoxin B (SEB) will be presented. Recent highlights of on cell vs. off-cell affinity behavior and correlation of the results with advanced docking simulations on the protein-peptide system(s) are included. The potential of this technology and approach to enable rapid development of a new affinity reagent with unprecedented speed (less than one week) would allow for rapid response to new and constantly emerging threats.

Thermodynamic basis for engineering high-affinity, high-specificity binding-induced DNA clamp nanoswitches.

PubMed

Idili, Andrea; Plaxco, Kevin W; Vallée-Bélisle, Alexis; Ricci, Francesco

2013-12-23

Naturally occurring chemoreceptors almost invariably employ structure-switching mechanisms, an observation that has inspired the use of biomolecular switches in a wide range of artificial technologies in the areas of diagnostics, imaging, and synthetic biology. In one mechanism for generating such behavior, clamp-based switching, binding occurs via the clamplike embrace of two recognition elements onto a single target molecule. In addition to coupling recognition with a large conformational change, this mechanism offers a second advantage: it improves both affinity and specificity simultaneously. To explore the physics of such switches we have dissected here the thermodynamics of a clamp-switch that recognizes a target DNA sequence through both Watson-Crick base pairing and triplex-forming Hoogsteen interactions. When compared to the equivalent linear DNA probe (which relies solely on Watson-Crick interactions), the extra Hoogsteen interactions in the DNA clamp-switch increase the probe's affinity for its target by ∼0.29 ± 0.02 kcal/mol/base. The Hoogsteen interactions of the clamp-switch likewise provide an additional specificity check that increases the discrimination efficiency toward a single-base mismatch by 1.2 ± 0.2 kcal/mol. This, in turn, leads to a 10-fold improvement in the width of the "specificity window" of this probe relative to that of the equivalent linear probe. Given these attributes, clamp-switches should be of utility not only for sensing applications but also, in the specific field of DNA nanotechnology, for applications calling for a better control over the building of nanostructures and nanomachines.

Relevance of protein-protein interactions on the biological identity of nanoparticles.

PubMed

Vasti, Cecilia; Bonnet, Laura V; Galiano, Mauricio R; Rojas, Ricardo; Giacomelli, Carla E

2018-06-01

Considering that the use of nanoparticles (NPs) as carriers of therapeutic or theranostic agents has increased in the last years, it is mandatory to understand the interaction between NPs and living systems. In contact with biological fluids, the NPs (synthetic identity) are covered with biomolecules that form a protein corona, which defines the biological identity. It is well known that the protein corona formation is mediated by non-specific physical interactions, but protein-protein interactions (PPI), involving specific recognition sites of the polypeptides, are also involved. This work explores the relationship between the synthetic and biological identities of layered double hydroxides nanoparticles (LDH-NPs) and the effect of the protein corona on the cellular response. With such a purpose, the synthetic identity was modified by coating LDH-NPs with either a single protein or a complex mixture of them, followed by the characterization of the protein corona formed in a commonly used cell culture medium. A proteomic approach was used to identify the protein corona molecules and the PPI network was constructed with a novel bioinformatic tool. The coating on LDH-NPs defines the biological identity in such a way that the composition of the protein corona as well as PPI are changed. Electrostatic interactions appear not to be the only driving force regulating the interactions between NPs, proteins and cells since the specific recognition also play a fundamental role. However, the biological identity of LDH-NPs does not affect the interactions with cells that shows negligible cytotoxicity and high internalization levels. Copyright © 2018 Elsevier B.V. All rights reserved.

An Environmental Assessment of United States Drinking Water Watersheds

EPA Science Inventory

There is an emerging recognition that natural lands and their conservation are important elements of a sustainable drinking water infrastructure. We conducted a national, watershed-level environmental assessment of drinking water watersheds using data on land cover, hydrography a...

Finite element analysis and full-scale testing of locomotive crashworthy components

DOT National Transportation Integrated Search

2013-04-15

The Office of Research and Development of the Federal Railroad Administration (FRA) and the Volpe Center are continuing to evaluate new technologies for increasing the safety of passengers and operators in rail equipment. In recognition of the import...

Amplifying Electrochemical Indicators

NASA Technical Reports Server (NTRS)

Fan, Wenhong; Li, Jun; Han, Jie

2004-01-01

Dendrimeric reporter compounds have been invented for use in sensing and amplifying electrochemical signals from molecular recognition events that involve many chemical and biological entities. These reporter compounds can be formulated to target specific molecules or molecular recognition events. They can also be formulated to be, variously, hydrophilic or amphiphilic so that they are suitable for use at interfaces between (1) aqueous solutions and (2) electrodes connected to external signal-processing electronic circuits. The invention of these reporter compounds is expected to enable the development of highly miniaturized, low-power-consumption, relatively inexpensive, mass-producible sensor units for diverse applications.

Primary Stability Recognition of the Newly Designed Cementless Femoral Stem Using Digital Signal Processing

PubMed Central

Salleh, Sh-Hussain; Hamedi, Mahyar; Zulkifly, Ahmad Hafiz; Lee, Muhammad Hisyam; Mohd Noor, Alias; Harris, Arief Ruhullah A.; Abdul Majid, Norazman

2014-01-01

Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems. The correlation of experimental validation with finite element analysis (FEA) is commonly used to evaluate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM) to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct transducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes. The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion. This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing. PMID:24800230

Primary stability recognition of the newly designed cementless femoral stem using digital signal processing.

PubMed

Baharuddin, Mohd Yusof; Salleh, Sh-Hussain; Hamedi, Mahyar; Zulkifly, Ahmad Hafiz; Lee, Muhammad Hisyam; Mohd Noor, Alias; Harris, Arief Ruhullah A; Abdul Majid, Norazman

2014-01-01

Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems. The correlation of experimental validation with finite element analysis (FEA) is commonly used to evaluate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM) to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct transducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes. The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion. This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing.

Nuclear microscopy in trace-element biology — from cellular studies to the clinic

NASA Astrophysics Data System (ADS)

Lindh, Ulf

1993-05-01

The concentration and distribution of trace and major elements in cells are of great interest in cell biology. PIXE can provide elemental concentrations in the bulk of cells or organelles as other bulk techniques such as atomic absorption spectrophotometry and nuclear activation analysis. Supplementary information, perhaps more exciting, on the intracellular distributions of trace elements can be provided using nuclear microscopy. Intracellular distributions of trace elements in normal and malignant cells are presented. The toxicity of mercury and cadmium can be prevented by supplementation of the essential trace element selenium. Some results from an experimental animal model are discussed. The intercellular distribution of major and trace elements in isolated blood cells, as revealed by nuclear microscopy, provides useful clinical information. Examples are given concerning inflammatory connective-tissue diseases and the chronic fatigue syndrome.

Elements of episodic-like memory in animal models.

PubMed

Crystal, Jonathon D

2009-03-01

Representations of unique events from one's past constitute the content of episodic memories. A number of studies with non-human animals have revealed that animals remember specific episodes from their past (referred to as episodic-like memory). The development of animal models of memory holds enormous potential for gaining insight into the biological bases of human memory. Specifically, given the extensive knowledge of the rodent brain, the development of rodent models of episodic memory would open new opportunities to explore the neuroanatomical, neurochemical, neurophysiological, and molecular mechanisms of memory. Development of such animal models holds enormous potential for studying functional changes in episodic memory in animal models of Alzheimer's disease, amnesia, and other human memory pathologies. This article reviews several approaches that have been used to assess episodic-like memory in animals. The approaches reviewed include the discrimination of what, where, and when in a radial arm maze, dissociation of recollection and familiarity, object recognition, binding, unexpected questions, and anticipation of a reproductive state. The diversity of approaches may promote the development of converging lines of evidence on the difficult problem of assessing episodic-like memory in animals.

Flexible regulation of DNA displacement reaction through nucleic acid-recognition enzyme and its application in keypad lock system and biosensing.

PubMed

Li, Chao; Shi, Liu; Tao, Yaqin; Mao, Xiaoxia; Xiang, Yang; Li, Genxi

2017-08-30

Toehold-mediated DNA strand displacement reaction (SDR) plays pivotal roles for the construction of diverse dynamic DNA nanodevices. To date, many elements have been introduced into SDR system to achieve controllable activation and fine regulation. However, as the most relevant stimuli for nucleic acid involved reaction, nucleic acid-recognizing enzymes (NAEs) have received nearly no attention so far despite SDR often takes place in NAEs-enriched environment (i.e., biological fluids). Herein, we report a set of NAEs-controlled SDR strategies, which take full advantage of NAEs' properties. In this study, three different kinds of enzymes belonging to several classes (i.e., exonuclease, endonuclease and polymerase) have been used to activate or inhibit SDR, and more importantly, some mechanisms behind these strategies on how NAEs affect SDR have also been revealed. The exploration to use NAEs as possible cues to operate SDR will expand the available toolbox to build novel stimuli-fueled DNA nanodevices and could open the door to many applications including enzyme-triggered biocomputing and biosensing.

Capturing microRNA targets using an RNA-induced silencing complex (RISC)-trap approach

PubMed Central

Cambronne, Xiaolu A.; Shen, Rongkun; Auer, Paul L.; Goodman, Richard H.

2012-01-01

Identifying targets is critical for understanding the biological effects of microRNA (miRNA) expression. The challenge lies in characterizing the cohort of targets for a specific miRNA, especially when targets are being actively down-regulated in miRNA– RNA-induced silencing complex (RISC)–messengerRNA (mRNA) complexes. We have developed a robust and versatile strategy called RISCtrap to stabilize and purify targets from this transient interaction. Its utility was demonstrated by determining specific high-confidence target datasets for miR-124, miR-132, and miR-181 that contained known and previously unknown transcripts. Two previously unknown miR-132 targets identified with RISCtrap, adaptor protein CT10 regulator of kinase 1 (CRK1) and tight junction-associated protein 1 (TJAP1), were shown to be endogenously regulated by miR-132 in adult mouse forebrain. The datasets, moreover, differed in the number of targets and in the types and frequency of microRNA recognition element (MRE) motifs, thus revealing a previously underappreciated level of specificity in the target sets regulated by individual miRNAs. PMID:23184980

Capturing microRNA targets using an RNA-induced silencing complex (RISC)-trap approach.

PubMed

Cambronne, Xiaolu A; Shen, Rongkun; Auer, Paul L; Goodman, Richard H

2012-12-11

Identifying targets is critical for understanding the biological effects of microRNA (miRNA) expression. The challenge lies in characterizing the cohort of targets for a specific miRNA, especially when targets are being actively down-regulated in miRNA- RNA-induced silencing complex (RISC)-messengerRNA (mRNA) complexes. We have developed a robust and versatile strategy called RISCtrap to stabilize and purify targets from this transient interaction. Its utility was demonstrated by determining specific high-confidence target datasets for miR-124, miR-132, and miR-181 that contained known and previously unknown transcripts. Two previously unknown miR-132 targets identified with RISCtrap, adaptor protein CT10 regulator of kinase 1 (CRK1) and tight junction-associated protein 1 (TJAP1), were shown to be endogenously regulated by miR-132 in adult mouse forebrain. The datasets, moreover, differed in the number of targets and in the types and frequency of microRNA recognition element (MRE) motifs, thus revealing a previously underappreciated level of specificity in the target sets regulated by individual miRNAs.

Nucleic Acids for Ultra-Sensitive Protein Detection

PubMed Central

Janssen, Kris P. F.; Knez, Karel; Spasic, Dragana; Lammertyn, Jeroen

2013-01-01

Major advancements in molecular biology and clinical diagnostics cannot be brought about strictly through the use of genomics based methods. Improved methods for protein detection and proteomic screening are an absolute necessity to complement to wealth of information offered by novel, high-throughput sequencing technologies. Only then will it be possible to advance insights into clinical processes and to characterize the importance of specific protein biomarkers for disease detection or the realization of “personalized medicine”. Currently however, large-scale proteomic information is still not as easily obtained as its genomic counterpart, mainly because traditional antibody-based technologies struggle to meet the stringent sensitivity and throughput requirements that are required whereas mass-spectrometry based methods might be burdened by significant costs involved. However, recent years have seen the development of new biodetection strategies linking nucleic acids with existing antibody technology or replacing antibodies with oligonucleotide recognition elements altogether. These advancements have unlocked many new strategies to lower detection limits and dramatically increase throughput of protein detection assays. In this review, an overview of these new strategies will be given. PMID:23337338

Polypeptide Functional Surface for the Aptamer Immobilization: Electrochemical Cocaine Biosensing.

