Insights About Brain Tumors Gained Through Immunohistochemistry and in Situ Hybridization of Nuclear and Phenotypic Markers

1997 ◽  
Vol 3 (S2) ◽  
pp. 13-14
Author(s):  
P.E. McKeever
Keyword(s):  
Brain Tumors ◽  
Malignant Gliomas ◽  
Growth Potential ◽  
Primary Antibody ◽  
Specific Marker ◽  
Nuclear Markers ◽  
Cellular Markers ◽  
Abc Method

Immunohistochemistry (IHC) has provided major insights about the classification of brain tumors by identifying cellular markers of phenotype, and about tumor growth potential with nuclear markers of proliferation. Newer in situ hybridization shows promise in tumor classification and prognostication.Fig. 1 shows the sensitive and reliable avidin-biotin conjugate (ABC) method of localizing glial fibrillary acidic protein (GFAP). GFAP is the most specific marker of gliomas, tumors of brain cells, available today. The ABC method can be used to find any antigen for which a primary antibody is available. A molecular bridge then links this primary antibody bound to tissue with a label that can be seen, a substrate of the horseradish peroxidase (HRP) enzyme like diaminobenzidine (DAB) that produces a brown, insoluble reaction product at the site of the antigen. IHC for GFAP has revealed that brain tumors previously thought to be sarcomas are actually malignant gliomas (Fig. 2).

scholarly journals Insights About Brain Tumors Gained Through Immunohistochemistry and in Situ Hybridization of Nuclear and Phenotypic Markers

1998 ◽  
Vol 46 (5) ◽  
pp. 585-594 ◽  
Author(s):  
Paul E. McKeever
Keyword(s):  
In Situ Hybridization ◽  
Brain Tumors ◽  
Tumor Growth ◽  
Growth Potential ◽  
Nuclear Antigen ◽  
Pituitary Hormone ◽  
Ki 67 ◽  
Proliferation Markers ◽  
Cellular Markers

Immunohistochemistry (IHC) has provided major insights about the classification of brain tumors by identifying cellular markers of phenotype and about tumor growth potential with nuclear markers of proliferation. In situ hybridization (ISH) research shows promise for diagnostic applications in tumor classification. The avidin-biotin conjugate IHC procedure is highlighted for diagnostic use on routinely processed clinical specimens. The immunophenotypes of brain tumors are tabulated in reference to their common IHC markers. Tumors that have been correctly classified by their IHC phenotypes include the giant-cell glioblastoma, primary brain lymphoma, and central neurocytoma. Phenotypes that may be more definitively detected by ISH, such as pituitary hormone, immunoglobulin light chain, and collagen messages are described. IHC of nuclear proliferation markers correlates with grade of malignancy, predicts tumor growth potential, and is prognostic for patient survival. The incorporation of bromodeoxyuridine, the expression of proliferating cell nuclear antigen, and the expression of Ki-67 antigen detected by MIB-1 antibody are compared in regard to their cell cycle activity and labeling index determinations. Fluorescence in situ hybridization (FISH) of brain tumor interphase nuclei and chromosomes is described. Abnormal FISH signals of specific chromosomes are associated with different types of brain tumors, with different grades of malignancy, and with mesenchymal drift of glioma cells in culture.

Audit of histomorphology and immunohistochemistry of the brain tumors: Revisited in context to the WHO 2016 molecular classification

2017 ◽  
Vol 2 (1) ◽  
pp. 15
Author(s):  
Tanushri Mukherjee ◽  
Rajat Dutta ◽  
Joydeep Ghosh
Keyword(s):  
Social Sciences ◽  
Statistical Analysis ◽  
Brain Tumors ◽  
Molecular Classification ◽  
Histopathological Diagnosis ◽  
Treatment Change ◽  
Tumor Patients ◽  
The Brain

