scholarly journals Semi-automated analysis of dot blots using ImageJ/Fiji

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 1385
Author(s):  
Anna H. Klemm
Keyword(s):  
Automated Analysis ◽  
Automatic Registration ◽  
Spot Intensity ◽  
Dot Blot ◽  
Spot Pattern ◽  
Specific Antibodies ◽  
User Input ◽  
Fully Automatic ◽  
Iterative Registration ◽  
Target Analyte

Commercially available dot blots provide a set of specific antibodies spotted on membranes in a given pattern. If the target analyte is present in the solution that the membrane is incubated with, the detection reaction will result in a chemiluminescence signal which is recorded by film or scanner. In order to know which analytes were detected, the analysis consists of measuring the intensity of the recorded signal on each spot. Manually measuring the entire array (typically ~200 spots) is unreliable and tedious. Fully automatic registration of the blot membrane to the template pattern often fails since there might be only very few positive spots on the membrane. This article presents an ImageJ/Fiji macro that requires minimal user input to perform a robust iterative registration of an adjustable template mask representing the spot pattern to the recorded blot. Once the template mask is matched to the dot blot, the spot intensity of each dot is measured and reported in a results table.

scholarly journals The Reactivity and Allergenic Potential of Hazelnut Peptides

2013 ◽  
Vol 70 (1) ◽  
pp. 25
Author(s):  
Lavinia Florina Calinoiu ◽  
Dan Cristian Vodnar ◽  
Carmen Socaciu
Keyword(s):  
Proteolytic Enzymes ◽  
Peptide Fragments ◽  
Dot Blot ◽  
Specific Antibodies ◽  
Allergenic Potential ◽  
Sds Page ◽  
Allergenic Proteins ◽  
Life Threatening ◽  
Specific Proteins ◽  
Sensitive Method

The aim of this paper was to focus on proteins present in some food products, like hazelnuts and to investigate their allergenic potential. Several techniques were used to characterize these extracted proteins, with respect to their composition, degradability by digestive proteolytic enzymes and their reactivity with specific antibodies. It was important to analyse which proteins were present in the hazelnuts, to see if there were proteins present to trigger an allergic reaction and if the digestion enzymes trypsin and pepsin influence the presence of the (allergic) protein compounds. Allergies to tree nuts and seeds can cause life-threatening and sometimes fatal reactions. To examine the properties of Hazelnut protein it was important to solubilize it by extraction. After extraction, it was investigated how hazelnut protein can be modified by proteases and what the effect was on the immune reaction. The Bradford method is a fast and sensitive method to determine the concentration of soluble protein. When the Bradford reagent (Coomassie Brilliant Blue) binds to the protein, the colour changes from red to purple and the absorption maximum changes from 495 to 595 nm. The value obtained as the final concentration of proteins was 7.3495. SDS-PAGE is a method to separate mixtures of proteins by electrophoresis. Protein molecules are negatively charged by binding of SDS molecules; subsequently they are separated in an electric field. Their differences in size (molecular weight) leads to separation. In this case the method is used to follow proteolytic degradation of hazelnut proteins (allergens) by intestinal proteases (trypsin, pepsin). A different, more specific and sensitive method is immunoblotting (Western Blot) in which the SDS-PAGE separated proteins are transferred from the gel to a membrane and specific antibodies are used in a series of reactions to visualize specific allergens on this membrane. The remarked spots represented a positive identification of allergenic proteins. This means that peptide fragments of various size, produced during the digestion of a protein can still be immunological active. As it was shown there was still reactivity between proteins and specific antibodies. The Dot Blot is a simple immunoblotting technique used to detected specific proteins in a mixture of different proteins and/or other molecules. No separation technique prior to the actual immuno-detection is necessary. Also, Dot Blot confirmed the presence of allergenic proteins made visible through the light spots on the membrane.

scholarly journals Synthesis and Immunogenicity Assessment of Elastin-Like Polypeptide-M2e Construct as an Influenza Antigen

Nano LIFE ◽  
2014 ◽  
Vol 04 (02) ◽  
pp. 1450004 ◽  
Author(s):  
Rohan S. Ingrole ◽  
Wenqian Tao ◽  
Jatindra N. Tripathy ◽  
Harvinder S. Gill
Keyword(s):  
Phase Transition ◽  
Influenza A ◽  
Transmembrane Protein ◽  
Immune Serum ◽  
Mouse Serum ◽  
Phase Transition Behavior ◽  
Dot Blot ◽  
Specific Antibodies ◽  
Protein Polymer ◽  
Transition Behavior

