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Journal articles on the topic 'Biologically Relevant Analytes'

Author: Grafiati
Published: 6 September 2023

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1

Wu, Luling, Qingye Yang, Liyuan Liu, Adam C. Sedgwick, Alexander J. Cresswell, Steven D. Bull, Chusen Huang, and Tony D. James. "ESIPT-based fluorescence probe for the rapid detection of hypochlorite (HOCl/ClO−)." Chemical Communications 54, no. 61 (2018): 8522–25. http://dx.doi.org/10.1039/c8cc03717e.

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2

Xu, Yifei, and Marco Bonizzoni. "Discrimination and Quantitation of Biologically Relevant Carboxylate Anions Using A [Dye•PAMAM] Complex." Sensors 21, no. 11 (May 24, 2021): 3637. http://dx.doi.org/10.3390/s21113637.

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Carboxylate anions are analytical targets with environmental and biological relevance, whose detection is often challenging in aqueous solutions. We describe a method for discrimination and quantitation of carboxylates in water buffered to pH 7.4 based on their differential interaction with a supramolecular fluorescent sensor, self-assembled from readily available building blocks. A fifth-generation poly(amidoamine) dendrimer (PAMAM G5), bound to organic fluorophores (calcein or pyranine) through noncovalent interactions, forms a [dye•PAMAM] complex responsive to interaction with carboxylates. The observed changes in absorbance, and in fluorescence emission and anisotropy, were interpreted through linear discriminant analysis (LDA) and principal component analysis (PCA) to differentiate 10 structurally similar carboxylates with a limit of discrimination around 100 μM. The relationship between the analytes’ chemical structures and the system’s response was also elucidated. This insight allowed us to extend the system’s capabilities to the simultaneous identification of the nature and concentration of unknown analytes, with excellent structural identification results and good concentration recovery, an uncommon feat for a pattern-based sensing system.
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3

Dick, Jeffrey E., Adam T. Hilterbrand, Aliaksei Boika, Jason W. Upton, and Allen J. Bard. "Electrochemical detection of a single cytomegalovirus at an ultramicroelectrode and its antibody anchoring." Proceedings of the National Academy of Sciences 112, no. 17 (April 13, 2015): 5303–8. http://dx.doi.org/10.1073/pnas.1504294112.

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We report observations of stochastic collisions of murine cytomegalovirus (MCMV) on ultramicroelectrodes (UMEs), extending the observation of discrete collision events on UMEs to biologically relevant analytes. Adsorption of an antibody specific for a virion surface glycoprotein allowed differentiation of MCMV from MCMV bound by antibody from the collision frequency decrease and current magnitudes in the electrochemical collision experiments, which shows the efficacy of the method to size viral samples. To add selectivity to the technique, interactions between MCMV, a glycoprotein-specific primary antibody to MCMV, and polystyrene bead “anchors,” which were functionalized with a secondary antibody specific to the Fc region of the primary antibody, were used to affect virus mobility. Bead aggregation was observed, and the extent of aggregation was measured using the electrochemical collision technique. Scanning electron microscopy and optical microscopy further supported aggregate shape and extent of aggregation with and without MCMV. This work extends the field of collisions to biologically relevant antigens and provides a novel foundation upon which qualitative sensor technology might be built for selective detection of viruses and other biologically relevant analytes.
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Baker, Gary A., Chase A. Munson, Eric J. Bukowski, Sheila N. Baker, and Frank V. Bright. "Assessment of One- and Two-Photon Excited Luminescence for Directly Measuring O2, pH, Na+, Mg2+, or Ca2+ in Optically Dense and Biologically Relevant Samples." Applied Spectroscopy 56, no. 4 (April 2002): 455–63. http://dx.doi.org/10.1366/0003702021955114.

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We compare the emission spectra and analytical response profiles of several semiselective luminescent probes that are commonly used to quantify nonfluorescent analytes (ruthenium(II) tris(2,2′-bipyridyl) dication, tris(4,7-diphenyl-1,10-phenanthroline)ruthenium(II) dication, SNARF®-1, fluorescein, Rhodol Green™, and Sodium™, Magnesium™, and Calcium Green™) when they are excited under one- and two-photon excitation conditions in water, aqueous solutions of dyes or fluorophores, undiluted mouse or human serum, human urine, and mouse whole blood. The results from this work can be summarized as follows. First, in cases where the probes possess ground states that are composed of multiple species in equilibrium (e.g., acid and base forms of a luminophore), the analyte-dependent emission spectra can be significantly different under one- and two-photon excitation conditions due to differences in the relative one- and two-photon cross-sections associated with the individual ground-state species. Second, for those probes that exhibit one- and two-photon dependent emission spectra, an assessment of the analytical response vs. target analyte concentration profiles show that the response dynamic range can be improved by up to 100 fold, but the response sensitivity can decrease by up to 25% for two- vs. one-photon excitation. Third, two-photon excited luminescence provides a means to use these semiselective luminescent probes to quantify nonfluorescent analytes directly within optically dense mixtures, including solutions of dyes, mouse or human serum, human urine, and mouse whole blood. Finally, two-photon excited luminescence allows one to quantify nonfluorescent analytes in a spatially defined manner within complex samples.
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5

Terán-Alcocer, Álvaro, Francisco Bravo-Plascencia, Carlos Cevallos-Morillo, and Alex Palma-Cando. "Electrochemical Sensors Based on Conducting Polymers for the Aqueous Detection of Biologically Relevant Molecules." Nanomaterials 11, no. 1 (January 19, 2021): 252. http://dx.doi.org/10.3390/nano11010252.

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Electrochemical sensors appear as low-cost, rapid, easy to use, and in situ devices for determination of diverse analytes in a liquid solution. In that context, conducting polymers are much-explored sensor building materials because of their semiconductivity, structural versatility, multiple synthetic pathways, and stability in environmental conditions. In this state-of-the-art review, synthetic processes, morphological characterization, and nanostructure formation are analyzed for relevant literature about electrochemical sensors based on conducting polymers for the determination of molecules that (i) have a fundamental role in the human body function regulation, and (ii) are considered as water emergent pollutants. Special focus is put on the different types of micro- and nanostructures generated for the polymer itself or the combination with different materials in a composite, and how the rough morphology of the conducting polymers based electrochemical sensors affect their limit of detection. Polypyrroles, polyanilines, and polythiophenes appear as the most recurrent conducting polymers for the construction of electrochemical sensors. These conducting polymers are usually built starting from bifunctional precursor monomers resulting in linear and branched polymer structures; however, opportunities for sensitivity enhancement in electrochemical sensors have been recently reported by using conjugated microporous polymers synthesized from multifunctional monomers.
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6

Peltomaa, Riikka, Bettina Glahn-Martínez, Elena Benito-Peña, and María Moreno-Bondi. "Optical Biosensors for Label-Free Detection of Small Molecules." Sensors 18, no. 12 (November 24, 2018): 4126. http://dx.doi.org/10.3390/s18124126.

