Current Protocols - Wiley Online Library

Time 2020-09-15 19:03:11

Web Name: Current Protocols - Wiley Online Library

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The Current Protocols collection includes over 24,000 step-by-step techniques, procedures, and practical overviews that provide researchers with reliable, efficient methods to ensure reproducible results and pave the way for critical scientific discovery. With its emphasis on carefully curated, highly edited methods rich in detail, practical advice, and troubleshooting, Current Protocols enables researchers to advance their research with an efficiency of time and resources.MORE Stem Cell Research in GermanyThe Editors of Current Protocols in Stem Cell Biology are pleased to bring you this special protocol-based virtual issue. This collection highlights cutting-edge research from Germany published in CPSC, in the areas of pluripotent stem cell culture, differentiation, disease modeling, cell-based therapies and tissue engineering. Current Protocols in BioinformaticsCovers the most important tools and resources that have become an essential part of research in all areas of the life sciences. Current Protocols in Chemical Biology Involves the application of chemistry to the investigation of biology and drug design. Current Protocols in Cell BiologyThe essential laboratory bench-side reference for researchers involved in any aspect of cell biology. Current Protocols in CytometryDistills and organizes methods and techniques from the top cytometry labs and specialists worldwide. Current Protocols: Essential Laboratory TechniquesSuitable for novice and expert alike, this journal is the ultimate all-in-one fundamentals guide for life scientists. Current Protocols in Food Analytical ChemistryThis Current Protocols title is no longer updated. Current Protocols in Human GeneticsProvides a curated compilation of methods covering all aspects of human genetics. Current Protocols in ImmunologyA "best-practices" collection that provides comprehensive coverage of immunological methods. Current Protocols in Magnetic Resonance Imaging This Current Protocols title is no longer updated. Current Protocols in Molecular BiologyAn essential tool for anyone at the forefront of molecular biology research, this journal remains the benchmark by which all other protocol resources are judged. Current Protocols in Microbiology Presents clear methodologies for research in priority areas such as infectious diseases, biodefense, microbe-host interactions, and host defense. Current Protocols in Mouse BiologyCreated by leading scientists in this rapidly evolving field and continuously updated, this journal brings together resources in mouse biology and genetics. Current Protocols in NeuroscienceThe most comprehensive collection of validated methods and preclinical models for researchers investigating the nervous system. Current Protocols in Nucleic Acid ChemistryThe resource for designing and running successful research projects in the field of nucleic acid, nucleotide, and nucleoside research. Current Protocols in Plant BiologyProvides a curated compilation of current methods that cover all aspects of plant biology with the goal of advancing the progress of plant science research. Current Protocols in Pharmacology A key resource that documents the broad spectrum of integrative techniques used in drug discovery and in the study of disease pathophysiology. Current Protocols in Protein ScienceProvides the most comprehensive collection of methods for the study of all aspects of proteins, and includes both classic and state-of-the-art methods. Current Protocols in ToxicologyThe best updated methods resource for accurate, efficient assessment of toxicity in whole organisms, organs and tissues, cells, and biochemical pathways. Current Protocols in Stem Cell BiologyCovers the most important methods in the rapidly growing field of stem cell biology. ISSUE INFORMATIONfree accessIssue InformationCurrent Protocols in Protein ScienceFirst Published:  11 September 2020https://doi.org/10.1002/cpps.91 Abstract Cover: In Welch et al. (http://doi.org/10.1002/cpps.113), the image shows schematic presentation of the capture and release (CaRe) method. 1, crude extracts. 2, crude extracts mixed with a target capturing agent (TCA). 3, TCA captures target (lectin or glycoprotein) by binding and cross‐linking the target. 4, after centrifugation, the supernatant containing all the impurities is discarded. Only the target‐TCA complex remains in the test tube. 5, monovalent ligand (ML) is added to the complex. 6, ML dissolves the complex and releases the target. 