PubMed

Bozokalfa, Guliz; Akbulut, Huseyin; Demir, Bilal; Guler, Emine; Gumus, Z Pınar; Odaci Demirkol, Dilek; Aldemir, Ebru; Yamada, Shuhei; Endo, Takeshi; Coskunol, Hakan; Timur, Suna; Yagci, Yusuf

2016-04-05

Electroanalytical technologies as a beneficial subject of modern analytical chemistry can play an important role for abused drug analysis which is crucial for both legal and social respects. This article reports a novel aptamer-based biosensing procedure for cocaine analysis by combining the advantages of aptamers as selective recognition elements with the well-known advantages of biosensor systems such as the possibility of miniaturization and automation, easy fabrication and modification, low cost, and sensitivity. In order to construct the aptasensor platform, first, polythiophene bearing polyalanine homopeptide side chains (PT-Pala) was electrochemically coated onto the surface of an electrode and then cocaine aptamer was attached to the polymer via covalent conjugation chemistry. The stepwise modification of the surface was confirmed by electrochemical characterization. The designed biosensing system was applied for the detection of cocaine and its metabolite, benzoylecgonine (BE), which exhibited a linear correlation in the range from 2.5 up to 10 nM and 0.5 up to 50 μM for cocaine and BE, respectively. In order to expand its practical application, the proposed method was successfully tested for the analysis of synthetic biological fluids.

Ionophore-based optical nanosensors incorporating hydrophobic carbon dots and a pH-sensitive quencher dye for sodium detection.

PubMed

Galyean, A A; Behr, M R; Cash, K J

2018-01-21

Nanosensors present a biological monitoring method that is biocompatible, reversible, and nano-scale, and they offer many advantages over traditional organic indicators. Typical ionophore-based nanosensors incorporate nile-blue derivative pH indicators but suffer from photobleaching while quantum dot alternatives pose a potential toxicity risk. In order to address this challenge, sodium selective nanosensors containing carbon dots and a pH-sensitive quencher molecule were developed based on an ion-exchange theory and a decoupled recognition element from the pH indicator. Carbon dots were synthesized and integrated into nanosensors containing a pH-indicator, an analyte-binding ligand (ionophore), and a charge-balancing additive. These nanosensors are ion-selective against potassium (selectivity coefficient of 0.4) and lithium (selectivity coefficient of 0.9). Reversible nanosensor response to sodium is also demonstrated. The carbon dot nanosensors are resistant to changes in optical properties for at least 12 h and display stable selectivity to physiologically-relevant sodium (alpha = 0.5 of 200 mM NaCl) for a minimum of 6 days.

Is synthetic biology mechanical biology?

PubMed

Holm, Sune

2015-12-01

A widespread and influential characterization of synthetic biology emphasizes that synthetic biology is the application of engineering principles to living systems. Furthermore, there is a strong tendency to express the engineering approach to organisms in terms of what seems to be an ontological claim: organisms are machines. In the paper I investigate the ontological and heuristic significance of the machine analogy in synthetic biology. I argue that the use of the machine analogy and the aim of producing rationally designed organisms does not necessarily imply a commitment to mechanical biology. The ideal of applying engineering principles to biology is best understood as expressing recognition of the machine-unlikeness of natural organisms and the limits of human cognition. The paper suggests an interpretation of the identification of organisms with machines in synthetic biology according to which it expresses a strategy for representing, understanding, and constructing living systems that are more machine-like than natural organisms.

Unsupervised learning of digit recognition using spike-timing-dependent plasticity

PubMed Central

Diehl, Peter U.; Cook, Matthew

2015-01-01

In order to understand how the mammalian neocortex is performing computations, two things are necessary; we need to have a good understanding of the available neuronal processing units and mechanisms, and we need to gain a better understanding of how those mechanisms are combined to build functioning systems. Therefore, in recent years there is an increasing interest in how spiking neural networks (SNN) can be used to perform complex computations or solve pattern recognition tasks. However, it remains a challenging task to design SNNs which use biologically plausible mechanisms (especially for learning new patterns), since most such SNN architectures rely on training in a rate-based network and subsequent conversion to a SNN. We present a SNN for digit recognition which is based on mechanisms with increased biological plausibility, i.e., conductance-based instead of current-based synapses, spike-timing-dependent plasticity with time-dependent weight change, lateral inhibition, and an adaptive spiking threshold. Unlike most other systems, we do not use a teaching signal and do not present any class labels to the network. Using this unsupervised learning scheme, our architecture achieves 95% accuracy on the MNIST benchmark, which is better than previous SNN implementations without supervision. The fact that we used no domain-specific knowledge points toward the general applicability of our network design. Also, the performance of our network scales well with the number of neurons used and shows similar performance for four different learning rules, indicating robustness of the full combination of mechanisms, which suggests applicability in heterogeneous biological neural networks. PMID:26941637

miREE: miRNA recognition elements ensemble

PubMed Central

2011-01-01

Background Computational methods for microRNA target prediction are a fundamental step to understand the miRNA role in gene regulation, a key process in molecular biology. In this paper we present miREE, a novel microRNA target prediction tool. miREE is an ensemble of two parts entailing complementary but integrated roles in the prediction. The Ab-Initio module leverages upon a genetic algorithmic approach to generate a set of candidate sites on the basis of their microRNA-mRNA duplex stability properties. Then, a Support Vector Machine (SVM) learning module evaluates the impact of microRNA recognition elements on the target gene. As a result the prediction takes into account information regarding both miRNA-target structural stability and accessibility. Results The proposed method significantly improves the state-of-the-art prediction tools in terms of accuracy with a better balance between specificity and sensitivity, as demonstrated by the experiments conducted on several large datasets across different species. miREE achieves this result by tackling two of the main challenges of current prediction tools: (1) The reduced number of false positives for the Ab-Initio part thanks to the integration of a machine learning module (2) the specificity of the machine learning part, obtained through an innovative technique for rich and representative negative records generation. The validation was conducted on experimental datasets where the miRNA:mRNA interactions had been obtained through (1) direct validation where even the binding site is provided, or through (2) indirect validation, based on gene expression variations obtained from high-throughput experiments where the specific interaction is not validated in detail and consequently the specific binding site is not provided. Conclusions The coupling of two parts: a sensitive Ab-Initio module and a selective machine learning part capable of recognizing the false positives, leads to an improved balance between sensitivity and specificity. miREE obtains a reasonable trade-off between filtering false positives and identifying targets. miREE tool is available online at http://didattica-online.polito.it/eda/miREE/ PMID:22115078

Optimization of biological sulfide removal in a CSTR bioreactor.

PubMed

Roosta, Aliakbar; Jahanmiri, Abdolhossein; Mowla, Dariush; Niazi, Ali; Sotoodeh, Hamidreza

2012-08-01

In this study, biological sulfide removal from natural gas in a continuous bioreactor is investigated for estimation of the optimal operational parameters. According to the carried out reactions, sulfide can be converted to elemental sulfur, sulfate, thiosulfate, and polysulfide, of which elemental sulfur is the desired product. A mathematical model is developed and was used for investigation of the effect of various parameters on elemental sulfur selectivity. The results of the simulation show that elemental sulfur selectivity is a function of dissolved oxygen, sulfide load, pH, and concentration of bacteria. Optimal parameter values are calculated for maximum elemental sulfur selectivity by using genetic algorithm as an adaptive heuristic search. In the optimal conditions, 87.76% of sulfide loaded to the bioreactor is converted to elemental sulfur.

Sibling Rivalry in Myxococcus xanthus Is Mediated by Kin Recognition and a Polyploid Prophage.

PubMed

Dey, Arup; Vassallo, Christopher N; Conklin, Austin C; Pathak, Darshankumar T; Troselj, Vera; Wall, Daniel

2016-01-19

Myxobacteria form complex social communities that elicit multicellular behaviors. One such behavior is kin recognition, in which cells identify siblings via their polymorphic TraA cell surface receptor, to transiently fuse outer membranes and exchange their contents. In addition, outer membrane exchange (OME) regulates behaviors, such as inhibition of wild-type Myxococcus xanthus (DK1622) from swarming. Here we monitored the fate of motile cells and surprisingly found they were killed by nonmotile siblings. The kill phenotype required OME (i.e., was TraA dependent). The genetic basis of killing was traced to ancestral strains used to construct DK1622. Specifically, the kill phenotype mapped to a large "polyploid prophage," Mx alpha. Sensitive strains contained a 200-kb deletion that removed two of three Mx alpha units. To explain these results, we suggest that Mx alpha expresses a toxin-antitoxin cassette that uses the OME machinery of M. xanthus to transfer a toxin that makes the population "addicted" to Mx alpha. Thus, siblings that lost Mx alpha units (no immunity) are killed by cells that harbor the element. To test this, an Mx alpha-harboring laboratory strain was engineered (by traA allele swap) to recognize a closely related species, Myxococcus fulvus. As a result, M. fulvus, which lacks Mx alpha, was killed. These TraA-mediated antagonisms provide an explanation for how kin recognition specificity might have evolved in myxobacteria. That is, recognition specificity is determined by polymorphisms in traA, which we hypothesize were selected for because OME with non-kin leads to lethal outcomes. The transition from single cell to multicellular life is considered a major evolutionary event. Myxobacteria have successfully made this transition. For example, in response to starvation, individual cells aggregate into multicellular fruiting bodies wherein cells differentiate into spores. To build fruits, cells need to recognize their siblings, and in part, this is mediated by the TraA cell surface receptor. Surprisingly, we report that TraA recognition can also involve sibling killing. We show that killing originates from a prophage-like element that has apparently hijacked the TraA system to deliver a toxin to kin. We hypothesize that this killing system has imposed selective pressures on kin recognition, which in turn has resulted in TraA polymorphisms and hence many different recognition groups. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Sibling Rivalry in Myxococcus xanthus Is Mediated by Kin Recognition and a Polyploid Prophage

PubMed Central

Dey, Arup; Vassallo, Christopher N.; Conklin, Austin C.; Pathak, Darshankumar T.; Troselj, Vera

2016-01-01

ABSTRACT Myxobacteria form complex social communities that elicit multicellular behaviors. One such behavior is kin recognition, in which cells identify siblings via their polymorphic TraA cell surface receptor, to transiently fuse outer membranes and exchange their contents. In addition, outer membrane exchange (OME) regulates behaviors, such as inhibition of wild-type Myxococcus xanthus (DK1622) from swarming. Here we monitored the fate of motile cells and surprisingly found they were killed by nonmotile siblings. The kill phenotype required OME (i.e., was TraA dependent). The genetic basis of killing was traced to ancestral strains used to construct DK1622. Specifically, the kill phenotype mapped to a large “polyploid prophage,” Mx alpha. Sensitive strains contained a 200-kb deletion that removed two of three Mx alpha units. To explain these results, we suggest that Mx alpha expresses a toxin-antitoxin cassette that uses the OME machinery of M. xanthus to transfer a toxin that makes the population “addicted” to Mx alpha. Thus, siblings that lost Mx alpha units (no immunity) are killed by cells that harbor the element. To test this, an Mx alpha-harboring laboratory strain was engineered (by traA allele swap) to recognize a closely related species, Myxococcus fulvus. As a result, M. fulvus, which lacks Mx alpha, was killed. These TraA-mediated antagonisms provide an explanation for how kin recognition specificity might have evolved in myxobacteria. That is, recognition specificity is determined by polymorphisms in traA, which we hypothesize were selected for because OME with non-kin leads to lethal outcomes. IMPORTANCE The transition from single cell to multicellular life is considered a major evolutionary event. Myxobacteria have successfully made this transition. For example, in response to starvation, individual cells aggregate into multicellular fruiting bodies wherein cells differentiate into spores. To build fruits, cells need to recognize their siblings, and in part, this is mediated by the TraA cell surface receptor. Surprisingly, we report that TraA recognition can also involve sibling killing. We show that killing originates from a prophage-like element that has apparently hijacked the TraA system to deliver a toxin to kin. We hypothesize that this killing system has imposed selective pressures on kin recognition, which in turn has resulted in TraA polymorphisms and hence many different recognition groups. PMID:26787762

[The determination of the natural content of chemical elements in human biological objects (liver, kidney, stomach) by mass spectrometry with inductively coupled plasma].

PubMed

Luzanova, I S; Svetlolobov, D Iu; Zorin, Iu V

2014-01-01

The objective of the present work was to continue the studies of the sites of concentration of the chemical elements corresponding to normal homeostasis in human biological objects by mass spectrometry with inductively coupled plasma. The study yielded the data on the natural content of 27 elements in the cadaveric liver, kidney, and stomach. It is recommended to use these findings as the reference parameters corresponding to normal homeostasis.

A Review of Subsequence Time Series Clustering

PubMed Central

Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies. PMID:25140332

A review of subsequence time series clustering.

PubMed

Zolhavarieh, Seyedjamal; Aghabozorgi, Saeed; Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies.

Character recognition from trajectory by recurrent spiking neural networks.

PubMed

Jiangrong Shen; Kang Lin; Yueming Wang; Gang Pan

2017-07-01

Spiking neural networks are biologically plausible and power-efficient on neuromorphic hardware, while recurrent neural networks have been proven to be efficient on time series data. However, how to use the recurrent property to improve the performance of spiking neural networks is still a problem. This paper proposes a recurrent spiking neural network for character recognition using trajectories. In the network, a new encoding method is designed, in which varying time ranges of input streams are used in different recurrent layers. This is able to improve the generalization ability of our model compared with general encoding methods. The experiments are conducted on four groups of the character data set from University of Edinburgh. The results show that our method can achieve a higher average recognition accuracy than existing methods.

Finite element model updating and damage detection for bridges using vibration measurement.