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Label-free optical biosensors are an intriguing option for the analyses of many analytes, as they offer several advantages such as high sensitivity, direct and real-time measurement in addition to multiplexing capabilities. However, development of label-free optical biosensors for small molecules can be challenging as most of them are not naturally chromogenic or fluorescent, and in some cases, the sensor response is related to the size of the analyte. To overcome some of the limitations associated with the analysis of biologically, pharmacologically, or environmentally relevant compounds of low molecular weight, recent advances in the field have improved the detection of these analytes using outstanding methodology, instrumentation, recognition elements, or immobilization strategies. In this review, we aim to introduce some of the latest developments in the field of label-free optical biosensors with the focus on applications with novel innovations to overcome the challenges related to small molecule detection. Optical label-free methods with different transduction schemes, including evanescent wave and optical fiber sensors, surface plasmon resonance, surface-enhanced Raman spectroscopy, and interferometry, using various biorecognition elements, such as antibodies, aptamers, enzymes, and bioinspired molecularly imprinted polymers, are reviewed.
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7

Crapnell, Robert, Alexander Hudson, Christopher Foster, Kasper Eersels, Bart Grinsven, Thomas Cleij, Craig Banks, and Marloes Peeters. "Recent Advances in Electrosynthesized Molecularly Imprinted Polymer Sensing Platforms for Bioanalyte Detection." Sensors 19, no. 5 (March 9, 2019): 1204. http://dx.doi.org/10.3390/s19051204.

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The accurate detection of biological materials has remained at the forefront of scientific research for decades. This includes the detection of molecules, proteins, and bacteria. Biomimetic sensors look to replicate the sensitive and selective mechanisms that are found in biological systems and incorporate these properties into functional sensing platforms. Molecularly imprinted polymers (MIPs) are synthetic receptors that can form high affinity binding sites complementary to the specific analyte of interest. They utilise the shape, size, and functionality to produce sensitive and selective recognition of target analytes. One route of synthesizing MIPs is through electropolymerization, utilising predominantly constant potential methods or cyclic voltammetry. This methodology allows for the formation of a polymer directly onto the surface of a transducer. The thickness, morphology, and topography of the films can be manipulated specifically for each template. Recently, numerous reviews have been published in the production and sensing applications of MIPs; however, there are few reports on the use of electrosynthesized MIPs (eMIPs). The number of publications and citations utilising eMIPs is increasing each year, with a review produced on the topic in 2012. This review will primarily focus on advancements from 2012 in the use of eMIPs in sensing platforms for the detection of biologically relevant materials, including the development of increased polymer layer dimensions for whole bacteria detection and the use of mixed monomer compositions to increase selectivity toward analytes.
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8

Redy-Keisar, Orit, Einat Kisin-Finfer, Shiran Ferber, Ronit Satchi-Fainaro, and Doron Shabat. "Synthesis and use of QCy7-derived modular probes for the detection and imaging of biologically relevant analytes." Nature Protocols 9, no. 1 (December 5, 2013): 27–36. http://dx.doi.org/10.1038/nprot.2013.166.

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9

González-Ruiz, Víctor, Jegathalaprathaban Rajesh, Ana I. Olives, Damiano Rocchi, Jorge Gómez-Carpintero, Juan F. González, Vellaisamy Sridharan, M. Antonia Martín, and J. Carlos Menéndez. "Antioxidants as Molecular Probes: Structurally Novel Dihydro-m-Terphenyls as Turn-On Fluorescence Chemodosimeters for Biologically Relevant Oxidants." Antioxidants 9, no. 7 (July 10, 2020): 605. http://dx.doi.org/10.3390/antiox9070605.

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One interesting aspect of antioxidant organic molecules is their use as probes for the detection and quantitation of biologically relevant reactive oxidant species (ROS). In this context, a small library of dihydroterphenyl derivatives has been synthesised and studied as fluorescent chemodosimeters for detecting reactive oxygen species and hypochlorite. The fluorescence quantum yields of these molecules are negligible, while the corresponding aromatized compounds formed upon oxidation show moderate to high native fluorescence, depending on their structures. The fluorescence signal is quickly developed in the presence of trace amounts of the probe and the analytes in acetonitrile media at room temperature, with good analytical figures. ROS detection in aqueous media required incubation at 37 °C in the presence of horseradish peroxidase, and was applied to glucose quantitation by coupling glucose oxidation by O2 to fluorescence detection of H2O2. The mild reaction conditions and sensitive fluorescent response lead us to propose dihydroterphenyls with an embedded anthranilate moiety as chemosensors/chemodosimeters for ROS detection.
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10

Granzhan, Anton, Heiko Ihmels, and Maoqun Tian. "The benzo[b]quinolizinium ion as a water-soluble platform for the fluorimetric detection of biologically relevant analytes." Arkivoc 2015, no. 6 (December 1, 2015): 494–523. http://dx.doi.org/10.3998/ark.5550190.p009.339.

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11

Calhoun, Margaret C., Christopher D. Stachurski, Sara L. Winn, Evan A. Gizzie, Aaron W. Daniel, Nathan D. Schley, and David E. Cliffel. "Trace Oxygen Affects Osmium Redox Polymer Synthesis for Wired Enzymatic Biosensors." Journal of The Electrochemical Society 169, no. 1 (January 1, 2022): 016506. http://dx.doi.org/10.1149/1945-7111/ac42a0.

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Electrochemical sensors that utilize enzymes are a sensitive, inexpensive means of detecting biologically relevant analytes. These sensors are categorized based on their construction and method of signal transport. Type I sensors consist of a crosslinked enzyme on an electrode surface and are potentially subject to interference from byproducts and other biological analytes. However, type II sensors help alleviate this problem with the addition of a redox polymer layer that assists in signal transduction, thus minimizing interferences. An osmium-loaded poly(vinylimidazole) polymer (Os-PVI) is commonly used with successful results, and when combined with an enzyme yields a type II sensor. Our initial attempts at the synthesis of this polymer resulted in an unexpected osmium precursor, which had fluorescent and redox properties that did not match with the desired Os-PVI polymer. Careful exclusion of oxygen during the Os complex precursor synthesis was necessary to avoid this unexpected oxygen containing Os-precursor, which had been seen previously in mass spectrometry studies. All precursors and osmium polymers were characterized with 1H NMR, fluorescence, mass spectrometry, and cyclic voltammetry to provide a better understanding of these compounds and assist in the building of new sensors.
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12

Kang, Chungwon, Soyoun Kim, Euiyeon Lee, Jeahee Ryu, Minhyeong Lee, and Youngeun Kwon. "Genetically Encoded Sensor Cells for the Screening of Glucocorticoid Receptor (GR) Effectors in Herbal Extracts." Biosensors 11, no. 9 (September 16, 2021): 341. http://dx.doi.org/10.3390/bios11090341.

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Although in vitro sensors provide facile low-cost ways to screen for biologically active targets, their results may not accurately represent the molecular interactions in biological systems. Cell-based sensors have emerged as promising platforms to screen targets in biologically relevant environments. However, there are few examples where cell-based sensors have been practically applied for drug screening. Here, we used engineered cortisol-detecting sensor cells to screen for natural mimetics of cortisol. The sensor cells were designed to report the presence of a target through signal peptide activation and subsequent fluorescence signal translocation. The developed sensor cells were able to detect known biological targets from human-derived analytes as well as natural product extracts, such as deer antlers and ginseng. The multi-use capability and versatility to screen in different cellular environments were also demonstrated. The sensor cells were used to identify novel GR effectors from medicinal plant extracts. Our results suggest that decursin from dongquai had the GR effector function as a selective GR agonist (SEGRA), making it a potent drug candidate with anti-inflammatory activity. We demonstrated the superiority of cell-based sensing technology over in vitro screening, proving its potential for practical drug screening applications that leads to the function-based discovery of target molecules.
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13

Zhang, Xiaozhou, Sabrina Heng, Jinxin Pei, Jacqueline Morey, Christopher McDevitt, and Andrew Abell. "A Liposomal Platform for Sensing of Extracellular Analytes Near Cells." Biosensors 8, no. 4 (November 26, 2018): 117. http://dx.doi.org/10.3390/bios8040117.