7, the released target is separated from the TCA by filtration.AbstractPDFRequest permissionsISSUE INFORMATIONfree accessIssue InformationCurrent Protocols in Mouse BiologyFirst Published:  9 September 2020https://doi.org/10.1002/cpmo.72 Abstract Cover: In Yeung et al. (http://doi.org/10.1002/cpmo.83), the image shows overview of mass spectrometry‐based proteomics workflow for eye wash and corneal tissues. Murine models of infection are used to initiate P. aeruginosa infection of the ocular surface. Corneal tissue and eye wash samples from infected, counter‐lateral, and uninfected mice are collected. Protein extraction, digestion, and peptide purification is performed as described in Basic Protocols 3‐5, followed by liquid chromatography and tandem mass spectrometry, as well as examples of data processing tools for analysis and visualization.AbstractFull textPDFReferencesRequest permissionsISSUE INFORMATIONfree accessIssue InformationCurrent Protocols in Chemical BiologyFirst Published:  5 September 2020https://doi.org/10.1002/cpch.68 Abstract Cover: In Ganobis et al. (http://doi.org/10.1002/cpch.83), the image shows ethanol peak observed at 3.66 ppm within a spectrum acquired from a mouse pellet. (A) Poor matching of ethanol, with the subtraction line (green) nearly matching the spectrum line (black), and the sum line (red) not reaching the spectrum line. (B) Good matching of ethanol peak at 3.66 ppm, with the subtraction line nearly flattened and the sum line reaching, but not surpassing, the spectrum line.AbstractPDFRequest permissionsISSUE INFORMATIONfree accessIssue InformationCurrent Protocols in Cell BiologyFirst Published:  4 September 2020https://doi.org/10.1002/cpcb.92 Abstract Cover: In Duband et al. (http://doi.org/10.1002/cpcb.109), the image shows Phenotypic characterization of neural crest cell cultures after several days in culture with cell lineage markers. (A) Phase contrast overview of a 48‐hr neural tube explant, showing, on the left, the dense network of neurites (arrows) emerging out of the ventral side of the neural tube and, on the right, the presence of cells with distinct morphologies and shapes among the neural crest cell population. (B) Detailed views of the main cell types derived from the neural crest outgrowth after 3 or 5 days in culture: Panel 1, large, well spread myofibroblasts; Panel 2, neurons with long neurites sitting on top of neural crest cells; and Panel 3, little, aster‐shaped melanoblasts. Note that these cells are often assembled as separate colonies. (C) Immunofluorescence labeling of neural crest‐derived cell populations after 3 days in culture with antibodies to Sox‐10, HNK‐1, α‐SMA, βIII‐tubulin (Tuj‐1), and Mitf revealed by secondary antibodies conjugated to Alexa‐488 (green), Cy‐3 (red), and Cy‐5 (purple in C1‐C3 and yellow in C4). Nuclei are visualized with Hoechst staining (blue). Panel 1 shows a group of myofibroblasts characterized by a dense meshwork of α‐SMA in their cytoplasm. Most of them do not express Sox‐10 in their nuclei and HNK‐1 on their surface but a few cells corresponding possibly to myofibroblasts having not yet completed their differentiation process express all three markers together (arrows). Besides myofibroblasts, a few large cells with an astrocyte‐like shape and expressing both HNK1 and Sox‐10 represent early differentiating glial cells (arrowheads). Panel 2 shows neurons expressing βIII‐tubulin but no Sox‐10. Panel 3 shows a large group of melanoblasts expressing MITF in their nuclei but no HNK‐1. As for myofibroblasts, a few melanoblasts can be seen coexpressing Mitf and HNK‐1 (arrows), likely corresponding to early melanoblasts. Panel 4 shows persistent Sox‐10 positive, HNK‐1 positive undifferentiated neural crest cell progenitors in the outgrowth. Bars in A, B, and C = 100 µm.AbstractPDFRequest permissionsISSUE INFORMATIONfree accessIssue InformationCurrent Protocols in Human GeneticsFirst Published:  4 September 2020https://doi.org/10.1002/cphg.90 Abstract Cover: In Chu et al. (http://doi.org/10.1002/cphg.102), the image shows different types of TE insertions and TE genotypes. (A‐C) Three different types of TE insertions with light yellow boxes indicating the time frames for when each arises. The colored triangles point to the origin of chromosomes carrying insertions. (A) Germline TE insertions are inherited from parents, and thus are present in every cell of the body. (B) De novo TE insertions arise during gametogenesis of the parents or early embryogenesis of the child, and thus are not detected in blood samples of the parents. (C) Somatic insertions occur during development and aging and create genetic mosaicism in an individual. Depending on when and where insertions occur, they are detected in different tissues at different