DOT National Transportation Integrated Search

2013-12-01

In this report, the results of a study on developing a damage detection methodology based on Statistical Pattern Recognition are : presented. This methodology uses a new damage sensitive feature developed in this study that relies entirely on modal :...

Biological monitoring of welders' exposure to chromium, molybdenum, tungsten and vanadium.

PubMed

Ellingsen, Dag G; Chashchin, Maxim; Berlinger, Balazs; Fedorov, Vladimir; Chashchin, Valery; Thomassen, Yngvar

2017-05-01

Welders are exposed to a number of metallic elements during work. Bioaccessability, that is important for element uptake, has been little studied. This study addresses bioaccessability and uptake of chromium (Cr), molybdenum (Mo), tungsten (W) and vanadium (V) among welders. Bioaccessability of Cr, Mo, V and W was studied in airborne particulate matter collected by personal sampling of the workroom air among shipyard welders by using the lung lining fluid simulant Hatch solution. Associations between concentrations of Hatch soluble and non-soluble elements (Hatch sol and Hatch non-sol ) and concentrations of the four elements in whole blood, serum, blood cells and urine were studied. Air concentrations of the four elements were low. Only a small fraction of Cr, V and W was Hatch sol , while similar amounts of Mo were Hatch sol and Hatch non-sol . Welders (N=70) had statistically significantly higher concentrations of all four elements in urine and serum when compared to referents (N=74). Highly statistically significant associations were observed between urinary W and Hatch sol W (p<0.001) and serum V and Hatch sol V (p<0.001), in particular when air samples collected the day before collection of biological samples were considered. Associations between Hatch sol elements in air and their biological concentrations were higher than when Hatch non-sol concentrations were considered. Associations were generally higher when air samples collected the day before biological sampling were considered as compared to air samples collected two days before. Copyright © 2017 Elsevier GmbH. All rights reserved.

Paradigms and progress in vocal fold restoration.

PubMed

Ford, Charles N

2008-09-01

Science advances occur through orderly steps, puzzle-solving leaps, or divergences from the accepted disciplinary matrix that occasionally result in a revolutionary paradigm shift. Key advances must overcome bias, criticism, and rejection. Examples in biological science include use of embryonic stem cells, recognition of Helicobacter pylori in the etiology of ulcer disease, and the evolution of species. Our work in vocal fold restoration reflects these patterns. We progressed through phases of tissue replacement with fillers and biological implants, to current efforts at vocal fold regeneration through tissue engineering, and face challenges of a new "systems biology" paradigm embracing genomics and proteomics.

Entropy in molecular recognition by proteins

PubMed Central

Caro, José A.; Harpole, Kyle W.; Kasinath, Vignesh; Lim, Jackwee; Granja, Jeffrey; Valentine, Kathleen G.; Sharp, Kim A.

2017-01-01

Molecular recognition by proteins is fundamental to molecular biology. Dissection of the thermodynamic energy terms governing protein–ligand interactions has proven difficult, with determination of entropic contributions being particularly elusive. NMR relaxation measurements have suggested that changes in protein conformational entropy can be quantitatively obtained through a dynamical proxy, but the generality of this relationship has not been shown. Twenty-eight protein–ligand complexes are used to show a quantitative relationship between measures of fast side-chain motion and the underlying conformational entropy. We find that the contribution of conformational entropy can range from favorable to unfavorable, which demonstrates the potential of this thermodynamic variable to modulate protein–ligand interactions. For about one-quarter of these complexes, the absence of conformational entropy would render the resulting affinity biologically meaningless. The dynamical proxy for conformational entropy or “entropy meter” also allows for refinement of the contributions of solvent entropy and the loss in rotational-translational entropy accompanying formation of high-affinity complexes. Furthermore, structure-based application of the approach can also provide insight into long-lived specific water–protein interactions that escape the generic treatments of solvent entropy based simply on changes in accessible surface area. These results provide a comprehensive and unified view of the general role of entropy in high-affinity molecular recognition by proteins. PMID:28584100

Entropy in molecular recognition by proteins.

PubMed

Caro, José A; Harpole, Kyle W; Kasinath, Vignesh; Lim, Jackwee; Granja, Jeffrey; Valentine, Kathleen G; Sharp, Kim A; Wand, A Joshua

2017-06-20

Molecular recognition by proteins is fundamental to molecular biology. Dissection of the thermodynamic energy terms governing protein-ligand interactions has proven difficult, with determination of entropic contributions being particularly elusive. NMR relaxation measurements have suggested that changes in protein conformational entropy can be quantitatively obtained through a dynamical proxy, but the generality of this relationship has not been shown. Twenty-eight protein-ligand complexes are used to show a quantitative relationship between measures of fast side-chain motion and the underlying conformational entropy. We find that the contribution of conformational entropy can range from favorable to unfavorable, which demonstrates the potential of this thermodynamic variable to modulate protein-ligand interactions. For about one-quarter of these complexes, the absence of conformational entropy would render the resulting affinity biologically meaningless. The dynamical proxy for conformational entropy or "entropy meter" also allows for refinement of the contributions of solvent entropy and the loss in rotational-translational entropy accompanying formation of high-affinity complexes. Furthermore, structure-based application of the approach can also provide insight into long-lived specific water-protein interactions that escape the generic treatments of solvent entropy based simply on changes in accessible surface area. These results provide a comprehensive and unified view of the general role of entropy in high-affinity molecular recognition by proteins.

Automated recognition and tracking of aerosol threat plumes with an IR camera pod

NASA Astrophysics Data System (ADS)

Fauth, Ryan; Powell, Christopher; Gruber, Thomas; Clapp, Dan

2012-06-01

Protection of fixed sites from chemical, biological, or radiological aerosol plume attacks depends on early warning so that there is time to take mitigating actions. Early warning requires continuous, autonomous, and rapid coverage of large surrounding areas; however, this must be done at an affordable cost. Once a potential threat plume is detected though, a different type of sensor (e.g., a more expensive, slower sensor) may be cued for identification purposes, but the problem is to quickly identify all of the potential threats around the fixed site of interest. To address this problem of low cost, persistent, wide area surveillance, an IR camera pod and multi-image stitching and processing algorithms have been developed for automatic recognition and tracking of aerosol plumes. A rugged, modular, static pod design, which accommodates as many as four micro-bolometer IR cameras for 45deg to 180deg of azimuth coverage, is presented. Various OpenCV1 based image-processing algorithms, including stitching of multiple adjacent FOVs, recognition of aerosol plume objects, and the tracking of aerosol plumes, are presented using process block diagrams and sample field test results, including chemical and biological simulant plumes. Methods for dealing with the background removal, brightness equalization between images, and focus quality for optimal plume tracking are also discussed.

DNA recognition by synthetic constructs.

PubMed

Pazos, Elena; Mosquera, Jesús; Vázquez, M Eugenio; Mascareñas, José L

2011-09-05

The interaction of transcription factors with specific DNA sites is key for the regulation of gene expression. Despite the availability of a large body of structural data on protein-DNA complexes, we are still far from fully understanding the molecular and biophysical bases underlying such interactions. Therefore, the development of non-natural agents that can reproduce the DNA-recognition properties of natural transcription factors remains a major and challenging goal in chemical biology. In this review we summarize the basics of double-stranded DNA recognition by transcription factors, and describe recent developments in the design and preparation of synthetic DNA binders. We mainly focus on synthetic peptides that have been designed by following the DNA interaction of natural proteins, and we discuss how the tools of organic synthesis can be used to make artificial constructs equipped with functionalities that introduce additional properties to the recognition process, such as sensing and controllability. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hierarchical ensemble of global and local classifiers for face recognition.

PubMed

Su, Yu; Shan, Shiguang; Chen, Xilin; Gao, Wen

2009-08-01

In the literature of psychophysics and neurophysiology, many studies have shown that both global and local features are crucial for face representation and recognition. This paper proposes a novel face recognition method which exploits both global and local discriminative features. In this method, global features are extracted from the whole face images by keeping the low-frequency coefficients of Fourier transform, which we believe encodes the holistic facial information, such as facial contour. For local feature extraction, Gabor wavelets are exploited considering their biological relevance. After that, Fisher's linear discriminant (FLD) is separately applied to the global Fourier features and each local patch of Gabor features. Thus, multiple FLD classifiers are obtained, each embodying different facial evidences for face recognition. Finally, all these classifiers are combined to form a hierarchical ensemble classifier. We evaluate the proposed method using two large-scale face databases: FERET and FRGC version 2.0. Experiments show that the results of our method are impressively better than the best known results with the same evaluation protocol.

Exploring Protein-Peptide Recognition Pathways Using a Supervised Molecular Dynamics Approach.

PubMed

Salmaso, Veronica; Sturlese, Mattia; Cuzzolin, Alberto; Moro, Stefano

2017-04-04

Peptides have gained increased interest as therapeutic agents during recent years. The high specificity and relatively low toxicity of peptide drugs derive from their extremely tight binding to their targets. Indeed, understanding the molecular mechanism of protein-peptide recognition has important implications in the fields of biology, medicine, and pharmaceutical sciences. Even if crystallography and nuclear magnetic resonance are offering valuable atomic insights into the assembling of the protein-peptide complexes, the mechanism of their recognition and binding events remains largely unclear. In this work we report, for the first time, the use of a supervised molecular dynamics approach to explore the possible protein-peptide binding pathways within a timescale reduced up to three orders of magnitude compared with classical molecular dynamics. The better and faster understating of the protein-peptide recognition pathways could be very beneficial in enlarging the applicability of peptide-based drug design approaches in several biotechnological and pharmaceutical fields. Copyright © 2017 Elsevier Ltd. All rights reserved.

Autonomous learning in gesture recognition by using lobe component analysis

NASA Astrophysics Data System (ADS)

Lu, Jian; Weng, Juyang

2007-02-01

Gesture recognition is a new human-machine interface method implemented by pattern recognition(PR).In order to assure robot safety when gesture is used in robot control, it is required to implement the interface reliably and accurately. Similar with other PR applications, 1) feature selection (or model establishment) and 2) training from samples, affect the performance of gesture recognition largely. For 1), a simple model with 6 feature points at shoulders, elbows, and hands, is established. The gestures to be recognized are restricted to still arm gestures, and the movement of arms is not considered. These restrictions are to reduce the misrecognition, but are not so unreasonable. For 2), a new biological network method, called lobe component analysis(LCA), is used in unsupervised learning. Lobe components, corresponding to high-concentrations in probability of the neuronal input, are orientation selective cells follow Hebbian rule and lateral inhibition. Due to the advantage of LCA method for balanced learning between global and local features, large amount of samples can be used in learning efficiently.

Identifying and detecting facial expressions of emotion in peripheral vision.

PubMed

Smith, Fraser W; Rossit, Stephanie

2018-01-01

Facial expressions of emotion are signals of high biological value. Whilst recognition of facial expressions has been much studied in central vision, the ability to perceive these signals in peripheral vision has only seen limited research to date, despite the potential adaptive advantages of such perception. In the present experiment, we investigate facial expression recognition and detection performance for each of the basic emotions (plus neutral) at up to 30 degrees of eccentricity. We demonstrate, as expected, a decrease in recognition and detection performance with increasing eccentricity, with happiness and surprised being the best recognized expressions in peripheral vision. In detection however, while happiness and surprised are still well detected, fear is also a well detected expression. We show that fear is a better detected than recognized expression. Our results demonstrate that task constraints shape the perception of expression in peripheral vision and provide novel evidence that detection and recognition rely on partially separate underlying mechanisms, with the latter more dependent on the higher spatial frequency content of the face stimulus.

The Potential of Using Brain Images for Authentication

PubMed Central

Zhou, Zongtan; Shen, Hui; Hu, Dewen

2014-01-01

Biometric recognition (also known as biometrics) refers to the automated recognition of individuals based on their biological or behavioral traits. Examples of biometric traits include fingerprint, palmprint, iris, and face. The brain is the most important and complex organ in the human body. Can it be used as a biometric trait? In this study, we analyze the uniqueness of the brain and try to use the brain for identity authentication. The proposed brain-based verification system operates in two stages: gray matter extraction and gray matter matching. A modified brain segmentation algorithm is implemented for extracting gray matter from an input brain image. Then, an alignment-based matching algorithm is developed for brain matching. Experimental results on two data sets show that the proposed brain recognition system meets the high accuracy requirement of identity authentication. Though currently the acquisition of the brain is still time consuming and expensive, brain images are highly unique and have the potential possibility for authentication in view of pattern recognition. PMID:25126604

Elucidating Mechanisms of Molecular Recognition Between Human Argonaute and miRNA Using Computational Approaches.