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Cell-permeable fluorescent chemosensors (calcein, monochlorobimane, and a recently reported spiropyran-based sensor SP2) have been incorporated into yeast total lipid extract-based liposomes to suppress inherent cell permeability to allow the detection of extracellular Ca2+, GSH, and Zn2+, respectively. The repurposed sensors have enhanced aqueous solubility and the ability to quantitatively measure biologically relevant concentrations of Ca2+ (0.25 mM–1 mM), Zn2+ (6.25 µM–50 µM), and GSH (0.25 mM–1 mM) by fluorescence in aqueous media. In addition, the liposomal sensors are nontoxic to HEK293 cells and have the ability to detect exogenously added Zn2+ (1 mM), Ca2+ (1 mM), or GSH (1 mM) near cells without internalisation. This new sensing platform provides a means to repurpose a range of intracellular fluorescent sensors to specifically detect extracellular analytes, while also improving biocompatibility for overall enhanced use in a wide range of biomedical applications.
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14

Johnson, Phil E., Sabine Baumgartner, Thomas Aldick, Conrad Bessant, Valeria Giosafatto, Julia Heick, Gianfranco Mamone, et al. "Current Perspectives and Recommendations for the Development of Mass Spectrometry Methods for the Determination of Allergens in Foods." Journal of AOAC INTERNATIONAL 94, no. 4 (July 1, 2011): 1026–33. http://dx.doi.org/10.1093/jaoac/94.4.1026.

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Abstract Allergen detection and quantification is an essential part of allergen management as practiced by food manufacturers. Recently, protein MS methods (in particular, multiple reaction monitoring experiments) have begun to be adopted by the allergen detection community to provide an alternative technique to ELISA and PCR methods. MS analysis of proteins in foods provides additional challenges to the analyst, both in terms of experimental design and methodology: (1) choice of analyte, including multiplexing to simultaneously detect several biologically relevant molecules able to trigger allergic reactions; (2) choice of processing stable peptide markers for different target analytes that should be placed in publicly available databases; (3) markers allowing quantification (e.g., through standard addition or isotopically labeled peptide standards); (4) optimization of protease digestion protocols to ensure reproducible and robust method development; and (5) effective validation of methods and harmonization of results through the use of naturally incurred reference materials spanning several types of food matrix.
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15

Bouilly, Delphine, Anouk Béraud, Claudia M. Bazan, Amira Bencherif, and Madline Sauvage. "(Invited) Surface Functionalization of Graphene Field-Effect Transistors for Biosensing Applications." ECS Meeting Abstracts MA2022-01, no. 8 (July 7, 2022): 683. http://dx.doi.org/10.1149/ma2022-018683mtgabs.

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Graphene field-effect transistors (GFETs) present beneficial features for their application as biomolecular or chemical sensors. Due to their atomically-thin 2D dimensionality, their high electrical conductance is particularly sensitive to small changes in the distribution of charged species near the graphene surface. Taking advantage of this property, GFET sensors have been designed to report the detection or quantitation of various types of biologically-relevant molecular analytes such as nucleic acids, proteins, ions or small molecules. By analyzing data from published literature on GFET bioanalytical sensors, we have recently shown that the detection metrics of such sensors vary enormously between studies, and argued that this variance is mainly driven by disparities in the bio-recognition interface [1]. Indeed, the selectivity of GFET sensors must be engineered, typically by covering the graphene surface with biological molecules having a specific affinity for the chosen analyte (e.g. antibodies to capture the corresponding antigen, ssDNA to capture its complementary sequence). Yet, the coverage, orientation, stability and interactions between immobilized probes, blocking species and captured analytes are often not well known or controlled. In this presentation, I will discuss our efforts to understand and regulate the surface functionalization of graphene field-effect transistors. Using electrical conductance measurements and Raman spectroscopy, I will characterize the response of devices to both covalent chemistry, using aryldiazonium reagents, and non-covalent chemistry, using pyrene derivatives. I will describe our recent developments in controlling these functionalization routes, and compare their use for further bioconjugation with molecular probes for bioanalytical purposes. [1] A. Béraud, M. Sauvage, C. M. Bazán, M. Tie, A. Bencherif and D. Bouilly. Graphene Field-Effect Transistors as Bioanalytical Sensors: Design, Operation and Performance. Analyst 146, 403-428 (2021) https://doi.org/10.1039/D0AN01661F
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16

Bereza-Malcolm, Lara T., and Ashley E. Franks. "Coupling anaerobic bacteria and microbial fuel cells as whole-cell environmental biosensors." Microbiology Australia 36, no. 3 (2015): 129. http://dx.doi.org/10.1071/ma15045.

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Microorganisms have evolved to respond to environmental factors allowing adaption to changing conditions and minimisation of potential harm. Microbes have the ability to sense a wide range of biotic and abiotic factors including nutrient levels, analytes, temperature, contaminants, community quorum, and metabolic activity. Due to this ability, the use of whole-cell microbes as biosensors is attractive as it can provide real-time in situ information on biologically relevant factors through qualitative and quantitative outputs. Interestingly, many of the environments where these biosensors will be of most of use lack oxygen; and as such the use of anaerobic microorganisms to sense environmental factors with easy to use outputs is essential. Furthermore, sensing of contaminants can be linked with bioremediation of known contaminated environments, allowing a flexible, multiplexed device.
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17

Siska, William, Aradhana Gupta, Lindsay Tomlinson, Niraj Tripathi, and Barbara von Beust. "Recommendations for Clinical Pathology Data Generation, Interpretation, and Reporting in Target Animal Safety Studies for Veterinary Drug Development." International Journal of Toxicology 36, no. 4 (June 6, 2017): 293–302. http://dx.doi.org/10.1177/1091581817711876.

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Clinical pathology testing is routinely performed in target animal safety studies in order to identify potential toxicity associated with administration of an investigational veterinary pharmaceutical product. Regulatory and other testing guidelines that address such studies provide recommendations for clinical pathology testing but occasionally contain outdated analytes and do not take into account interspecies physiologic differences that affect the practical selection of appropriate clinical pathology tests. Additionally, strong emphasis is often placed on statistical analysis and use of reference intervals for interpretation of test article–related clinical pathology changes, with limited attention given to the critical scientific review of clinically, toxicologically, or biologically relevant changes. The purpose of this communication from the Regulatory Affairs Committee of the American Society for Veterinary Clinical Pathology is to provide current recommendations for clinical pathology testing and data interpretation in target animal safety studies and thereby enhance the value of clinical pathology testing in these studies.
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18

Soleymani, Leyla, Richa Pandey, Amanda Victorious, Sudip Saha, Sadman Sakib, Zijie Zhang, Yingfu Li, and Igor Zhitomirsky. "(Invited) Developing Universal Sensing Strategies-Combining Functional Nucleic Acids with Photoelectrochemical and Electrochemical Signal Transduction." ECS Meeting Abstracts MA2022-02, no. 61 (October 9, 2022): 2225. http://dx.doi.org/10.1149/ma2022-02612225mtgabs.