mosaic levels. (D) Every TE insertion in an individual genome has three genotypes: homozygous (1/1), heterozygous (0/1), or no insertion (0/0). A homozygous insertion produces TE‐junction‐spanning reads originating from two insertion alleles; a heterozygous insertion produces reads from both insertion and reference alleles. Chromosomes carrying a non‐reference TE insertion and sequence reads derived from the chromosomes are marked in red.AbstractPDFRequest permissionsISSUE INFORMATIONfree accessIssue InformationCurrent Protocols in ToxicologyFirst Published:  4 September 2020https://doi.org/10.1002/cptx.82 Abstract Cover: In Dikovskaya and Dinkova‐Kostova et al. (http://doi.org/10.1002/cptx.96), the image shows (A) Data processing pipeline for an individual FLIM measurement. A fluorescence lifetime data file acquired with SPCM software that contains fluorescence decay measurements is first processed in SPCImage to determine a value of fluorescence lifetime in each pixel, using a 1‐component exponential decay fitting. The data are exported from SPCImage as two files, “_photons.asc” containing photon numbers in pixel positions and “_t1.asc” containing fluorescence lifetime values in pixel positions. The “_photons.asc” file depicting cell morphology is imported to ImageJ/FIJI, and areas of interest, such as entire cell, cytoplasm, or nucleus, are outlined within this file. For each area of interest, a new text image file is generated in which all values outside selected areas are set to zero. These files and the “_t1.asc” file are further combined within the FLIM DAtaSet Tool (FLIMDAST) that assembles the data into a 3D array, and generates scatterplots of fluorescence lifetime versus photon number in corresponding non‐zero pixels of the cellular image, with optional color‐coding for different cellular areas. (B) Visualization and calculation of fluorescence lifetime changes in FLIMDAST. The data from the same repeatedly measured cell are first processed as in A, and the 3D arrays representing individual cellular measurements are assembled together and displayed as an overlay of fluorescence lifetime versus photon number scatterplots. The change in fluorescence lifetime is apparent as a vertical shift of the entire distribution. To quantify this shift, a local polynomial regression (LOESS) curve is fitted to each dataset (red and dark blue lines), and the average difference between reference and non‐reference curves is determined within the range of photon numbers common to both distributions after removing the brightest 0.5% and the dimmest 0.5% of the pixels from each dataset (gray shaded area), as illustrated in the “quantification of change compared to reference” panel. This produces a single value of change in the fluorescence lifetime from the reference measurement for each non‐reference measurement. (C) Analysis of the entire time‐course experiment within FLIMDAST. The FLIM data from multiple cells for multiple experimental conditions repeatedly collected throughout the time course are located and assembled within FLIMDAST, and each measurement is assigned a reference to which it will be compared. Several measurements of the same cell can share the same reference, as depicted in the “multiple data assembly” panel. The entire experiment is processed at once, to generate overlay scatterplots similar to that in B, as shown in the “multiple data visualisation” panel. The changes in fluorescence lifetimes are also quantified at once for all measurement‐reference pairs in the entire experiment, using the same algorithm as in B, and is provided as a table, as illustrated in the “multiple data quantification” panel.AbstractPDFRequest permissionsISSUE INFORMATIONfree accessIssue InformationCurrent Protocols in PharmacologyFirst Published:  3 September 2020https://doi.org/10.1002/cpph.63 Abstract Cover: In Horváth het al. (http://doi.org/10.1002/cpph.78), the image shows histological analysis. (A,B) Representative images of Vaseline‐ and Aldara‐treated dorsal mouse skin on Day 5. (C) Composite histological scores of mouse dorsal skin after different treatments. Data are mean ± SEM for n = 6/group. **p .01 for Aldara versus Vaseline based on Mann‐Whitney t‐test. Please check your email for instructions on resetting your password. If you do not receive an email within 10 minutes, your email address may not be registered, and you may need to create a new Wiley Online Library account. Can't sign in? Forgot your username? Enter your email address below and we will send you your username If the address matches an existing account you will receive an email with instructions to retrieve your username

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