PubMed

Jiang, Hanlun; Zhu, Lizhe; Héliou, Amélie; Gao, Xin; Bernauer, Julie; Huang, Xuhui

2017-01-01

MicroRNA (miRNA) and Argonaute (AGO) protein together form the RNA-induced silencing complex (RISC) that plays an essential role in the regulation of gene expression. Elucidating the underlying mechanism of AGO-miRNA recognition is thus of great importance not only for the in-depth understanding of miRNA function but also for inspiring new drugs targeting miRNAs. In this chapter we introduce a combined computational approach of molecular dynamics (MD) simulations, Markov state models (MSMs), and protein-RNA docking to investigate AGO-miRNA recognition. Constructed from MD simulations, MSMs can elucidate the conformational dynamics of AGO at biologically relevant timescales. Protein-RNA docking can then efficiently identify the AGO conformations that are geometrically accessible to miRNA. Using our recent work on human AGO2 as an example, we explain the rationale and the workflow of our method in details. This combined approach holds great promise to complement experiments in unraveling the mechanisms of molecular recognition between large, flexible, and complex biomolecules.

The potential of using brain images for authentication.

PubMed

Chen, Fanglin; Zhou, Zongtan; Shen, Hui; Hu, Dewen

2014-01-01

Biometric recognition (also known as biometrics) refers to the automated recognition of individuals based on their biological or behavioral traits. Examples of biometric traits include fingerprint, palmprint, iris, and face. The brain is the most important and complex organ in the human body. Can it be used as a biometric trait? In this study, we analyze the uniqueness of the brain and try to use the brain for identity authentication. The proposed brain-based verification system operates in two stages: gray matter extraction and gray matter matching. A modified brain segmentation algorithm is implemented for extracting gray matter from an input brain image. Then, an alignment-based matching algorithm is developed for brain matching. Experimental results on two data sets show that the proposed brain recognition system meets the high accuracy requirement of identity authentication. Though currently the acquisition of the brain is still time consuming and expensive, brain images are highly unique and have the potential possibility for authentication in view of pattern recognition.

Conformational selection in a protein-protein interaction revealed by dynamic pathway analysis

DOE PAGES

Chakrabarti, Kalyan S.; Agafonov, Roman V.; Pontiggia, Francesco; ...

2015-12-24

Molecular recognition plays a central role in biology, and protein dynamics has been acknowledged to be important in this process. However, it is highly debated whether conformational changes happen before ligand binding to produce a binding-competent state (conformational selection) or are caused in response to ligand binding (induced fit). Proposals for both mechanisms in protein/protein recognition have been primarily based on structural arguments. However, the distinction between them is a question of the probabilities of going via these two opposing pathways. Here we present a direct demonstration of exclusive conformational selection in protein/protein recognition by measuring the flux for rhodopsinmore » kinase binding to its regulator recoverin, an important molecular recognition in the vision system. Using NMR spectroscopy, stopped-flow kinetics and isothermal titration calorimetry we show that recoverin populates a minor conformation in solution that exposes a hydrophobic binding pocket responsible for binding rhodopsin kinase. Lastly, protein dynamics in free recoverin limits the overall rate of binding.« less

Identifying and detecting facial expressions of emotion in peripheral vision

PubMed Central

Rossit, Stephanie

2018-01-01

Facial expressions of emotion are signals of high biological value. Whilst recognition of facial expressions has been much studied in central vision, the ability to perceive these signals in peripheral vision has only seen limited research to date, despite the potential adaptive advantages of such perception. In the present experiment, we investigate facial expression recognition and detection performance for each of the basic emotions (plus neutral) at up to 30 degrees of eccentricity. We demonstrate, as expected, a decrease in recognition and detection performance with increasing eccentricity, with happiness and surprised being the best recognized expressions in peripheral vision. In detection however, while happiness and surprised are still well detected, fear is also a well detected expression. We show that fear is a better detected than recognized expression. Our results demonstrate that task constraints shape the perception of expression in peripheral vision and provide novel evidence that detection and recognition rely on partially separate underlying mechanisms, with the latter more dependent on the higher spatial frequency content of the face stimulus. PMID:29847562

Conformational selection in a protein-protein interaction revealed by dynamic pathway analysis

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

Chakrabarti, Kalyan S.; Agafonov, Roman V.; Pontiggia, Francesco

Molecular recognition plays a central role in biology, and protein dynamics has been acknowledged to be important in this process. However, it is highly debated whether conformational changes happen before ligand binding to produce a binding-competent state (conformational selection) or are caused in response to ligand binding (induced fit). Proposals for both mechanisms in protein/protein recognition have been primarily based on structural arguments. However, the distinction between them is a question of the probabilities of going via these two opposing pathways. Here we present a direct demonstration of exclusive conformational selection in protein/protein recognition by measuring the flux for rhodopsinmore » kinase binding to its regulator recoverin, an important molecular recognition in the vision system. Using NMR spectroscopy, stopped-flow kinetics and isothermal titration calorimetry we show that recoverin populates a minor conformation in solution that exposes a hydrophobic binding pocket responsible for binding rhodopsin kinase. Lastly, protein dynamics in free recoverin limits the overall rate of binding.« less

Use of UV-vis-NIR spectroscopy to monitor label-free interaction between molecular recognition elements and erythropoietin on a gold-coated polycarbonate platform.

PubMed

Citartan, Marimuthu; Gopinath, Subash C B; Tominaga, Junji; Chen, Yeng; Tang, Thean-Hock

2014-08-01

Label-free-based detection is pivotal for real-time monitoring of biomolecular interactions and to eliminate the need for labeling with tags that can occupy important binding sites of biomolecules. One simplest form of label-free-based detection is ultraviolet-visible-near-infrared (UV-vis-NIR) spectroscopy, which measure changes in reflectivity as a means to monitor immobilization and interaction of biomolecules with their corresponding partners. In biosensor development, the platform used for the biomolecular interaction should be suitable for different molecular recognition elements. In this study, gold (Au)-coated polycarbonate was used as a platform and as a proof-of-concept, erythropoietin (EPO), a doping substance widely abused by the athletes was used as the target. The interaction of EPO with its corresponding molecular recognition elements (anti-EPO monoclonal antibody and anti-EPO DNA aptamer) is monitored by UV-vis-NIR spectroscopy. Prior to this, to show that UV-vis-NIR spectroscopy is a suitable method for measuring biomolecular interaction, the interaction between biotin and streptavidin was demonstrated via this strategy and reflectivity of this interaction decreased by 25%. Subsequent to this, interaction of the EPO with anti-EPO monoclonal antibody and anti-EPO DNA aptamer resulted in the decrease of reflectivity by 5% and 10%, respectively. The results indicated that Au-coated polycarbonate could be an ideal biosensor platform for monitoring biomolecular interactions using UV-vis-NIR spectroscopy. A smaller version of the Au-coated polycarbonate substrates can be derived from the recent set-up, to be applied towards detecting EPO abuse among atheletes. Copyright © 2014 Elsevier B.V. All rights reserved.

On the mechanics of growing thin biological membranes

NASA Astrophysics Data System (ADS)

Rausch, Manuel K.; Kuhl, Ellen

2014-02-01

Despite their seemingly delicate appearance, thin biological membranes fulfill various crucial roles in the human body and can sustain substantial mechanical loads. Unlike engineering structures, biological membranes are able to grow and adapt to changes in their mechanical environment. Finite element modeling of biological growth holds the potential to better understand the interplay of membrane form and function and to reliably predict the effects of disease or medical intervention. However, standard continuum elements typically fail to represent thin biological membranes efficiently, accurately, and robustly. Moreover, continuum models are typically cumbersome to generate from surface-based medical imaging data. Here we propose a computational model for finite membrane growth using a classical midsurface representation compatible with standard shell elements. By assuming elastic incompressibility and membrane-only growth, the model a priori satisfies the zero-normal stress condition. To demonstrate its modular nature, we implement the membrane growth model into the general-purpose non-linear finite element package Abaqus/Standard using the concept of user subroutines. To probe efficiently and robustness, we simulate selected benchmark examples of growing biological membranes under different loading conditions. To demonstrate the clinical potential, we simulate the functional adaptation of a heart valve leaflet in ischemic cardiomyopathy. We believe that our novel approach will be widely applicable to simulate the adaptive chronic growth of thin biological structures including skin membranes, mucous membranes, fetal membranes, tympanic membranes, corneoscleral membranes, and heart valve membranes. Ultimately, our model can be used to identify diseased states, predict disease evolution, and guide the design of interventional or pharmaceutic therapies to arrest or revert disease progression.

On the mechanics of growing thin biological membranes

PubMed Central

Rausch, Manuel K.; Kuhl, Ellen

2013-01-01

Despite their seemingly delicate appearance, thin biological membranes fulfill various crucial roles in the human body and can sustain substantial mechanical loads. Unlike engineering structures, biological membranes are able to grow and adapt to changes in their mechanical environment. Finite element modeling of biological growth holds the potential to better understand the interplay of membrane form and function and to reliably predict the effects of disease or medical intervention. However, standard continuum elements typically fail to represent thin biological membranes efficiently, accurately, and robustly. Moreover, continuum models are typically cumbersome to generate from surface-based medical imaging data. Here we propose a computational model for finite membrane growth using a classical midsurface representation compatible with standard shell elements. By assuming elastic incompressibility and membrane-only growth, the model a priori satisfies the zero-normal stress condition. To demonstrate its modular nature, we implement the membrane growth model into the general-purpose non-linear finite element package Abaqus/Standard using the concept of user subroutines. To probe efficiently and robustness, we simulate selected benchmark examples of growing biological membranes under different loading conditions. To demonstrate the clinical potential, we simulate the functional adaptation of a heart valve leaflet in ischemic cardiomyopathy. We believe that our novel approach will be widely applicable to simulate the adaptive chronic growth of thin biological structures including skin membranes, mucous membranes, fetal membranes, tympanic membranes, corneoscleral membranes, and heart valve membranes. Ultimately, our model can be used to identify diseased states, predict disease evolution, and guide the design of interventional or pharmaceutic therapies to arrest or revert disease progression. PMID:24563551

Recognition and defect detection of dot-matrix text via variation-model based learning

NASA Astrophysics Data System (ADS)

Ohyama, Wataru; Suzuki, Koushi; Wakabayashi, Tetsushi

2017-03-01

An algorithm for recognition and defect detection of dot-matrix text printed on products is proposed. Extraction and recognition of dot-matrix text contains several difficulties, which are not involved in standard camera-based OCR, that the appearance of dot-matrix characters is corrupted and broken by illumination, complex texture in the background and other standard characters printed on product packages. We propose a dot-matrix text extraction and recognition method which does not require any user interaction. The method employs detected location of corner points and classification score. The result of evaluation experiment using 250 images shows that recall and precision of extraction are 78.60% and 76.03%, respectively. Recognition accuracy of correctly extracted characters is 94.43%. Detecting printing defect of dot-matrix text is also important in the production scene to avoid illegal productions. We also propose a detection method for printing defect of dot-matrix characters. The method constructs a feature vector of which elements are classification scores of each character class and employs support vector machine to classify four types of printing defect. The detection accuracy of the proposed method is 96.68 %.

Self-assembled lipid bilayer materials

DOEpatents

Sasaki, Darryl Y.; Waggoner, Tina A.; Last, Julie A.

2005-11-08

The present invention is a self-assembling material comprised of stacks of lipid bilayers formed in a columnar structure, where the assembly process is mediated and regulated by chemical recognition events. The material, through the chemical recognition interactions, has a self-regulating system that corrects the radial size of the assembly creating a uniform diameter throughout most of the structure. The materials form and are stable in aqueous solution. These materials are useful as structural elements for the architecture of materials and components in nanotechnology, efficient light harvesting systems for optical sensing, chemical processing centers, and drug delivery vehicles.

Parametric Representation of the Speaker's Lips for Multimodal Sign Language and Speech Recognition

NASA Astrophysics Data System (ADS)

Ryumin, D.; Karpov, A. A.

2017-05-01

In this article, we propose a new method for parametric representation of human's lips region. The functional diagram of the method is described and implementation details with the explanation of its key stages and features are given. The results of automatic detection of the regions of interest are illustrated. A speed of the method work using several computers with different performances is reported. This universal method allows applying parametrical representation of the speaker's lipsfor the tasks of biometrics, computer vision, machine learning, and automatic recognition of face, elements of sign languages, and audio-visual speech, including lip-reading.

Is it worth changing pattern recognition methods for structural health monitoring?

NASA Astrophysics Data System (ADS)

Bull, L. A.; Worden, K.; Cross, E. J.; Dervilis, N.

2017-05-01

The key element of this work is to demonstrate alternative strategies for using pattern recognition algorithms whilst investigating structural health monitoring. This paper looks to determine if it makes any difference in choosing from a range of established classification techniques: from decision trees and support vector machines, to Gaussian processes. Classification algorithms are tested on adjustable synthetic data to establish performance metrics, then all techniques are applied to real SHM data. To aid the selection of training data, an informative chain of artificial intelligence tools is used to explore an active learning interaction between meaningful clusters of data.

ICP-MS: Analytical Method for Identification and Detection of Elemental Impurities.