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Biosensors combine biorecognition with signal transduction for analyzing biologically-relevant analytes. Nucleic acids are powerful building blocks for biosensors and are used both for biorecognition and facilitating signal transduction. In this talk, we will show that functional nucleic acids can be specifically engineered for electrochemical signal transduction. We develop both aptamers and DNAzymes that are designed for electrochemical signal transduction. Electrochemical biosensors relying on functional nucleic acids are used herein to detect bacterial and viral infectious diseases in native clinical samples such as saliva and urine. In addition to electrochemical signal transduction, we show that nucleic acids serve as powerful tools in photoelectrochemical signal transduction. We use double stranded DNA for biorecognition and for serving as a nano-ruler for tuning the separation between a photoelectrochemical label and the electrode surface. This allows us to switch the signal transduction capability of the system between signal-on and signal-off. Additionally, engineering functional nucleic acids for photoelectrochemical signal transduction, enabled us to develop a new class of pathogen biosensors. These biosensors are used in direct analysis of bacteria in water.
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Yousef, Malik, Ege Ülgen, and Osman Uğur Sezerman. "CogNet: classification of gene expression data based on ranked active-subnetwork-oriented KEGG pathway enrichment analysis." PeerJ Computer Science 7 (February 22, 2021): e336. http://dx.doi.org/10.7717/peerj-cs.336.

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Most of the traditional gene selection approaches are borrowed from other fields such as statistics and computer science, However, they do not prioritize biologically relevant genes since the ultimate goal is to determine features that optimize model performance metrics not to build a biologically meaningful model. Therefore, there is an imminent need for new computational tools that integrate the biological knowledge about the data in the process of gene selection and machine learning. Integrative gene selection enables incorporation of biological domain knowledge from external biological resources. In this study, we propose a new computational approach named CogNet that is an integrative gene selection tool that exploits biological knowledge for grouping the genes for the computational modeling tasks of ranking and classification. In CogNet, the pathfindR serves as the biological grouping tool to allow the main algorithm to rank active-subnetwork-oriented KEGG pathway enrichment analysis results to build a biologically relevant model. CogNet provides a list of significant KEGG pathways that can classify the data with a very high accuracy. The list also provides the genes belonging to these pathways that are differentially expressed that are used as features in the classification problem. The list facilitates deep analysis and better interpretability of the role of KEGG pathways in classification of the data thus better establishing the biological relevance of these differentially expressed genes. Even though the main aim of our study is not to improve the accuracy of any existing tool, the performance of the CogNet outperforms a similar approach called maTE while obtaining similar performance compared to other similar tools including SVM-RCE. CogNet was tested on 13 gene expression datasets concerning a variety of diseases.
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Fershal, M., and N. Chubirka. "ELABORATION OF CHEMICAL SENSOR SENSITIVE TO BORON BENZILATE." Scientific Bulletin of the Uzhhorod University. Series «Chemistry» 48, no. 2 (May 23, 2023): 43–53. http://dx.doi.org/10.24144/2414-0260.2022.2.43-53.

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Over the last decades, the development of simple and selective methods for the determination of organic analytes has been getting attention from analytical chemists. Particularly, the same applies to biologically active substances of natural and artificial origin, precursors, and metabolites of pharmaceuticals[1]. An example of such substance is benzylic acid (2, 2-diphenyl-2-hydroxyacetic acid) (BA), gravimetric reagent for zirconium [2], a product of hydrolysis and a metabolite of the antispasmodic and sedative drugs Pipoxolan, Benactyzine, or Metacin [3]. The complexes of BA have been proposed as corrosion inhibitors for some steels and aluminum alloys [4]. Its derivatives are being studied as new analgesics [5], anticancer drugs [6], and also as deep eutectic solvents [7]. The BA was used in the synthesis of the psychotropic combatant substance 3-quinuclidinyl benzilate (BZ), which causes mental slowing, and hydrolyzes to form BC [8-11]. For BA determination high-performance liquid chromatography and chromatography-mass spectrometry [12-15] are mostly used, hence the development of simple methods for determining benzylic acid is pertinent and relevant. Boric acid is known to form compounds with diols, α-hydroxy acids, dicarboxylic acids, and α-diketones [16] and that was used in developing potentiometric sensors for the determination of mandelic acid and vitamin C [17, 18]. As BA also forms complexes with boric acid and various metals [19, 20] the H3BO3 has been used in the present study as a reagent for obtaining boric acid benzilate ester - the analytical form of BA, as well as the ionic associate of its anion with tetraoctylammonium(TOA) as the active substance of a potentiometric PVC plasticized sensor sensitive to the mentioned above analytical form. The complex formation has been confirmed using IR spectroscopy. On the IR spectrum of BA, the absorption bands in the region of 3393. 69 cm-1 and 1715. 77 cm-1, which correspond to the vibrations of –ОН and >С=О groups, respectively have been detected [23]. At the same time, in the IR spectrum of the complex, the absorption band of –ОН groups in the region of 3300 - 3400 cm-1 was absent, that indicates their participation in the formation of ether bonds, additionally, the intensive bands of >C=O in the region of 1723. 41 cm-1 and 1742. 05 cm-1 has appeared. The ion pair of tetraoctylammonium cation with synthesized complex ion [B(Benz)2]- has been used as an active substance of the potentiometric sensor. The metrological and operational characteristics of the sensor and the optimal conditions of the analytical form obtaining have been systematically studied. The optimized composition of the sensitive PVC membrane was 0. 1% of IP, 33. 0% of PVC and 66. 9% of o-NFOE. For high yield [B(Benz)(ОН)2]--analytical form preparation the boiling of BA for 15 minutes in the medium of a buffer solution that consists of H3BO3 (sat.) - 0. 1 M NaOH - 0. 1 M H3PO4 with a pH of 5. 5 is needed. In optimal conditions, the slope of the sensor developed is close to the theoretical value of 55. 2 mV/pС, has a detection limit pCmin= 4. 9, and the linearity range 10-2 – 10-4mol/l. The response time of a sensor ranges from 5 to 30 seconds depending on the added quantity. High selectivity of the sensor to metal cations, anions of organic and inorganic acids, as well as polyatomic alcohols that are able to form complex compounds with BA or H3BO3 has been shown. The sensor developed was used for benzylic acid analysis in "Difenin", which can be formed during the synthesis of this drug [27]. It has been shown that the use of potentiometry in combination with the conversion of the analyte into an active form using a cheap reagent - boric acid allows to develop simple methods of the organic analytes determination for which the use of potentiometry is not common. Preparation of the complex boronate ester of benzylic acid in the sample provides the selectivity of the technique to the target analyte. Keywords: benzylic acid; boron benzilate; potentiometric sensor; ion pair.
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21

Su, Mack, Laurie A. Steiner, Hannah Bogardus, Vincent P. Schulz, Ross C. Hardison, and Patrick G. Gallagher. "Identification of Biologicaly Relevant Enhancers in Human Erythroid Cells." Blood 120, no. 21 (November 16, 2012): 368. http://dx.doi.org/10.1182/blood.v120.21.368.368.