The 23 amino acid-long extracellular domain of the influenza virus transmembrane protein M2 (M2e) has remained highly conserved since the 1918 pandemic, and is thus considered a good candidate for development of a universal influenza A vaccine. However, M2e is poorly immunogenic. In this study we assessed the potential of increasing immunogenicity of M2e by constructing a nanoscale-designed protein polymer containing the M2e sequence and an elastin-like polypeptide (ELP) nanodomain consisting of alanine and tyrosine guest residues (ELP(A2YA2)24). The ELP nanodomain was included to increase antigen size, and to exploit the inherent thermal inverse phase transition behavior of ELPs to purify the protein polymer. The ELP(A2YA2)24 + M2e nanodomained molecule was recombinantly synthesized. Characterization of its inverse phase transition behavior demonstrated that attachment of M2e to ELP(A2YA2)24 increased its transition temperature compared to ELP(A2YA2)24. Using a dot blot test we determined that M2e conjugated to ELP is recognizable by M2e-specific antibodies, suggesting that the conjugation process does not adversely affect the immunogenic property of M2e. Further, upon vaccinating mice with ELP(A2YA2)24 + M2e it was found that indeed the nanodomained protein enhanced M2e-specific antibodies in mouse serum compared to free M2e peptide and ELP(A2YA2)24. The immune serum could also recognize M2 expressed on influenza virions. Overall, this data suggests the potential of using molecules containing M2e-ELP nanodomains to develop a universal influenza vaccine.

Generating Spectrum Images from Different Types — Visible, Thermal, and Infrared Based on Autoencoder Architecture (GVTI-AE)

2021 ◽  
pp. 2250005
Author(s):  
Samer Kais Jameel ◽  
Jafar Majidpour
Keyword(s):  
Near Infrared ◽  
Visible Spectrum ◽  
Image Database ◽  
Post Processing ◽  
Face Database ◽  
User Input ◽  
Different Types ◽  
Fully Automatic ◽  
Realistic Images ◽  
Hand Image

Recently, numerous challenging problems have existed for transforming different image types (thermal infrared (TIR), visible spectrum, and near-infrared (NIR)). Other types of cameras may lack the ability and features of certain types of frequently-used cameras that produce different types of images. Based on camera features, different applications might emerge from observing a scenario under specific conditions (darkness, fog, night, day, and artificial light). We need to jump from one field to another to understand the scenario better. This paper proposes a fully automatic model (GVTI-AE) to manipulate the transformation into different types of vibrant, realistic images using the AutoEncoder method, which requires neither pre-nor post-processing or any user input. The experiments carried out using the GVTI-AE model showed that the perceptually realistic results produced in the widely available datasets (Tecnocampus Hand Image Database, Carl dataset, and IRIS Thermal/Visible Face Database).

scholarly journals Vessel segmentation for automatic registration of untracked laparoscopic ultrasound to CT of the liver

2021 ◽  
Author(s):  
Nina Montaña-Brown ◽  
João Ramalhinho ◽  
Moustafa Allam ◽  
Brian Davidson ◽  
Yipeng Hu ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Deep Learning ◽  
Liver Resection ◽  
Image Guidance ◽  
Laparoscopic Ultrasound ◽  
Multiple Models ◽  
Automatic Registration ◽  
Registration Method ◽  
Fully Automatic ◽  
Tracking Device

Abstract Purpose: Registration of Laparoscopic Ultrasound (LUS) to a pre-operative scan such as Computed Tomography (CT) using blood vessel information has been proposed as a method to enable image-guidance for laparoscopic liver resection. Currently, there are solutions for this problem that can potentially enable clinical translation by bypassing the need for a manual initialisation and tracking information. However, no reliable framework for the segmentation of vessels in 2D untracked LUS images has been presented. Methods: We propose the use of 2D UNet for the segmentation of liver vessels in 2D LUS images. We integrate these results in a previously developed registration method, and show the feasibility of a fully automatic initialisation to the LUS to CT registration problem without a tracking device. Results: We validate our segmentation using LUS data from 6 patients. We test multiple models by placing patient datasets into different combinations of training, testing and hold-out, and obtain mean Dice scores ranging from 0.543 to 0.706. Using these segmentations, we obtain registration accuracies between 6.3 and 16.6 mm in 50% of cases. Conclusions: We demonstrate the first instance of deep learning (DL) for the segmentation of liver vessels in LUS. Our results show the feasibility of UNet in detecting multiple vessel instances in 2D LUS images, and potentially automating a LUS to CT registration pipeline.

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