PubMed

Mittal, Mohini; Kumar, Kapil; Anghore, Durgadas; Rawal, Ravindra K

2017-01-01

Aim of this article is to review and discuss the currently used quantitative analytical method ICP-MS, which is used for quality control of pharmaceutical products. ICP-MS technique has several applications such as determination of single elements, multi element analysis in synthetic drugs, heavy metals in environmental water, trace element content of selected fertilizers and dairy manures. ICP-MS is also used for determination of toxic and essential elements in different varieties of food samples and metal pollutant present in the environment. The pharmaceuticals may generate impurities at various stages of development, transportation and storage which make them risky to be administered. Thus, it is essential that these impurities must be detected and quantified. ICP-MS plays an important function in the recognition and revealing of elemental impurities. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Multifunctional receptor model for dioxin and related compound toxic action: possible thyroid hormone-responsive effector-linked site.

PubMed Central

McKinney, J D

1989-01-01

Molecular/theoretical modeling studies have revealed that thyroid hormones and toxic chlorinated aromatic hydrocarbons of environmental significance (for which dioxin or TCDD is the prototype) have similar structural properties that could be important in molecular recognition in biochemical systems. These molecular properties include a somewhat rigid, sterically accessible and polarizable aromatic ring and size-limited, hydrophobic lateral substituents, usually contained in opposite adjoining rings of a diphenyl compound. These molecular properties define the primary binding groups thought to be important in molecular recognition of both types of structures in biochemical systems. Similar molecular reactivities are supported by the demonstration of effective specific binding of thyroid hormones and chlorinated aromatic hydrocarbons with four different proteins, enzymes, or receptor preparations that are known or suspected to be involved in the expression of thyroid hormone activity. These binding interactions represent both aromatic-aromatic (stacking) and molecular cleft-type recognition processes. A multiple protein or multifunctional receptor-ligand binding mechanism model is proposed as a way of visualizing the details and possible role of both the stacking and cleft type molecular recognition factors in the expression of biological activity. The model suggests a means by which hormone-responsive effector-linked sites (possible protein-protein-DNA complexes) can maintain highly structurally specific control of hormone action. Finally, the model also provides a theoretical basis for the design and conduct of further biological experimentation on the molecular mechanism(s) of action of toxic chlorinated aromatic hydrocarbons and thyroid hormones. Images FIGURE 3. A FIGURE 3. B FIGURE 3. C FIGURE 3. D PMID:2551666

Rigorous Science: a How-To Guide

PubMed Central

Fang, Ferric C.

2016-01-01

ABSTRACT Proposals to improve the reproducibility of biomedical research have emphasized scientific rigor. Although the word “rigor” is widely used, there has been little specific discussion as to what it means and how it can be achieved. We suggest that scientific rigor combines elements of mathematics, logic, philosophy, and ethics. We propose a framework for rigor that includes redundant experimental design, sound statistical analysis, recognition of error, avoidance of logical fallacies, and intellectual honesty. These elements lead to five actionable recommendations for research education. PMID:27834205

Rigorous Science: a How-To Guide.

PubMed

Casadevall, Arturo; Fang, Ferric C

2016-11-08

Proposals to improve the reproducibility of biomedical research have emphasized scientific rigor. Although the word "rigor" is widely used, there has been little specific discussion as to what it means and how it can be achieved. We suggest that scientific rigor combines elements of mathematics, logic, philosophy, and ethics. We propose a framework for rigor that includes redundant experimental design, sound statistical analysis, recognition of error, avoidance of logical fallacies, and intellectual honesty. These elements lead to five actionable recommendations for research education. Copyright © 2016 Casadevall and Fang.

Pattern recognition methods and air pollution source identification. [based on wind direction

NASA Technical Reports Server (NTRS)

Leibecki, H. F.; King, R. B.

1978-01-01

Directional air samplers, used for resolving suspended particulate matter on the basis of time and wind direction were used to assess the feasibility of characterizing and identifying emission source types in urban multisource environments. Filters were evaluated for 16 elements and X-ray fluorescence methods yielded elemental concentrations for direction, day, and the interaction of direction and day. Large numbers of samples are necessary to compensate for large day-to-day variations caused by wind perturbations and/or source changes.

A stable biologically motivated learning mechanism for visual feature extraction to handle facial categorization.

PubMed

Rajaei, Karim; Khaligh-Razavi, Seyed-Mahdi; Ghodrati, Masoud; Ebrahimpour, Reza; Shiri Ahmad Abadi, Mohammad Ebrahim

2012-01-01

The brain mechanism of extracting visual features for recognizing various objects has consistently been a controversial issue in computational models of object recognition. To extract visual features, we introduce a new, biologically motivated model for facial categorization, which is an extension of the Hubel and Wiesel simple-to-complex cell hierarchy. To address the synaptic stability versus plasticity dilemma, we apply the Adaptive Resonance Theory (ART) for extracting informative intermediate level visual features during the learning process, which also makes this model stable against the destruction of previously learned information while learning new information. Such a mechanism has been suggested to be embedded within known laminar microcircuits of the cerebral cortex. To reveal the strength of the proposed visual feature learning mechanism, we show that when we use this mechanism in the training process of a well-known biologically motivated object recognition model (the HMAX model), it performs better than the HMAX model in face/non-face classification tasks. Furthermore, we demonstrate that our proposed mechanism is capable of following similar trends in performance as humans in a psychophysical experiment using a face versus non-face rapid categorization task.

Platelets and cancer: a casual or causal relationship: revisited

PubMed Central

Menter, David G.; Tucker, Stephanie C.; Kopetz, Scott; Sood, Anil K.; Crissman, John D.; Honn, Kenneth V.

2014-01-01

Human platelets arise as subcellular fragments of megakaryocytes in bone marrow. The physiologic demand, presence of disease such as cancer, or drug effects can regulate the production circulating platelets. Platelet biology is essential to hemostasis, vascular integrity, angiogenesis, inflammation, innate immunity, wound healing, and cancer biology. The most critical biological platelet response is serving as “First Responders” during the wounding process. The exposure of extracellular matrix proteins and intracellular components occurs after wounding. Numerous platelet receptors recognize matrix proteins that trigger platelet activation, adhesion, aggregation, and stabilization. Once activated, platelets change shape and degranulate to release growth factors and bioactive lipids into the blood stream. This cyclic process recruits and aggregates platelets along with thrombogenesis. This process facilitates wound closure or can recognize circulating pathologic bodies. Cancer cell entry into the blood stream triggers platelet-mediated recognition and is amplified by cell surface receptors, cellular products, extracellular factors, and immune cells. In some cases, these interactions suppress immune recognition and elimination of cancer cells or promote arrest at the endothelium, or entrapment in the microvasculature, and survival. This supports survival and spread of cancer cells and the establishment of secondary lesions to serve as important targets for prevention and therapy. PMID:24696047

Self-organization versus Watchmaker: ambiguity of molecular recognition and design charts of cellular circuitry.

PubMed

Kurakin, Alexei

2007-01-01

A large body of experimental evidence indicates that the specific molecular interactions and/or chemical conversions depicted as links in the conventional diagrams of cellular signal transduction and metabolic pathways are inherently probabilistic, ambiguous and context-dependent. Being the inevitable consequence of the dynamic nature of protein structure in solution, the ambiguity of protein-mediated interactions and conversions challenges the conceptual adequacy and practical usefulness of the mechanistic assumptions and inferences embodied in the design charts of cellular circuitry. It is argued that the reconceptualization of molecular recognition and cellular organization within the emerging interpretational framework of self-organization, which is expanded here to include such concepts as bounded stochasticity, evolutionary memory, and adaptive plasticity offers a significantly more adequate representation of experimental reality than conventional mechanistic conceptions do. Importantly, the expanded framework of self-organization appears to be universal and scale-invariant, providing conceptual continuity across multiple scales of biological organization, from molecules to societies. This new conceptualization of biological phenomena suggests that such attributes of intelligence as adaptive plasticity, decision-making, and memory are enforced by evolution at different scales of biological organization and may represent inherent properties of living matter. (c) 2007 John Wiley & Sons, Ltd.

Silvics of North America: 1. Conifers; 2. Hardwoods

Treesearch

Russell M. Burns; Barbara H. (tech. Coords.) Honkala

1990-01-01

The total environment of a tree is a complex integration of physical and biological elements. The physical elements are related to climate and soil and include radiation, precipitation, and the movement and composition of air; as well as the texture of the soil and its structure, depth, moisture capacity, drainage, nutrient content, and topographic position. Biological...

Biological X-ray absorption spectroscopy (BioXAS): a valuable tool for the study of trace elements in the life sciences.

PubMed

Strange, Richard W; Feiters, Martin C

2008-10-01

Using X-ray absorption spectroscopy (XAS) the binding modes (type and number of ligands, distances and geometry) and oxidation states of metals and other trace elements in crystalline as well as non-crystalline samples can be revealed. The method may be applied to biological systems as a 'stand-alone' technique, but it is particularly powerful when used alongside other X-ray and spectroscopic techniques and computational approaches. In this review, we highlight how biological XAS is being used in concert with crystallography, spectroscopy and computational chemistry to study metalloproteins in crystals, and report recent applications on relatively rare trace elements utilised by living organisms and metals involved in neurodegenerative diseases.

Using GOMS and Bayesian plan recognition to develop recognition models of operator behavior

NASA Astrophysics Data System (ADS)

Zaientz, Jack D.; DeKoven, Elyon; Piegdon, Nicholas; Wood, Scott D.; Huber, Marcus J.

2006-05-01

Trends in combat technology research point to an increasing role for uninhabited vehicles in modern warfare tactics. To support increased span of control over these vehicles human responsibilities need to be transformed from tedious, error-prone and cognition intensive operations into tasks that are more supervisory and manageable, even under intensely stressful conditions. The goal is to move away from only supporting human command of low-level system functions to intention-level human-system dialogue about the operator's tasks and situation. A critical element of this process is developing the means to identify when human operators need automated assistance and to identify what assistance they need. Toward this goal, we are developing an unmanned vehicle operator task recognition system that combines work in human behavior modeling and Bayesian plan recognition. Traditionally, human behavior models have been considered generative, meaning they describe all possible valid behaviors. Basing behavior recognition on models designed for behavior generation can offers advantages in improved model fidelity and reuse. It is not clear, however, how to reconcile the structural differences between behavior recognition and behavior modeling approaches. Our current work demonstrates that by pairing a cognitive psychology derived human behavior modeling approach, GOMS, with a Bayesian plan recognition engine, ASPRN, we can translate a behavior generation model into a recognition model. We will discuss the implications for using human performance models in this manner as well as suggest how this kind of modeling may be used to support the real-time control of multiple, uninhabited battlefield vehicles and other semi-autonomous systems.

Perception and motivation in face recognition: a critical review of theories of the Cross-Race Effect.

PubMed

Young, Steven G; Hugenberg, Kurt; Bernstein, Michael J; Sacco, Donald F

2012-05-01

Although humans possess well-developed face processing expertise, face processing is nevertheless subject to a variety of biases. Perhaps the best known of these biases is the Cross-Race Effect--the tendency to have more accurate recognition for same-race than cross-race faces. The current work reviews the evidence for and provides a critical review of theories of the Cross-Race Effect, including perceptual expertise and social cognitive accounts of the bias. The authors conclude that recent hybrid models of the Cross-Race Effect, which combine elements of both perceptual expertise and social cognitive frameworks, provide an opportunity for theoretical synthesis and advancement not afforded by independent expertise or social cognitive models. Finally, the authors suggest future research directions intended to further develop a comprehensive and integrative understanding of biases in face recognition.

Elements in human serum—CCQM-K139

NASA Astrophysics Data System (ADS)

Shin, Richard; Dewi, Fransiska; Tong, Benny; Wah, Leung Ho; Saxby, David; Armishaw, Paul; Ivanova, Veronika; Feng, Liuxing; Wang, Jun; Estela del Castillo Busto, M.; Fisicaro, Paola; Rienitz, Olaf; Fung, Wai-Hong; Ho-pan Yau, Michael; Yim, Yong-Hyeon; Buzoianu, Mirella; Can, Suleyman Z.; Ari, Betul; Cankur, Oktay; Goenaga Infante, Heidi; Pérez-Zambra, Ramiro; Ferreira, Elizabeth; Long, Stephen

2018-01-01

Elements in human serum serve as important biomarkers and their levels reflect the well-being of an individual. Electrolytes such as sodium (Na) and chloride (Cl) are crucial in maintaining the normal distribution of water, osmotic pressure and electrical neutrality in the body. Trace element such as copper (Cu) plays a part in many oxidation-reduction reactions and metalloenzymes. The majority of selenium (Se) exists as selenoproteins which are cofactors in the glutathione peroxidase activity that protects the body against free radicals. Phosphorus (P) is required for strong bones and teeth. It is also indispensable for growth, maintenance and repair of tissues and cells. The key comparison CCQM-K139: elements in human serum was coordinated by the Health Sciences Authority, Singapore. This comparison aimed to enable participating National Metrology Institutes (NMIs) and Designated Institutes (DIs) to demonstrate their competence in the determination of elements (electrolytes and essential elements) in human serum. The five measurands (Na, Cl, Cu, Se and P) selected for this comparison were not covered in the last two comparisons in the clinical area (CCQM-K14 and CCQM-K107) and offered different analytical challenges. Their concentration levels were within the normal biological range. They were also within the range of existing calibration and measurement capability (CMC) claims in the International Bureau of Weights and Measures' Key Comparison Database (BIPM KCDB). Ten institutes participated in the comparison for Na, eight for Cl, eleven for Cu, six for Se and eight for P. For the analysis of Na, Cu, Se and P, most of the participating institutes employed microwave-assisted digestion and acid digestion (with or without heating) sample dissolution. For the analysis of Cl, in addition to the microwave-assisted digestion and acid digestion, a wider variety of techniques were employed. These included matrix separation, alkaline extraction and coulometric titration. Inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma optical emission spectrometry (ICP-OES) were the two most commonly used instrumental techniques. Other techniques used included ion chromatography (IC), flame atomic absorption spectrometry (FAAS), titration and micro-coulometry. The medians were used as the estimators of Key Comparison Reference Values (KCRVs) for all measurands. The KCRVs (+/- standard uncertainty) for Na, Cl, Cu, Se and P (in mg/kg) were 3346 (+/- 14), 3871 (+/- 22), 1.151 (+/- 0.007), 0.1292 (+/- 0.0007) and 125.70 (+/- 0.35), respectively. The k-factor of 2 was used for the estimation of the expanded uncertainties of the KCRVs. The degree of equivalence and its associated uncertainty were calculated for each submitted result. For the five measurands, most participating institutes were able to demonstrate their capabilities in the determination of elements in human serum. CMC claims based on elements covered in this study may include other elements with similar core competencies, such as zinc (Zn), potassium (K), magnesium (Mg), calcium (Ca) and iron (Fe), in a wide range of biological materials. The measurands should be at similar concentration range and analysed using the same measurement technique(s) applied in this key comparison. Main text To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/. The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Structural basis for substrate recognition by the human N-terminal methyltransferase 1

DOE PAGES

Dong, Cheng; Mao, Yunfei; Tempel, Wolfram; ...