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Abstract Abstract 368 Identification of cell-type specific enhancers is important for understanding the regulation of programs controlling cellular development and differentiation. Recent studies utilizing genomic methodologies have shown that enhancers are frequently associated with biologically relevant and disease-associated genetic variants. Enhancers are typically marked by the co-transcriptional activator protein p300 or by groups of cell-expressed transcription factors. We hypothesized that a unique set of enhancers regulate gene expression in human erythroid cells, a highly specialized cell type evolved to provide adequate amounts of oxygen throughout the body. Using chromatin immunoprecipitation followed by massively parallel sequencing, genome-wide maps of candidate enhancers were constructed for p300 and four transcription factors, GATA1, NF-E2, KLF1, and SCL, in primary human erythroid cells. These data were combined with parallel gene expression analyses and candidate enhancers identified. Cell and tissue-type specific enhancers act over distances of tens to hundreds of kilobases, thus bona fide erythroid enhancers are expected to be enriched in the genomic vicinity of genes expressed and functional in erythroid cells. Sites of occupancy were correlated with levels of gene expression. Promoter sites within 2kb of annotated transcriptional start sites (TSS) were excluded. Consistent with their predicted function, there was significant enrichment of p300 peaks within 2–50kb of the TSS of genes highly expressed in erythroid cells c.f. peaks >100kb of a TSS. There was also significant enrichment of combinations of 2, 3, and 4 co-localizing erythroid transcription factor peaks within 2–50kb of the TSS of genes highly expressed in erythroid cells. In contrast, similar to other cell type-specific enhancers, there was no enrichment of p300 or erythroid transcription factor sites within 2–50kb of genes highly expressed in nonerythroid cells. When analyses were performed comparing a set of erythroid-specific genes vs. a random set of genes, there was significant enrichment of combinations of 2, 3, and 4 co-localizing erythroid transcription factor binding sites, but not p300, within 2–50kb of the TSS of erythroid-specific genes. Evolutionary analyses revealed high conservation between man and chimp for p300 and erythroid transcription factors. However, there was a very large falloff between human and mouse, with. Disclosures: No relevant conflicts of interest to declare.
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SIVACHENKO, ANDREY Y., ANTON YURYEV, NIKOLAI DARASELIA, and ILYA MAZO. "MOLECULAR NETWORKS IN MICROARRAY ANALYSIS." Journal of Bioinformatics and Computational Biology 05, no. 02b (April 2007): 429–56. http://dx.doi.org/10.1142/s0219720007002795.

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Microarray-based characterization of tissues, cellular and disease states, and environmental condition and treatment responses provides genome-wide snapshots containing large amounts of invaluable information. However, the lack of inherent structure within the data and strong noise make extracting and interpreting this information and formulating and prioritizing domain relevant hypotheses difficult tasks. Integration with different types of biological data is required to place the expression measurements into a biologically meaningful context. A few approaches in microarray data interpretation are discussed with the emphasis on the use of molecular network information. Statistical procedures are demonstrated that superimpose expression data onto the transcription regulation network mined from scientific literature and aim at selecting transcription regulators with significant patterns of expression changes downstream. Tests are suggested that take into account network topology and signs of transcription regulation effects. The approaches are illustrated using two different expression datasets, the performance is compared, and biological relevance of the predictions is discussed.
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Deng, Xutao, Huimin Geng, and Hesham H. Ali. "Cross-platform Analysis of Cancer Biomarkers: A Bayesian Network Approach to Incorporating Mass Spectrometry and Microarray Data." Cancer Informatics 3 (January 2007): 117693510700300. http://dx.doi.org/10.1177/117693510700300001.

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Many studies showed inconsistent cancer biomarkers due to bioinformatics artifacts. In this paper we use multiple data sets from microarrays, mass spectrometry, protein sequences, and other biological knowledge in order to improve the reliability of cancer biomarkers. We present a novel Bayesian network (BN) model which integrates and cross-annotates multiple data sets related to prostate cancer. The main contribution of this study is that we provide a method that is designed to find cancer biomarkers whose presence is supported by multiple data sources and biological knowledge. Relevant biological knowledge is explicitly encoded into the model parameters, and the biomarker finding problem is formulated as a Bayesian inference problem. Besides diagnostic accuracy, we introduce reliability as another quality measurement of the biological relevance of biomarkers. Based on the proposed BN model, we develop an empirical scoring scheme and a simulation algorithm for inferring biomarkers. Fourteen genes/proteins including prostate specific antigen (PSA) are identified as reliable serum biomarkers which are insensitive to the model assumptions. The computational results show that our method is able to find biologically relevant biomarkers with highest reliability while maintaining competitive predictive power. In addition, by combining biological knowledge and data from multiple platforms, the number of putative biomarkers is greatly reduced to allow more-focused clinical studies.
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Shoemaker, Benjamin A., Anna R. Panchenko, and Stephen H. Bryant. "Finding biologically relevant protein domain interactions: Conserved binding mode analysis." Protein Science 15, no. 2 (February 2006): 352–61. http://dx.doi.org/10.1110/ps.051760806.

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25

Koepke, Tyson, Scott Schaeffer, Artemus Harper, Federico Dicenta, Mark Edwards, Robert J. Henry, Birger L. Møller, et al. "Comparative genomics analysis in Prunoideae to identify biologically relevant polymorphisms." Plant Biotechnology Journal 11, no. 7 (June 13, 2013): 883–93. http://dx.doi.org/10.1111/pbi.12081.

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Powell, A. K., and S. L. Heath. "X-ray structural analysis of biologically relevant aluminium(III) complexes." Coordination Chemistry Reviews 149 (May 1996): 59–80. http://dx.doi.org/10.1016/s0010-8545(96)90012-0.

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Powell, A. "X-ray structural analysis of biologically relevant aluminium (III) complexes." Coordination Chemistry Reviews 149, no. 1 (March 1996): 59–80. http://dx.doi.org/10.1016/0010-8545(95)01161-7.

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Lawrence, Nathan S., Emma L. Beckett, James Davis, and Richard G. Compton. "Advances in the Voltammetric Analysis of Small Biologically Relevant Compounds." Analytical Biochemistry 303, no. 1 (April 2002): 1–16. http://dx.doi.org/10.1006/abio.2002.5584.

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Frigyesi, Attila, and Mattias Höglund. "Non-Negative Matrix Factorization for the Analysis of Complex Gene Expression Data: Identification of Clinically Relevant Tumor Subtypes." Cancer Informatics 6 (January 2008): CIN.S606. http://dx.doi.org/10.4137/cin.s606.

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Non-negative matrix factorization (NMF) is a relatively new approach to analyze gene expression data that models data by additive combinations of non-negative basis vectors (metagenes). The non-negativity constraint makes sense biologically as genes may either be expressed or not, but never show negative expression. We applied NMF to five different microarray data sets. We estimated the appropriate number metagens by comparing the residual error of NMF reconstruction of data to that of NMF reconstruction of permutated data, thus finding when a given solution contained more information than noise. This analysis also revealed that NMF could not factorize one of the data sets in a meaningful way. We used GO categories and pre defined gene sets to evaluate the biological significance of the obtained metagenes. By analyses of metagenes specific for the same GO-categories we could show that individual metagenes activated different aspects of the same biological processes. Several of the obtained metagenes correlated with tumor subtypes and tumors with characteristic chromosomal translocations, indicating that metagenes may correspond to specific disease entities. Hence, NMF extracts biological relevant structures of microarray expression data and may thus contribute to a deeper understanding of tumor behavior.
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Desharnais, Brigitte, Marie-Jo Lajoie, Julie Laquerre, Stéphanie Savard, Pascal Mireault, and Cameron D. Skinner. "A Tool for Automatic Correction of Endogenous Concentrations: Application to BHB Analysis by LC–MS-MS and GC-MS." Journal of Analytical Toxicology 43, no. 7 (May 29, 2019): 512–19. http://dx.doi.org/10.1093/jat/bkz024.