<p><span class="Bold">Background:</span><span> The WHO 2016 molecular classification corroborating with the histology has given more significant diagnostic objectivity to the diagnosis of brain tumors and it is more reliable for instituting therapy as the heterogeneity and observer subjectivity are bypassed with the addition of isocitrate dehydrogenase, ATRX, and 1p19q, and other molecular markers. </span><span class="Bold">Aim:</span><span> Our aim is to review the histopathology of diagnosed brain tumors and correlate with immunohistochemical (IHC) findings to note for any disparity to reform the diagnosis in order to benefit the patient and report to the clinician if any treatment change is to be considered. </span><span class="Bold">Materials and Methods:</span><span> This article is based on studies of screening and diagnostic test. A total of 150 brain tumors were retrospectively analyzed. Age, gender, and the tumor histological type and grade were systematically recorded. We compared our histopathological diagnosis before the introduction of the WHO 2016 molecular classification of central nervous system tumors and later after the relevant IHC and fluorescence </span><span class="Italic">in situ</span><span> hybridization studies. </span><span class="Bold">Statistical Analysis:</span><span> The statistical analysis was done by using Statistical Package for Social Sciences version recent for Windows. </span><span class="Bold">Results:</span><span> Out of the total 150 brain tumor patients, 65 were males and 45 were females. About 37 were glial and the rest were in other categories. </span><span class="Bold">Conclusions:</span><span> </span><span lang="en-US">The molecular diagnosis that substantiated with the histomorphology is more objective and beneficial in the treatment of the patients.</span></p>

scholarly journals Transfer learning networks with skip connections for classification of brain tumors

2021 ◽  
Author(s):  
Saleh Alaraimi ◽  
Kenneth E. Okedu ◽  
Hugo Tianfield ◽  
Richard Holden ◽  
Omair Uthmani
Keyword(s):  
Brain Tumors ◽  
Transfer Learning ◽  
Learning Networks

Strategies of In Situ Generated Magnesium Catalysis in Asymmetric Reactions

Synlett ◽  
2021 ◽  
Author(s):  
Dongxu Yang ◽  
Linqing Wang
Keyword(s):  
Asymmetric Synthesis ◽  
Alkaline Earth ◽  
Earth Metal ◽  
Asymmetric Reactions ◽  
Chiral Ligands ◽  
Alkaline Earth Metal ◽  
Enantioselective Reactions ◽  
Earth's Crust

AbstractMagnesium (Mg) is a cheap, non-toxic, and recyclable alkaline earth metal that constitutes about 2% weight in the Earth’s crust. The use of magnesium catalysts to forge chiral moieties in molecules is highly attractive. Based on our work in recent years, we describe the current progress in the development of in situ generated magnesium catalysts and their application in asymmetric synthesis. In this perspective, a critically concise classification of in situ generated magnesium catalytic modes, with relevant examples, is presented, and representative mechanisms of each category are discussed. Building on the established diverse strategies, one can foresee that more innovative and structurally creative magnesium catalysts that are generated in situ will be developed to overcome more formidable challenges of catalytic enantioselective reactions.1 Introduction2 Magnesium Catalysts Generated in Situ from Chiral Ligands Containing Dual Reactive Hydrogens3 Magnesium Catalysts Generated in Situ from Monoanionic Chiral Ligands4 Bimetallic and Polymetallic Magnesium Catalysts Assembled in Situ5 Summary and Outlook

scholarly journals Underwater Holographic Sensor for Plankton Studies In Situ Including Accompanying Measurements

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4863
Author(s):  
Victor Dyomin ◽  
Alexandra Davydova ◽  
Igor Polovtsev ◽  
Alexey Olshukov ◽  
Nikolay Kirillov ◽  
...  
Keyword(s):  
World Ocean ◽  
Field Tests ◽  
Field Measurements ◽  
Measuring Systems ◽  
Water Turbidity ◽  
Background Data ◽  
Average Size ◽  
Size Dispersion

The paper presents an underwater holographic sensor to study marine particles—a miniDHC digital holographic camera, which may be used as part of a hydrobiological probe for accompanying (background) measurements. The results of field measurements of plankton are given and interpreted, their verification is performed. Errors of measurements and classification of plankton particles are estimated. MiniDHC allows measurement of the following set of background data, which is confirmed by field tests: plankton concentration, average size and size dispersion of individuals, particle size distribution, including on major taxa, as well as water turbidity and suspension statistics. Version of constructing measuring systems based on modern carriers of operational oceanography for the purpose of ecological diagnostics of the world ocean using autochthonous plankton are discussed. The results of field measurements of plankton using miniDHC as part of a hydrobiological probe are presented and interpreted, and their verification is carried out. The results of comparing the data on the concentration of individual taxa obtained using miniDHC with the data obtained by the traditional method using plankton catching with a net showed a difference of no more than 23%. The article also contains recommendations for expanding the potential of miniDHC, its purpose indicators, and improving metrological characteristics.

scholarly journals Differential Deep Convolutional Neural Network Model for Brain Tumor Classification