2015-11-05

α-N-terminal methylation represents a highly conserved and prevalent post-translational modification, yet its biological function has remained largely speculative. The recent discovery of α-N-terminal methyltransferase 1 (NTMT1) and its physiological substrates propels the elucidation of a general role of α-N-terminal methylation in mediating DNA-binding ability of the modified proteins. The phenotypes, observed from both NTMT1 knockdown in breast cancer cell lines and knockout mouse models, suggest the potential involvement of α-N-terminal methylation in DNA damage response and cancer development. In this study, we report the first crystal structures of human NTMT1 in complex with cofactor S-adenosyl-L-homocysteine (SAH) and six substrate peptides,more » respectively, and reveal that NTMT1 contains two characteristic structural elements (a β hairpin and an N-terminal extension) that contribute to its substrate specificity. Our complex structures, coupled with mutagenesis, binding, and enzymatic studies, also present the key elements involved in locking the consensus substrate motif XPK (X indicates any residue type other than D/E) into the catalytic pocket for α-N-terminal methylation and explain why NTMT1 prefers an XPK sequence motif. We propose a catalytic mechanism for α-N-terminal methylation. Overall, this study gives us the first glimpse of the molecular mechanism of α-N-terminal methylation and potentially contributes to the advent of therapeutic agents for human diseases associated with deregulated α-N-terminal methylation.« less

Physical, chemical, and biological data for detailed study of the Sun River Irrigation Project, Freezout Lake Wildlife Management Area, and Benton Lake National Wildlife Refuge, west-central Montana, 1990-92, with selected data for 1987-89

USGS Publications Warehouse

Lambing, J.H.; Nimick, D.A.; Knapton, J.R.; Palawski, D.U.

1994-01-01

Physical chemical, and biological data were collected in the lower Sun River area of west-central Montana during 1990-92 as part of a U.S. Department of the Interior detailed study of the extent, magnitude, sources, and potential biological impacts of contaminants associated with irrigation drainage. Physical and chemical data were collected from areas within and near the Sun River Irrigation Project and from wetland areas receiving irrigation drainage. Biological data were collected from areas in and near Freezout Lake Wildlife Management Area and Benton Lake National Wildlife Refuge. Additional biological data were collected previously during 1987-89 as part of a U.S. Fish and Wildlife Service program. This report presents data for selenium and other potentially toxic constituents in solid-phase, water, and biological media. Data consist of concentrations of major and trace elements in soil and drill cores; concen- trations of major ions, nutrients, and trace elements in ground water and surface water; and trace-element concentrations in bottom sediment and biological tissue. Hydrogeologic data for domestic and test wells and daily streamflow data for selected sites also are included.

Road sign recognition during computer testing versus driving simulator performance for stroke and stroke+aphasia groups.

DOT National Transportation Integrated Search

2015-07-01

Driving is essential to maintaining independence. For most Americans preserving personal mobility is a : key element to retaining jobs, friends, activities and the basic necessities to maintain a household. This : is particularly true for older peopl...

A modular framework for biomedical concept recognition

PubMed Central

2013-01-01

Background Concept recognition is an essential task in biomedical information extraction, presenting several complex and unsolved challenges. The development of such solutions is typically performed in an ad-hoc manner or using general information extraction frameworks, which are not optimized for the biomedical domain and normally require the integration of complex external libraries and/or the development of custom tools. Results This article presents Neji, an open source framework optimized for biomedical concept recognition built around four key characteristics: modularity, scalability, speed, and usability. It integrates modules for biomedical natural language processing, such as sentence splitting, tokenization, lemmatization, part-of-speech tagging, chunking and dependency parsing. Concept recognition is provided through dictionary matching and machine learning with normalization methods. Neji also integrates an innovative concept tree implementation, supporting overlapped concept names and respective disambiguation techniques. The most popular input and output formats, namely Pubmed XML, IeXML, CoNLL and A1, are also supported. On top of the built-in functionalities, developers and researchers can implement new processing modules or pipelines, or use the provided command-line interface tool to build their own solutions, applying the most appropriate techniques to identify heterogeneous biomedical concepts. Neji was evaluated against three gold standard corpora with heterogeneous biomedical concepts (CRAFT, AnEM and NCBI disease corpus), achieving high performance results on named entity recognition (F1-measure for overlap matching: species 95%, cell 92%, cellular components 83%, gene and proteins 76%, chemicals 65%, biological processes and molecular functions 63%, disorders 85%, and anatomical entities 82%) and on entity normalization (F1-measure for overlap name matching and correct identifier included in the returned list of identifiers: species 88%, cell 71%, cellular components 72%, gene and proteins 64%, chemicals 53%, and biological processes and molecular functions 40%). Neji provides fast and multi-threaded data processing, annotating up to 1200 sentences/second when using dictionary-based concept identification. Conclusions Considering the provided features and underlying characteristics, we believe that Neji is an important contribution to the biomedical community, streamlining the development of complex concept recognition solutions. Neji is freely available at http://bioinformatics.ua.pt/neji. PMID:24063607

AzaHx, a novel fluorescent, DNA minor groove and G·C recognition element: Synthesis and DNA binding properties of a p-anisyl-4-aza-benzimidazole-pyrrole-imidazole (azaHx-PI) polyamide.

PubMed

Satam, Vijay; Babu, Balaji; Patil, Pravin; Brien, Kimberly A; Olson, Kevin; Savagian, Mia; Lee, Megan; Mepham, Andrew; Jobe, Laura Beth; Bingham, John P; Pett, Luke; Wang, Shuo; Ferrara, Maddi; Bruce, Chrystal D; Wilson, W David; Lee, Moses; Hartley, John A; Kiakos, Konstantinos

2015-09-01

The design, synthesis, and DNA binding properties of azaHx-PI or p-anisyl-4-aza-benzimidazole-pyrrole-imidazole (5) are described. AzaHx, 2-(p-anisyl)-4-aza-benzimidazole-5-carboxamide, is a novel, fluorescent DNA recognition element, derived from Hoechst 33258 to recognize G·C base pairs. Supported by theoretical data, the results from DNase I footprinting, CD, ΔT(M), and SPR studies provided evidence that an azaHx/IP pairing, formed from antiparallel stacking of two azaHx-PI molecules in a side-by-side manner in the minor groove, selectively recognized a C-G doublet. AzaHx-PI was found to target 5'-ACGCGT-3', the Mlu1 Cell Cycle Box (MCB) promoter sequence with specificity and significant affinity (K(eq) 4.0±0.2×10(7) M(-1)). Copyright © 2015 Elsevier Ltd. All rights reserved.

Turning tryptophanase into odor-generating biosensors.

PubMed

Xu, Yaqin; Zhang, Zhuyuan; Ali, M Monsur; Sauder, Joanna; Deng, Xudong; Giang, Karen; Aguirre, Sergio D; Pelton, Robert; Li, Yingfu; Filipe, Carlos D M

2014-03-03

An odor-based sensor system that exploits the metabolic enzyme tryptophanase (TPase) as the key component is reported. This enzyme is able to convert an odorless substrate like S-methyl-L-cysteine or L-tryptophan into the odorous products methyl mercaptan or indole. To make a biosensor, TPase was biotinylated so that it could be coupled with a molecular recognition element, such as an antibody, to develop an ELISA-like assay. This method was used for the detection of an antibody present in nM concentrations by the human nose. TPase can also be combined with the enzyme pyridoxal kinase (PKase) for use in a coupled assay to detect adenosine 5'-triphosphate (ATP). When ATP is present in the low μM concentration range, the coupled enzymatic system generates an odor that is easily detectable by the human nose. Biotinylated TPase can be combined with various biotin-labeled molecular recognition elements, thereby enabling a broad range of applications for this odor-based reporting system. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Determination of L-phenylalanine on-line based on molecularly imprinted polymeric microspheres and flow injection chemiluminescence

NASA Astrophysics Data System (ADS)

Qiu, Huamin; Xi, Yulei; Lu, Fuguang; Fan, Lulu; Luo, Chuannan

2012-02-01

A novel molecular imprinting-chemiluminescence (MIP-CL) sensor for the determination of L-phenylalanine (Phe) using molecularly imprinted polymer (MIP) as recognition element is reported. The Phe-MIP was synthesized using acrylamide (AM) as functional monomer and ethylene glycol dimethacrylate (EGDMA) as cross-linker, 2,2-azobisisobutyronitrile (AIBN) as initiator and the polymers' properties were characterized. Then the synthesized MIP was employed as recognition element by packing into flow cell to establish a novel flow injection CL sensor. The CL intensity responded linearly to the concentration of Phe in the range 1.3 × 10 -6 to 5.44 × 10 -4 mol/L with a detection limit of 6.23 × 10 -7 mol/L (3 σ), which is lower than that of conventional methods. The sensor is reusable and has a great improvement in sensitivity and selectivity for CL analysis. As a result, the new MIP-CL sensor had been successfully applied to the determination of Phe in samples.

Artificial Neural Networks for Processing Graphs with Application to Image Understanding: A Survey

NASA Astrophysics Data System (ADS)

Bianchini, Monica; Scarselli, Franco

In graphical pattern recognition, each data is represented as an arrangement of elements, that encodes both the properties of each element and the relations among them. Hence, patterns are modelled as labelled graphs where, in general, labels can be attached to both nodes and edges. Artificial neural networks able to process graphs are a powerful tool for addressing a great variety of real-world problems, where the information is naturally organized in entities and relationships among entities and, in fact, they have been widely used in computer vision, f.i. in logo recognition, in similarity retrieval, and for object detection. In this chapter, we propose a survey of neural network models able to process structured information, with a particular focus on those architectures tailored to address image understanding applications. Starting from the original recursive model (RNNs), we subsequently present different ways to represent images - by trees, forests of trees, multiresolution trees, directed acyclic graphs with labelled edges, general graphs - and, correspondingly, neural network architectures appropriate to process such structures.

Event Recognition Based on Deep Learning in Chinese Texts

PubMed Central

Zhang, Yajun; Liu, Zongtian; Zhou, Wen

2016-01-01

Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features using methods based on rules is difficult; methods based on shallow neural networks converge too quickly to a local minimum, resulting in low recognition precision. To address these problems, we propose the Chinese emergency event recognition model based on deep learning (CEERM). Firstly, we use a word segmentation system to segment sentences. According to event elements labeled in the CEC 2.0 corpus, we classify words into five categories: trigger words, participants, objects, time and location. Each word is vectorized according to the following six feature layers: part of speech, dependency grammar, length, location, distance between trigger word and core word and trigger word frequency. We obtain deep semantic features of words by training a feature vector set using a deep belief network (DBN), then analyze those features in order to identify trigger words by means of a back propagation neural network. Extensive testing shows that the CEERM achieves excellent recognition performance, with a maximum F-measure value of 85.17%. Moreover, we propose the dynamic-supervised DBN, which adds supervised fine-tuning to a restricted Boltzmann machine layer by monitoring its training performance. Test analysis reveals that the new DBN improves recognition performance and effectively controls the training time. Although the F-measure increases to 88.11%, the training time increases by only 25.35%. PMID:27501231

Event Recognition Based on Deep Learning in Chinese Texts.