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Abstract Several substances relevant for forensic toxicology purposes have an endogenous presence in biological matrices: beta-hydroxybutyric acid (BHB), gamma-hydroxybutyric acid (GHB), steroids and human insulin, to name only a few. The presence of significant amounts of these endogenous substances in the biological matrix used to prepare calibration standards and quality control samples (QCs) can compromise validation steps and quantitative analyses. Several approaches to overcome this problem have been suggested, including using an analog matrix or analyte, relying entirely on standard addition analyses for these analytes, or simply ignoring the endogenous contribution provided that it is small enough. Although these approaches side-step the issue of endogenous analyte presence in spiked matrix-matched samples, they create serious problems with regards to the accuracy of the analyses or production capacity. We present here a solution that addresses head-on the problem of endogenous concentrations in matrices used for calibration standards and quality control purposes. The endogenous analyte concentration is estimated via a standard-addition type process. This estimated concentration, plus the spiked concentration are then used as the de facto analyte concentration present in the sample. These de facto concentrations are then used in data analysis software (MultiQuant, Mass Hunter, etc.) as the sample’s concentration. This yields an accurate quantification of the analyte, free from interference of the endogenous contribution. This de facto correction has been applied in a production setting on two BHB quantification methods (GC-MS and LC–MS-MS), allowing the rectification of BHB biases of up to 30 μg/mL. The additional error introduced by this correction procedure is minimal, although the exact amount will be highly method-dependent. The endogenous concentration correction process has been automated with an R script. The final procedure is therefore highly efficient, only adding four mouse clicks to the data analysis operations.
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Fasterius, Erik, and Cristina Al-Khalili Szigyarto. "seqCAT: a Bioconductor R-package for variant analysis of high throughput sequencing data." F1000Research 7 (September 14, 2018): 1466. http://dx.doi.org/10.12688/f1000research.16083.1.

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High throughput sequencing technologies are flourishing in the biological sciences, enabling unprecedented insights into e.g. genetic variation, but require extensive bioinformatic expertise for the analysis. There is thus a need for simple yet effective software that can analyse both existing and novel data, providing interpretable biological results with little bioinformatic prowess. We present seqCAT, a Bioconductor toolkit for analysing genetic variation in high throughput sequencing data. It is a highly accessible, easy-to-use and well-documented R-package that enables a wide range of researchers to analyse their own and publicly available data, providing biologically relevant conclusions and publication-ready figures. SeqCAT can provide information regarding genetic similarities between an arbitrary number of samples, validate specific variants as well as define functionally similar variant groups for further downstream analyses. Its ease of use, installation, complete data-to-conclusions functionality and the inherent flexibility of the R programming language make seqCAT a powerful tool for variant analyses compared to already existing solutions. A publicly available dataset of liver cancer-derived organoids is analysed herein using the seqCAT package, demonstrating that the organoids are genetically stable. A previously known liver cancer-related mutation is additionally shown to be present in a sample though it was not listed in the original publication. Differences between DNA- and RNA-based variant calls in this dataset are also analysed revealing a high median concordance of 97.5%.
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Garman, Katherine S., Chaitanya R. Acharya, Ryan D. Madanick, Dawn Provenzale, Anil Potti, and Nicholas J. Shaheen. "T1914 Distinguishing Biologically Relevant Phenotypes in Barrett's Esophagus: A Microarray Analysis." Gastroenterology 136, no. 5 (May 2009): A—599—A—600. http://dx.doi.org/10.1016/s0016-5085(09)62762-1.

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33

Coskun, Cihan, Berrin Bercik Inal, Humeyra Ozturk Emre, Sehide Baz, Alper Gumus, Derya Sonmez, Bagnu Orhan, Muhammed Emin Duz, Erdinc Serin, and Macit Koldas. "Evaluation of biological variations in glucose and glycated hemoglobin levels in healthy individuals." Turkish Journal of Biochemistry 43, no. 5 (December 8, 2017): 495–501. http://dx.doi.org/10.1515/tjb-2017-0165.

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Abstract Objective: In this study, we firstly aimed to determine components of biological variations (BVCs) in levels of glucose and glycated hemoglobin (HbA1c) in detail based on guidance from relevant organizations and experts. We also investigated whether reference intervals for both analytes were useful for evaluations, particularly consecutive test results. Methods: The study group consisted of 36 healthy volunteers. Samples were collected from each individual 4 times every 2 weeks for 45 days. All samples were assayed in duplicate within a single run. Finally, we estimated BVCs and the analytical performance specifications of both analytes. Results: Our results were fairly compatible with current biological variations (BVs) in both analytes reported in a database. It was calculated as within biological variation (CVI)=4.2% and between-subject variation (CVG)=5.3% for glucose while calculating as CVI=1.7% and CVG=4.5% for HbA1c. According to these results, the index of individuality (II) of glucose was higher than 0.6 while HbA1c’s II was lower than this value. Conclusion: We thought that guidelines from relevant international organizations should be followed to standardize the study design and to appropriately calculate BVCs for any analyte in BV studies. Finally, reference change value should be used to evaluate meaningful differences in HbA1c levels instead of reference interval.
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Negredo, Adelia De Miguel. "Relevance of temperament traits in sexual fluidity in a sample of Spanish young university students." Advances in Social Sciences Research Journal 7, no. 5 (May 31, 2020): 369–81. http://dx.doi.org/10.14738/assrj.75.8257.

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Assessing the relevance of temperament traits to predict sexual fluidity, taking into account gender and sexual orientation, was the main goal of this paper. Participants (435 Spanish young-adults students, 310 females and 125 males) completed an online questionnaire, which included measures of sexual fluidity, the short version of the Big Five Inventory, two factors of Sensation Seeking Scale, and State-Trait Anxiety Inventory. Analyses showed gender differences in sexual fluidity, anxiety and sensation seeking. Sexually fluid individuals also reported higher scores than no-sexually fluid individuals in these factors. Bisexual orientation, anxiety-trait and sensation seeking were good predictors of female sexual fluidity. Anxiety state was relevant to male sexual fluidity. We concluded that sexual fluidity can be related to emotional and biological personality traits, but it is not clear if the origin of this relationship is only biologically caused or depends on experience moderator effects. Again, the controversy nature-nurture is needed to be considered when assessing sexual fluidity across life-span.
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35

Golovan, Serguei, and Mainul Husain. "Identification of biologically significant genes using Gene Ontology (GO) and pathways analysis (144.16)." Journal of Immunology 184, no. 1_Supplement (April 1, 2010): 144.16. http://dx.doi.org/10.4049/jimmunol.184.supp.144.16.

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Abstract Due to the small sample size and high dimensionality, it is not always possible to identify all of the biologically relevant genes from microarray analysis by simply selecting an arbitrary fold change and p-value thresholds. Such concerns are especially relevant in the analysis of immune response. It has been long known that large variability exist in immune responsiveness with the coefficient of variation (CV) as high as 230% reported for antibody response. Similarly, immune related genes were shown to have CV in excess of 100%. As a consequence, some genes involved in immune response will never be detected as differentially expressed as the number of replications required to detect statistically significant effects may be unobtainable even in well-designed experiments. To better understand which biological pathways were affected by allergenic response to ovomucoid treatment in mouse spleen, two gene sets for GO analysis were selected using different selection criteria. First set included differentially expressed genes that were biologically and statistically significant between treatments (>1.5 fold, P<0.05). Genes for the second gene set were selected based only on their biological significance (>1.5 fold). It is demonstrated that not only new biologically significant genes were identified in previously detected GO and pathway categories (p<0.05) but completely new categories (p<0.05) were detected using second gene set.
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36

Harrington, Sophie A., Anna E. Backhaus, Ajit Singh, Keywan Hassani-Pak, and Cristobal Uauy. "The Wheat GENIE3 Network Provides Biologically-Relevant Information in Polyploid Wheat." G3: Genes|Genomes|Genetics 10, no. 10 (August 3, 2020): 3675–86. http://dx.doi.org/10.1534/g3.120.401436.