2021 ◽  
Vol 11 (3) ◽  
pp. 352
Author(s):  
Isselmou Abd El Kader ◽  
Guizhi Xu ◽  
Zhang Shuai ◽  
Sani Saminu ◽  
Imran Javaid ◽  
...  
Keyword(s):  
Neural Network ◽  
Magnetic Resonance Imaging ◽  
Brain Tumor ◽  
Magnetic Resonance ◽  
Brain Tumors ◽  
Medical Image ◽  
Resonance Imaging ◽  
Feature Maps ◽  
Deep Cnn

The classification of brain tumors is a difficult task in the field of medical image analysis. Improving algorithms and machine learning technology helps radiologists to easily diagnose the tumor without surgical intervention. In recent years, deep learning techniques have made excellent progress in the field of medical image processing and analysis. However, there are many difficulties in classifying brain tumors using magnetic resonance imaging; first, the difficulty of brain structure and the intertwining of tissues in it; and secondly, the difficulty of classifying brain tumors due to the high density nature of the brain. We propose a differential deep convolutional neural network model (differential deep-CNN) to classify different types of brain tumor, including abnormal and normal magnetic resonance (MR) images. Using differential operators in the differential deep-CNN architecture, we derived the additional differential feature maps in the original CNN feature maps. The derivation process led to an improvement in the performance of the proposed approach in accordance with the results of the evaluation parameters used. The advantage of the differential deep-CNN model is an analysis of a pixel directional pattern of images using contrast calculations and its high ability to classify a large database of images with high accuracy and without technical problems. Therefore, the proposed approach gives an excellent overall performance. To test and train the performance of this model, we used a dataset consisting of 25,000 brain magnetic resonance imaging (MRI) images, which includes abnormal and normal images. The experimental results showed that the proposed model achieved an accuracy of 99.25%. This study demonstrates that the proposed differential deep-CNN model can be used to facilitate the automatic classification of brain tumors.

Standoff femtosecond filament-induced breakdown spectroscopy for classification of geological materials

2020 ◽  
Vol 35 (12) ◽  
pp. 3007-3020
Author(s):  
S. Abdul Kalam ◽  
S. V. Balaji Manasa Rao ◽  
M. Jayananda ◽  
S. Venugopal Rao
Keyword(s):  
Geological Materials ◽  
Breakdown Spectroscopy ◽  
Remote Locations

Femtosecond (fs) filaments delivering substantial peak intensities at remote locations are exploited in classification of geological materials together with in situ /standoff investigations.

scholarly journals α-Fetoprotein mRNA in situ hybridisation is a highly specific marker of hepatocellular carcinoma: a multi-centre study

2021 ◽  
Author(s):  
Shi-Xun Lu ◽  
Yu-Hua Huang ◽  
Li-Li Liu ◽  
Chris Zhiyi Zhang ◽  
Xia Yang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
In Situ Hybridisation ◽  
Diagnostic Value ◽  
Detection Sensitivity ◽  
Specific Marker ◽  
Specific Method ◽  
Multi Centre Study ◽  
Arginase 1 ◽  
Afp Mrna

Abstract Background Pathologic diagnosis of hepatocellular carcinoma (HCC) can be challenging in differentiating from benign and non-hepatocytic malignancy lesions. The aim of this study was to investigate the potential utility of α-fetoprotein (AFP) mRNA RNAscope, a sensitive and specific method, in the diagnosis of HCC. Methods Three independent retrospective cohorts containing 2216 patients with HCC, benign liver lesions, and non-hepatocytic tumours were examined. AFP was detected using ELISA, IHC (Immunohistochemistry), and RNAscope. Glypican3 (GPC3), hepatocyte paraffin-1 (HepPar-1), and arginase-1 (Arg-1) proteins were detected using IHC. Results AFP RNAscope improved the HCC detection sensitivity by 24.7–32.7% compared with IHC. In two surgical cohorts, a panel of AFP RNAscope and GPC3 provided the best diagnostic value in differentiating HCC from benign hepatocytic lesions (AUC = 0.905 and 0.811), and a panel including AFP RNAscope, GPC3, HepPar-1, and Arg-1 yielded the best AUC (0.971 and 0.977) when distinguishing HCC from non-hepatocytic malignancies. The results from the liver biopsy cohort were similar, and additional application of AFP RNAscope improved the sensitivity by 18% when distinguishing HCC from benign hepatocytic lesions. Conclusions AFP mRNA detected by RNAscope is highly specific for hepatocytic malignancy and may serve as a novel diagnostic biomarker for HCC.

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