PubMed

Zhang, Yajun; Liu, Zongtian; Zhou, Wen

2016-01-01

Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features using methods based on rules is difficult; methods based on shallow neural networks converge too quickly to a local minimum, resulting in low recognition precision. To address these problems, we propose the Chinese emergency event recognition model based on deep learning (CEERM). Firstly, we use a word segmentation system to segment sentences. According to event elements labeled in the CEC 2.0 corpus, we classify words into five categories: trigger words, participants, objects, time and location. Each word is vectorized according to the following six feature layers: part of speech, dependency grammar, length, location, distance between trigger word and core word and trigger word frequency. We obtain deep semantic features of words by training a feature vector set using a deep belief network (DBN), then analyze those features in order to identify trigger words by means of a back propagation neural network. Extensive testing shows that the CEERM achieves excellent recognition performance, with a maximum F-measure value of 85.17%. Moreover, we propose the dynamic-supervised DBN, which adds supervised fine-tuning to a restricted Boltzmann machine layer by monitoring its training performance. Test analysis reveals that the new DBN improves recognition performance and effectively controls the training time. Although the F-measure increases to 88.11%, the training time increases by only 25.35%.

Natural production of biological optical systems

NASA Astrophysics Data System (ADS)

Choi, Seung Ho; Kim, Young L.

2015-03-01

Synthesis and production in nature often provide ideas to design and fabricate advanced biomimetic photonic materials and structures, leading to excellent physical properties and enhanced performance. In addition, the recognition and utilization of natural or biological substances have been typical routes to develop biocompatible and biodegradable materials for medical applications. In this respect, biological lasers utilizing such biomaterials and biostructures have been received considerable attention, given a variety of implications and potentials for bioimaging, biosensing, implantation, and therapy. However, without relying on industrial facilities, eco-friendly massive production of such optical components or systems has not yet been investigated. We show examples of bioproduction of biological lasers using agriculture and fisheries. We anticipate that such approaches will open new possibilities for scalable eco-friendly `green' production of biological photonics components and systems.

Ultra-deep sequencing of ribosome-associated poly-adenylated RNA in early Drosophila embryos reveals hundreds of conserved translated sORFs.

PubMed

Li, Hongmei; Hu, Chuansheng; Bai, Ling; Li, Hua; Li, Mingfa; Zhao, Xiaodong; Czajkowsky, Daniel M; Shao, Zhifeng

2016-12-01

There is growing recognition that small open reading frames (sORFs) encoding peptides shorter than 100 amino acids are an important class of functional elements in the eukaryotic genome, with several already identified to play critical roles in growth, development, and disease. However, our understanding of their biological importance has been hindered owing to the significant technical challenges limiting their annotation. Here we combined ultra-deep sequencing of ribosome-associated poly-adenylated RNAs with rigorous conservation analysis to identify a comprehensive population of translated sORFs during early Drosophila embryogenesis. In total, we identify 399 sORFs, including those previously annotated but without evidence of translational capacity, those found within transcripts previously classified as non-coding, and those not previously known to be transcribed. Further, we find, for the first time, evidence for translation of many sORFs with different isoforms, suggesting their regulation is as complex as longer ORFs. Furthermore, many sORFs are found not associated with ribosomes in late-stage Drosophila S2 cells, suggesting that many of the translated sORFs may have stage-specific functions during embryogenesis. These results thus provide the first comprehensive annotation of the sORFs present during early Drosophila embryogenesis, a necessary basis for a detailed delineation of their function in embryogenesis and other biological processes. © The Author 2016. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Deep sequencing of cardiac microRNA-mRNA interactomes in clinical and experimental cardiomyopathy

PubMed Central

Matkovich, Scot J.; Dorn, Gerald W.

2018-01-01

Summary MicroRNAs are a family of short (~21 nucleotide) noncoding RNAs that serve key roles in cellular growth and differentiation and the response of the heart to stress stimuli. As the sequence-specific recognition element of RNA-induced silencing complexes (RISCs), microRNAs bind mRNAs and prevent their translation via mechanisms that may include transcript degradation and/or prevention of ribosome binding. Short microRNA sequences and the ability of microRNAs to bind to mRNA sites having only partial/imperfect sequence complementarity complicates purely computational analyses of microRNA-mRNA interactomes. Furthermore, computational microRNA target prediction programs typically ignore biological context, and therefore the principal determinants of microRNA-mRNA binding: the presence and quantity of each. To address these deficiencies we describe an empirical method, developed via studies of stressed and failing hearts, to determine disease-induced changes in microRNAs, mRNAs, and the mRNAs targeted to the RISC, without cross-linking mRNAs to RISC proteins. Deep sequencing methods are used to determine RNA abundances, delivering unbiased, quantitative RNA data limited only by their annotation in the genome of interest. We describe the laboratory bench steps required to perform these experiments, experimental design strategies to achieve an appropriate number of sequencing reads per biological replicate, and computer-based processing tools and procedures to convert large raw sequencing data files into gene expression measures useful for differential expression analyses. PMID:25836573

Deep sequencing of cardiac microRNA-mRNA interactomes in clinical and experimental cardiomyopathy.

PubMed

Matkovich, Scot J; Dorn, Gerald W

2015-01-01

MicroRNAs are a family of short (~21 nucleotide) noncoding RNAs that serve key roles in cellular growth and differentiation and the response of the heart to stress stimuli. As the sequence-specific recognition element of RNA-induced silencing complexes (RISCs), microRNAs bind mRNAs and prevent their translation via mechanisms that may include transcript degradation and/or prevention of ribosome binding. Short microRNA sequences and the ability of microRNAs to bind to mRNA sites having only partial/imperfect sequence complementarity complicate purely computational analyses of microRNA-mRNA interactomes. Furthermore, computational microRNA target prediction programs typically ignore biological context, and therefore the principal determinants of microRNA-mRNA binding: the presence and quantity of each. To address these deficiencies we describe an empirical method, developed via studies of stressed and failing hearts, to determine disease-induced changes in microRNAs, mRNAs, and the mRNAs targeted to the RISC, without cross-linking mRNAs to RISC proteins. Deep sequencing methods are used to determine RNA abundances, delivering unbiased, quantitative RNA data limited only by their annotation in the genome of interest. We describe the laboratory bench steps required to perform these experiments, experimental design strategies to achieve an appropriate number of sequencing reads per biological replicate, and computer-based processing tools and procedures to convert large raw sequencing data files into gene expression measures useful for differential expression analyses.

Towards molecular medicine: a case for a biological periodic table.

PubMed

Gawad, Charles

2005-01-01

The recently amplified pace of development in the technologies to study both normal and aberrant cellular physiology has allowed for a transition from the traditional reductionist approaches to global interrogations of human biology. This transformation has created the anticipation that we will soon more effectively treat or contain most types of diseases through a 'systems-based' approach to understanding and correcting the underlying etiology of these processes. However, to accomplish these goals, we must first have a more comprehensive understanding of all the elements involved in human cellular physiology, as well as why and how they interact. With the vast number of biological components that have and are being discovered, creating methods with modern computational techniques to better organize biological elements is the next requisite step in this process. This article aims to articulate the importance of the organization of chemical elements into a periodic table had on the conversion of chemistry into a quantitative, translatable science, as well as how we can apply the lessons learned in that transition to the current transformation taking place in biology.

Name that tune: Melodic recognition by songbirds.

PubMed

Templeton, Christopher N

2016-12-01

Recent findings have indicated that European starlings perceive overall spectral shape and use this, rather than absolute pitch or timbre, to generalize between similar melodic progressions. This finding highlights yet another parallel between human and avian vocal communication systems and has many biological implications.

BIOMOLECULAR SENSING FOR BIOLOGICAL PROCESSES AND ENVIRONMENTAL MONITORING APPLICATIONS

EPA Science Inventory

Biomolecular recognition is being increasingly employed as the basis for a variety of analytical methods such as biosensors. he sensitivity, selectivity, and format versatility inherent in these methods may allow them to be adapted to solving a number of analytical problems. ltho...

36 CFR 220.3 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... practices based on clearly identified intended outcomes and monitoring to determine if management actions... those outcomes are met or re-evaluated. Adaptive management stems from the recognition that knowledge... the least harm to the biological and physical environment; it also is the alternative which best...

36 CFR 220.3 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... practices based on clearly identified intended outcomes and monitoring to determine if management actions... those outcomes are met or re-evaluated. Adaptive management stems from the recognition that knowledge... the least harm to the biological and physical environment; it also is the alternative which best...

36 CFR 220.3 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... practices based on clearly identified intended outcomes and monitoring to determine if management actions... those outcomes are met or re-evaluated. Adaptive management stems from the recognition that knowledge... the least harm to the biological and physical environment; it also is the alternative which best...

36 CFR 220.3 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... practices based on clearly identified intended outcomes and monitoring to determine if management actions... those outcomes are met or re-evaluated. Adaptive management stems from the recognition that knowledge... the least harm to the biological and physical environment; it also is the alternative which best...

Systems biology approach to understanding uterine receptivity and pregnancy loss

USDA-ARS?s Scientific Manuscript database

Infertility and subfertility represent major problems in domestic animals and humans. The majority of embryonic loss in those species occurs during the first month of gestation when pregnancy recognition and conceptus (embryo and associated extraembryonic membranes) implantation are obligatory. The ...

Integrated structural biology to unravel molecular mechanisms of protein-RNA recognition.

PubMed

Schlundt, Andreas; Tants, Jan-Niklas; Sattler, Michael

2017-04-15

Recent advances in RNA sequencing technologies have greatly expanded our knowledge of the RNA landscape in cells, often with spatiotemporal resolution. These techniques identified many new (often non-coding) RNA molecules. Large-scale studies have also discovered novel RNA binding proteins (RBPs), which exhibit single or multiple RNA binding domains (RBDs) for recognition of specific sequence or structured motifs in RNA. Starting from these large-scale approaches it is crucial to unravel the molecular principles of protein-RNA recognition in ribonucleoprotein complexes (RNPs) to understand the underlying mechanisms of gene regulation. Structural biology and biophysical studies at highest possible resolution are key to elucidate molecular mechanisms of RNA recognition by RBPs and how conformational dynamics, weak interactions and cooperative binding contribute to the formation of specific, context-dependent RNPs. While large compact RNPs can be well studied by X-ray crystallography and cryo-EM, analysis of dynamics and weak interaction necessitates the use of solution methods to capture these properties. Here, we illustrate methods to study the structure and conformational dynamics of protein-RNA complexes in solution starting from the identification of interaction partners in a given RNP. Biophysical and biochemical techniques support the characterization of a protein-RNA complex and identify regions relevant in structural analysis. Nuclear magnetic resonance (NMR) is a powerful tool to gain information on folding, stability and dynamics of RNAs and characterize RNPs in solution. It provides crucial information that is complementary to the static pictures derived from other techniques. NMR can be readily combined with other solution techniques, such as small angle X-ray and/or neutron scattering (SAXS/SANS), electron paramagnetic resonance (EPR), and Förster resonance energy transfer (FRET), which provide information about overall shapes, internal domain arrangements and dynamics. Principles of protein-RNA recognition and current approaches are reviewed and illustrated with recent studies. Copyright © 2017 Elsevier Inc. All rights reserved.

Activation of Supraoptic Oxytocin Neurons by Secretin Facilitates Social Recognition.

PubMed

Takayanagi, Yuki; Yoshida, Masahide; Takashima, Akihide; Takanami, Keiko; Yoshida, Shoma; Nishimori, Katsuhiko; Nishijima, Ichiko; Sakamoto, Hirotaka; Yamagata, Takanori; Onaka, Tatsushi

2017-02-01

Social recognition underlies social behavior in animals, and patients with psychiatric disorders associated with social deficits show abnormalities in social recognition. Oxytocin is implicated in social behavior and has received attention as an effective treatment for sociobehavioral deficits. Secretin receptor-deficient mice show deficits in social behavior. The relationship between oxytocin and secretin concerning social behavior remains to be determined. Expression of c-Fos in oxytocin neurons and release of oxytocin from their dendrites after secretin application were investigated. Social recognition was examined after intracerebroventricular or local injection of secretin, oxytocin, or an oxytocin receptor antagonist in rats, oxytocin receptor-deficient mice, and secretin receptor-deficient mice. Electron and light microscopic immunohistochemical analysis was also performed to determine whether oxytocin neurons extend their dendrites into the medial amygdala. Supraoptic oxytocin neurons expressed the secretin receptor. Secretin activated supraoptic oxytocin neurons and facilitated oxytocin release from dendrites. Secretin increased acquisition of social recognition in an oxytocin receptor-dependent manner. Local application of secretin into the supraoptic nucleus facilitated social recognition, and this facilitation was blocked by an oxytocin receptor antagonist injected into, but not outside of, the medial amygdala. In the medial amygdala, dendrite-like thick oxytocin processes were found to extend from the supraoptic nucleus. Furthermore, oxytocin treatment restored deficits of social recognition in secretin receptor-deficient mice. The results of our study demonstrate that secretin-induced dendritic oxytocin release from supraoptic neurons enhances social recognition. The newly defined secretin-oxytocin system may lead to a possible treatment for social deficits. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Phosphotyrosine recognition domains: the typical, the atypical and the versatile

PubMed Central

2012-01-01

SH2 domains are long known prominent players in the field of phosphotyrosine recognition within signaling protein networks. However, over the years they have been joined by an increasing number of other protein domain families that can, at least with some of their members, also recognise pTyr residues in a sequence-specific context. This superfamily of pTyr recognition modules, which includes substantial fractions of the PTB domains, as well as much smaller, or even single member fractions like the HYB domain, the PKCδ and PKCθ C2 domains and RKIP, represents a fascinating, medically relevant and hence intensely studied part of the cellular signaling architecture of metazoans. Protein tyrosine phosphorylation clearly serves a plethora of functions and pTyr recognition domains are used in a similarly wide range of interaction modes, which encompass, for example, partner protein switching, tandem recognition functionalities and the interaction with catalytically active protein domains. If looked upon closely enough, virtually no pTyr recognition and regulation event is an exact mirror image of another one in the same cell. Thus, the more we learn about the biology and ultrastructural details of pTyr recognition domains, the more does it become apparent that nature cleverly combines and varies a few basic principles to generate a sheer endless number of sophisticated and highly effective recognition/regulation events that are, under normal conditions, elegantly orchestrated in time and space. This knowledge is also valuable when exploring pTyr reader domains as diagnostic tools, drug targets or therapeutic reagents to combat human diseases. PMID:23134684

Spatial location of neutralizing and non-neutralizing B cell epitopes on domain 1 of ricin toxin's binding subunit.