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Gene regulatory networks are powerful tools which facilitate hypothesis generation and candidate gene discovery. However, the extent to which the network predictions are biologically relevant is often unclear. Recently a GENIE3 network which predicted targets of wheat transcription factors was produced. Here we used an independent RNA-Seq dataset to test the predictions of the wheat GENIE3 network for the senescence-regulating transcription factor NAM-A1 (TraesCS6A02G108300). We re-analyzed the RNA-Seq data against the RefSeqv1.0 genome and identified a set of differentially expressed genes (DEGs) between the wild-type and nam-a1 mutant which recapitulated the known role of NAM-A1 in senescence and nutrient remobilisation. We found that the GENIE3-predicted target genes of NAM-A1 overlap significantly with the DEGs, more than would be expected by chance. Based on high levels of overlap between GENIE3-predicted target genes and the DEGs, we identified candidate senescence regulators. We then explored genome-wide trends in the network related to polyploidy and found that only homeologous transcription factors are likely to share predicted targets in common. However, homeologs which vary in expression levels across tissues are less likely to share predicted targets than those that do not, suggesting that they may be more likely to act in distinct pathways. This work demonstrates that the wheat GENIE3 network can provide biologically-relevant predictions of transcription factor targets, which can be used for candidate gene prediction and for global analyses of transcription factor function. The GENIE3 network has now been integrated into the KnetMiner web application, facilitating its use in future studies.
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37

Fasterius, Erik, and Cristina Al-Khalili Szigyarto. "seqCAT: a Bioconductor R-package for variant analysis of high throughput sequencing data." F1000Research 7 (August 12, 2019): 1466. http://dx.doi.org/10.12688/f1000research.16083.2.

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High throughput sequencing technologies are flourishing in the biological sciences, enabling unprecedented insights into e.g. genetic variation, but require extensive bioinformatic expertise for the analysis. There is thus a need for simple yet effective software that can analyse both existing and novel data, providing interpretable biological results with little bioinformatic prowess. We present seqCAT, a Bioconductor toolkit for analysing genetic variation in high throughput sequencing data. It is a highly accessible, easy-to-use and well-documented R-package that enables a wide range of researchers to analyse their own and publicly available data, providing biologically relevant conclusions and publication-ready figures. SeqCAT can provide information regarding genetic similarities between an arbitrary number of samples, validate specific variants as well as define functionally similar variant groups for further downstream analyses. Its ease of use, installation, complete data-to-conclusions functionality and the inherent flexibility of the R programming language make seqCAT a powerful tool for variant analyses compared to already existing solutions. A publicly available dataset of liver cancer-derived organoids is analysed herein using the seqCAT package, corroborating the original authors' conclusions that the organoids are genetically stable. A previously known liver cancer-related mutation is additionally shown to be present in a sample though it was not listed in the original publication. Differences between DNA- and RNA-based variant calls in this dataset are also analysed revealing a high median concordance of 97.5%. SeqCAT is an open source software under a MIT licence available at https://bioconductor.org/packages/release/bioc/html/seqCAT.html.
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38

Yu, Pei, and Xiangyu Wang. "Analysis on recurrence behavior in oscillating networks of biologically relevant organic reactions." Mathematical Biosciences and Engineering 16, no. 5 (2019): 5263–86. http://dx.doi.org/10.3934/mbe.2019263.

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39

Senthilkumar, Kittusamy, Jon I. Mujika, Kara E. Ranaghan, Frederick R. Manby, Adrian J. Mulholland, and Jeremy N. Harvey. "Analysis of polarization in QM/MM modelling of biologically relevant hydrogen bonds." Journal of The Royal Society Interface 5, suppl_3 (September 2, 2008): 207–16. http://dx.doi.org/10.1098/rsif.2008.0243.focus.

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Combined quantum mechanics/molecular mechanics (QM/MM) methods are increasingly important for the study of chemical reactions and systems in condensed phases. Here, we have tested the accuracy of a density functional theory-based QM/MM implementation (B3LYP/6-311+G(d,p)/CHARMM27) on a set of biologically relevant interactions by comparison with full QM calculations. Intermolecular charge transfer due to hydrogen bond formation is studied to assess the severity of spurious polarization of QM atoms by MM point charges close to the QM/MM boundary. The changes in total electron density and natural bond orbital atomic charges due to hydrogen bond formation in selected complexes obtained at the QM/MM level are compared with full QM results. It is found that charge leakage from the QM atoms to MM atomic point charges close to the QM/MM boundary is not a serious problem, at least with limited basis sets. The results are encouraging in showing that important properties of key biomolecular interactions can be treated well at the QM/MM level employing good-quality levels of QM theory.
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40

Saithong, Treenut, Kevin J. Painter, and Andrew J. Millar. "Consistent Robustness Analysis (CRA) Identifies Biologically Relevant Properties of Regulatory Network Models." PLoS ONE 5, no. 12 (December 16, 2010): e15589. http://dx.doi.org/10.1371/journal.pone.0015589.

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41

Pinese, Mark, Christopher J. Scarlett, James G. Kench, Emily K. Colvin, Davendra Segara, Susan M. Henshall, Robert L. Sutherland, and Andrew V. Biankin. "Messina: A Novel Analysis Tool to Identify Biologically Relevant Molecules in Disease." PLoS ONE 4, no. 4 (April 28, 2009): e5337. http://dx.doi.org/10.1371/journal.pone.0005337.

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42

Glazier, Douglas S. "The Relevance of Time in Biological Scaling." Biology 12, no. 8 (August 3, 2023): 1084. http://dx.doi.org/10.3390/biology12081084.

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Various phenotypic traits relate to the size of a living system in regular but often disproportionate (allometric) ways. These “biological scaling” relationships have been studied by biologists for over a century, but their causes remain hotly debated. Here, I focus on the patterns and possible causes of the body-mass scaling of the rates/durations of various biological processes and life-history events, i.e., the “pace of life”. Many biologists have regarded the rate of metabolism or energy use as the master driver of the “pace of life” and its scaling with body size. Although this “energy perspective” has provided valuable insight, here I argue that a “time perspective” may be equally or even more important. I evaluate various major ways that time may be relevant in biological scaling, including as (1) an independent “fourth dimension” in biological dimensional analyses, (2) a universal “biological clock” that synchronizes various biological rates/durations, (3) a scaling method that uses various biological time periods (allochrony) as scaling metrics, rather than various measures of physical size (allometry), as traditionally performed, (4) an ultimate body-size-related constraint on the rates/timing of biological processes/events that is set by the inevitability of death, and (5) a geological “deep time” approach for viewing the evolution of biological scaling patterns. Although previously proposed universal four-dimensional space-time and “biological clock” views of biological scaling are problematic, novel approaches using allochronic analyses and time perspectives based on size-related rates of individual mortality and species origination/extinction may provide new valuable insights.
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43

Stekel, Dov J., Yoav Git, and Francesco Falciani. "The Comparison of Gene Expression from Multiple cDNA Libraries." Genome Research 10, no. 12 (November 21, 2000): 2055–61. http://dx.doi.org/10.1101/gr.132500.

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We describe a method for comparing the abundance of gene transcripts in cDNA libraries. This method allows for the comparison of gene expression in any number of libraries, in a single statistical analysis, to identify differentially expressed genes. Such genes may be of potential biological or pharmaceutical relevance. The formula that we derive is essentially the entropy of a partitioning of genes among cDNA libraries. This work goes beyond previously published analyses, which can either compare only two libraries, or identify a single outlier in a group of libraries. This work also addresses the problem of false positives associated with repeating the test on many thousands of genes. A randomization procedure is described that provides a quantitative measure of the degree of belief in the results; the results are further verified by considering a theoretically derived large deviations rate for the test statistic. As an example, the analysis is applied to four prostate cancer libraries from the Cancer Genome Anatomy Project. The analysis identifies biologically relevant genes that are differentially expressed in the different tumor cell types.
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44

Vieira, Douglas B., Karen Thur, Saki Sultana, David Priestman, and Aarnoud C. van der Spoel. "Verification and refinement of cellular glycosphingolipid profiles using HPLC." Biochemistry and Cell Biology 93, no. 6 (December 2015): 581–86. http://dx.doi.org/10.1139/bcb-2015-0074.

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Glycosphingolipids (GSLs) are hybrid molecules consisting of the sphingolipid ceramide linked to a mono- or oligo-saccharide. In comparison to other membrane lipids, the family of GSLs stands out because of the extensive variation in the carbohydrate headgroup. GSLs are cell surface binding partners, in cis with growth factor receptors, and in trans with bacterial toxins and viruses, and are among the host-derived membrane components of viral particles, including those of HIV. In spite of their biological relevance, GSL profiles of commonly used cell lines have been analyzed to different degrees. Here, we directly compare the GSL complements from CHO-K1, COS-7, HeLa, HEK-293, HEPG2, Jurkat, and SH-SY5Y cells using an HPLC-based method requiring modest amounts of material. Compared to previous studies, the HPLC-based analyses provided more detailed information on the complexity of the cellular GSL complement, qualitatively as well as quantitatively. In particular for cells expressing multiple GSLs, we found higher numbers of GSL species, and different levels of abundance. Our study thus extends our knowledge of biologically relevant lipids in widely used cell lines.
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45

Abdillah, Ariq, Prasad M. Sonawane, Donghyeon Kim, Dooronbek Mametov, Shingo Shimodaira, Yunseon Park, and David G. Churchill. "Discussions of Fluorescence in Selenium Chemistry: Recently Reported Probes, Particles, and a Clearer Biological Knowledge." Molecules 26, no. 3 (January 28, 2021): 692. http://dx.doi.org/10.3390/molecules26030692.

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In this review from literature appearing over about the past 5 years, we focus on selected selenide reports and related chemistry; we aimed for a digestible, relevant, review intended to be usefully interconnected within the realm of fluorescence and selenium chemistry. Tellurium is mentioned where relevant. Topics include selenium in physics and surfaces, nanoscience, sensing and fluorescence, quantum dots and nanoparticles, Au and oxide nanoparticles quantum dot based, coatings and catalyst poisons, thin film, and aspects of solar energy conversion. Chemosensing is covered, whether small molecule or nanoparticle based, relating to metal ion analytes, H2S, as well as analyte sulfane (biothiols—including glutathione). We cover recent reports of probing and fluorescence when they deal with redox biology aspects. Selenium in therapeutics, medicinal chemistry and skeleton cores is covered. Selenium serves as a constituent for some small molecule sensors and probes. Typically, the selenium is part of the reactive, or active site of the probe; in other cases, it is featured as the analyte, either as a reduced or oxidized form of selenium. Free radicals and ROS are also mentioned; aggregation strategies are treated in some places. Also, the relationship between reduced selenium and oxidized selenium is developed.
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Giulivi, C., N. J. Traaseth, and K. J. A. Davies. "Tyrosine oxidation products: analysis and biological relevance." Amino Acids 25, no. 3-4 (July 29, 2003): 227–32. http://dx.doi.org/10.1007/s00726-003-0013-0.

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47

CHIU, IVEY, and L. H. SHU. "Biomimetic design through natural language analysis to facilitate cross-domain information retrieval." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 21, no. 1 (January 2007): 45–59. http://dx.doi.org/10.1017/s0890060407070138.

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Biomimetic, or biologically inspired, design uses analogous biological phenomena to develop solutions for engineering problems. Several instances of biomimetic design result from personal observations of biological phenomena. However, many engineers' knowledge of biology may be limited, thus reducing the potential of biologically inspired solutions. Our approach to biomimetic design takes advantage of the large amount of biological knowledge already available in books, journals, and so forth, by performing keyword searches on these existing natural-language sources. Because of the ambiguity and imprecision of natural language, challenges inherent to natural language processing were encountered. One challenge of retrieving relevant cross-domain information involves differences in domain vocabularies, or lexicons. A keyword meaningful to biologists may not occur to engineers. For an example problem that involved cleaning, that is, removing dirt, a biochemist suggested the keyword “defend.” Defend is not an obvious keyword to most engineers for this problem, nor are the words defend and “clean/remove” directly related within lexical references. However, previous work showed that biological phenomena retrieved by the keyword defend provided useful stimuli and produced successful concepts for the clean/remove problem. In this paper, we describe a method to systematically bridge the disparate biology and engineering domains using natural language analysis. For the clean/remove example, we were able to algorithmically generate several biologically meaningful keywords, including defend, that are not obviously related to the engineering problem. We developed a method to organize and rank the set of biologically meaningful keywords identified, and confirmed that we could achieve similar results for two other examples in encapsulation and microassembly. Although we specifically address cross-domain information retrieval from biology, the bridging process presented in this paper is not limited to biology, and can be used for any other domain given the availability of appropriate domain-specific knowledge sources and references.
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Muetze, Tanja, Ivan H. Goenawan, Heather L. Wiencko, Manuel Bernal-Llinares, Kenneth Bryan, and David J. Lynn. "Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks." F1000Research 5 (July 19, 2016): 1745. http://dx.doi.org/10.12688/f1000research.9118.1.

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Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene list of interest, integrate contextual information, such as gene expression data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest. Availability: CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store (http://apps.cytoscape.org/apps/chat).
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49

Ghosh, Debajyoti, Lili Ding, Umasundari Sivaprasad, Esmond Geh, Jocelyn Biagini Myers, Jonathan A. Bernstein, Gurjit K. Khurana Hershey, and Tesfaye B. Mersha. "Multiple Transcriptome Data Analysis Reveals Biologically Relevant Atopic Dermatitis Signature Genes and Pathways." PLOS ONE 10, no. 12 (December 30, 2015): e0144316. http://dx.doi.org/10.1371/journal.pone.0144316.

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50

Muetze, Tanja, Ivan H. Goenawan, Heather L. Wiencko, Manuel Bernal-Llinares, Kenneth Bryan, and David J. Lynn. "Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks." F1000Research 5 (August 30, 2016): 1745. http://dx.doi.org/10.12688/f1000research.9118.2.

Full text
Abstract:
Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest. Availability: CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store (http://apps.cytoscape.org/apps/chat).
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