PubMed

Rong, Yinghui; Van Slyke, Greta; Vance, David J; Westfall, Jennifer; Ehrbar, Dylan; Mantis, Nicholas J

2017-01-01

Ricin toxin's binding subunit (RTB) is a galactose-/N-acetylgalactosamine (Gal/GalNac)-specific lectin that mediates uptake and intracellular trafficking of ricin within mammalian cells. Structurally, RTB consists of two globular domains, each divided into three homologous sub-domains (α, β, γ). In this report, we describe five new murine IgG monoclonal antibodies (mAbs) against RTB: MH3, 8A1, 8B3, LF1, and LC5. The mAbs have similar binding affinities (KD) for ricin holotoxin, but displayed a wide range of in vitro toxin-neutralizing activities. Competition ELISAs indicate that the two most potent toxin-neutralizing mAbs (MH3, 8A1), as well as one of the moderate toxin-neutralizing mAbs (LF1), recognize distinct epitopes near the low affinity Gal recognition domain in RTB subdomain 1α. Evaluated in a mouse model of systemic ricin challenge, all five mAbs afforded some benefit against intoxication, but only MH3 was protective. However, neither MH3 nor 24B11, another well-characterized mAb against RTB subdomain 1α, could passively protect mice against a mucosal (intranasal) ricin challenge. This is in contrast to SylH3, a previously characterized mAb directed against an epitope near RTB's high affinity Gal/GalNac recognition element in sub-domain 2γ, which protected animals against systemic and mucosal ricin exposure. SylH3 was significantly more effective than MH3 and 24B11 at blocking ricin attachment to host cell receptors, suggesting that mucosal immunity to ricin is best imparted by antibodies that target RTB's high affinity Gal/GalNac recognition element in subdomain 2γ, not the low affinity Gal recognition domain in subdomain 1α.

A Biologically Plausible Transform for Visual Recognition that is Invariant to Translation, Scale, and Rotation.

PubMed

Sountsov, Pavel; Santucci, David M; Lisman, John E

2011-01-01

Visual object recognition occurs easily despite differences in position, size, and rotation of the object, but the neural mechanisms responsible for this invariance are not known. We have found a set of transforms that achieve invariance in a neurally plausible way. We find that a transform based on local spatial frequency analysis of oriented segments and on logarithmic mapping, when applied twice in an iterative fashion, produces an output image that is unique to the object and that remains constant as the input image is shifted, scaled, or rotated.

A Biologically Plausible Transform for Visual Recognition that is Invariant to Translation, Scale, and Rotation

PubMed Central

Sountsov, Pavel; Santucci, David M.; Lisman, John E.

2011-01-01

Visual object recognition occurs easily despite differences in position, size, and rotation of the object, but the neural mechanisms responsible for this invariance are not known. We have found a set of transforms that achieve invariance in a neurally plausible way. We find that a transform based on local spatial frequency analysis of oriented segments and on logarithmic mapping, when applied twice in an iterative fashion, produces an output image that is unique to the object and that remains constant as the input image is shifted, scaled, or rotated. PMID:22125522

Network Analysis Reveals the Recognition Mechanism for Mannose-binding Lectins

NASA Astrophysics Data System (ADS)

Zhao, Yunjie; Jian, Yiren; Zeng, Chen; Computational Biophysics Lab Team

The specific carbohydrate binding of mannose-binding lectin (MBL) protein in plants makes it a very useful molecular tool for cancer cell detection and other applications. The biological states of most MBL proteins are dimeric. Using dynamics network analysis on molecular dynamics (MD) simulations on the model protein of MBL, we elucidate the short- and long-range driving forces behind the dimer formation. The results are further supported by sequence coevolution analysis. We propose a general framework for deciphering the recognition mechanism underlying protein-protein interactions that may have potential applications in signaling pathways.

Periodic Table Target: A Game that Introduces the Biological Significance of Chemical Element Periodicity

ERIC Educational Resources Information Center

Sevcik, Richard S.; McGinty, Ragan L.; Schultz, Linda D.; Alexander, Susan V.

2008-01-01

Periodic Table Target, a game for middle school or high school students, familiarizes students with the form of the periodic table and the biological significance of different elements. The Periodic Table Target game board is constructed as a class project, and the game is played to reinforce the content. Students are assigned several elements…

Electron microprobe analysis program for biological specimens: BIOMAP

NASA Technical Reports Server (NTRS)

Edwards, B. F.

1972-01-01

BIOMAP is a Univac 1108 compatible program which facilitates the electron probe microanalysis of biological specimens. Input data are X-ray intensity data from biological samples, the X-ray intensity and composition data from a standard sample and the electron probe operating parameters. Outputs are estimates of the weight percentages of the analyzed elements, the distribution of these estimates for sets of red blood cells and the probabilities for correlation between elemental concentrations. An optional feature statistically estimates the X-ray intensity and residual background of a principal standard relative to a series of standards.

Effect of arginine methylation on the RNA recognition and cellular uptake of Tat-derived peptides.

PubMed

Li, Jhe-Hao; Chiu, Wen-Chieh; Yao, Yun-Chiao; Cheng, Richard P

2015-05-01

Arginine (Arg) methylation is a common post-translational modification that regulates gene expression and viral infection. The HIV-1 Tat protein is an essential regulatory protein for HIV proliferation, and is methylated in the cell. The basic region (residues 47-57) of the Tat protein contains six Arg residues, and is responsible for two biological functions: RNA recognition and cellular uptake. In this study, we explore the effect of three different methylation states at each Arg residue in Tat-derived peptides on the two biological functions. The Tat-derived peptides were synthesized by solid phase peptide synthesis. TAR RNA binding of the peptides was assessed by electrophoresis mobility shift assays. The cellular uptake of the peptides into Jurkat cells was determined by flow cytometry. Our results showed that RNA recognition was affected by both methylation state and position. In particular, asymmetric dimethylation at position 53 decreased TAR RNA binding affinity significantly, but unexpectedly less so upon asymmetric dimethylation at position 52. The RNA binding affinity even slightly increased upon methylation at some of the flanking Arg residues. Upon Arg methylation, the cellular uptake of Tat-derived peptides mostly decreased. Interestingly, cellular uptake of Tat-derived peptides with a single asymmetrically dimethylated Arg residue was similar to the native all Arg peptide (at 120 μM). Based on our results, TAR RNA binding apparently required both guanidinium terminal NH groups on Arg53, whereas cellular uptake apparently required guanidinium terminal NH₂ groups instead. These results should provide insight into how nature uses arginine methylation to regulate different biological functions, and should be useful for the development of functional molecules with methylated arginines. Copyright © 2015. Published by Elsevier Ltd.

An expanded framework for biomolecular visualization in the classroom: Learning goals and competencies

PubMed Central

Dries, Daniel R.; Dean, Diane M.; Listenberger, Laura L.; Novak, Walter R.P.

2016-01-01

Abstract A thorough understanding of the molecular biosciences requires the ability to visualize and manipulate molecules in order to interpret results or to generate hypotheses. While many instructors in biochemistry and molecular biology use visual representations, few indicate that they explicitly teach visual literacy. One reason is the need for a list of core content and competencies to guide a more deliberate instruction in visual literacy. We offer here the second stage in the development of one such resource for biomolecular three‐dimensional visual literacy. We present this work with the goal of building a community for online resource development and use. In the first stage, overarching themes were identified and submitted to the biosciences community for comment: atomic geometry; alternate renderings; construction/annotation; het group recognition; molecular dynamics; molecular interactions; monomer recognition; symmetry/asymmetry recognition; structure‐function relationships; structural model skepticism; and topology and connectivity. Herein, the overarching themes have been expanded to include a 12th theme (macromolecular assemblies), 27 learning goals, and more than 200 corresponding objectives, many of which cut across multiple overarching themes. The learning goals and objectives offered here provide educators with a framework on which to map the use of molecular visualization in their classrooms. In addition, the framework may also be used by biochemistry and molecular biology educators to identify gaps in coverage and drive the creation of new activities to improve visual literacy. This work represents the first attempt, to our knowledge, to catalog a comprehensive list of explicit learning goals and objectives in visual literacy. © 2016 by The International Union of Biochemistry and Molecular Biology, 45(1):69–75, 2017. PMID:27486685

Automatic Recognition and Understanding of the Driving Environment for Driver Feedback

DOT National Transportation Integrated Search

2018-01-01

A smart driving system must consider two key elements to be able to generate recommendations and make driving decisions that are effective and accurate: The environment of the car and the behavior of the driver. Our long-term goal is to develop techn...

Educational Master Planning: Creative or Cathartic?

ERIC Educational Resources Information Center

Rossmeier, Joseph G.

Recently, Northern Virginia Community College has moved into a new era of institutional development, whereby primary attention to facility planning and increasing enrollments has given way to a comprehensive, program-based, and strategic planning process which transcends all elements of the institution. Recognition is given to the integral…

Definition of a high-affinity Gag recognition structure mediating packaging of a retroviral RNA genome

PubMed Central

Gherghe, Cristina; Lombo, Tania; Leonard, Christopher W.; Datta, Siddhartha A. K.; Bess, Julian W.; Gorelick, Robert J.; Rein, Alan; Weeks, Kevin M.

2010-01-01

All retroviral genomic RNAs contain a cis-acting packaging signal by which dimeric genomes are selectively packaged into nascent virions. However, it is not understood how Gag (the viral structural protein) interacts with these signals to package the genome with high selectivity. We probed the structure of murine leukemia virus RNA inside virus particles using SHAPE, a high-throughput RNA structure analysis technology. These experiments showed that NC (the nucleic acid binding domain derived from Gag) binds within the virus to the sequence UCUG-UR-UCUG. Recombinant Gag and NC proteins bound to this same RNA sequence in dimeric RNA in vitro; in all cases, interactions were strongest with the first U and final G in each UCUG element. The RNA structural context is critical: High-affinity binding requires base-paired regions flanking this motif, and two UCUG-UR-UCUG motifs are specifically exposed in the viral RNA dimer. Mutating the guanosine residues in these two motifs—only four nucleotides per genomic RNA—reduced packaging 100-fold, comparable to the level of nonspecific packaging. These results thus explain the selective packaging of dimeric RNA. This paradigm has implications for RNA recognition in general, illustrating how local context and RNA structure can create information-rich recognition signals from simple single-stranded sequence elements in large RNAs. PMID:20974908

In search of a consumer-focused food classification system. An experimental heuristic approach to differentiate degrees of quality.

PubMed

Torres-Ruiz, Francisco J; Marano-Marcolini, Carla; Lopez-Zafra, Esther

2018-06-01

The present paper focuses on the problems that arise in food classification systems (FCSs), especially when the food product type has different levels or grades of quality. Despite the principal function of these systems being to assist the consumer (to inform, clarify and facilitate choice and purchase), they frequently have the opposite effect. Thus, the main aim of the present research involves providing orientations for the design of effective food classification systems. To address this objective, considering the context of food product consumption (related to heuristic processing), we conducted an experimental study with 720 participants. We analysed the usefulness of heuristic elements by a factorial 2 (category length: short and long) × 3 (visual signs: colours, numbers and images) design in relation to recall and recognition activities. The results showed that the elements used to make the classification more effective for consumers vary depending on whether the user seeks to prioritize the recall or the recognition of product categories. Thus, long categories with images significantly improve recognition, and short categories with colours improve recall. A series of recommendations are provided that can help to enhance FCSs and to make them more intuitive and easier to understand for consumers. Implications with regard to theory and practice are discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.

Systems biology, adverse outcome pathways, and ecotoxicology in the 21st century

EPA Science Inventory

While many definitions of systems biology exist, the majority of these contain most (if not all) of the following elements: global measurements of biological molecules to the extent technically feasible, dynamic measurements of key biological molecules to establish quantitative r...