scholarly journals High multiplex, digital spatial profiling of proteins and RNA in fixed tissue using genomic detection methods

2019 ◽  
Author(s):  
Christopher R. Merritt ◽  
Giang T. Ong ◽  
Sarah Church ◽  
Kristi Barker ◽  
Gary Geiss ◽  
...  
Keyword(s):  
Immune Cell ◽  
Tissue Sample ◽  
Detection Methods ◽  
Fixed Tissue ◽  
Affinity Reagents ◽  
Spatial Profiling ◽  
Rna Probes ◽  
Oligonucleotide Detection ◽  
Modern Genomic ◽  
Non Destructive

ABSTRACTWe have developed Digital Spatial Profiling (DSP), a non-destructive method for high-plex spatial profiling of proteins and RNA, using oligonucleotide detection technologies with unlimited multiplexing capability. The key breakthroughs underlying DSP are threefold: (1) multiplexed readout of proteins/RNA using oligo-tags; (2) oligo-tags attached to affinity reagents (antibodies/RNA probes) through a photocleavable (PC) linker; (3) photocleaving light projected onto the tissue sample to release PC-oligos in any spatial pattern. Here we show precise analyte reproducibility, validation, and cellular resolution using DSP. We also demonstrate biological proof-of-concept using lymphoid, colorectal tumor, and autoimmune tissue as models to profile immune cell populations, stroma, and cancer cells to identify factors specific for the diseased microenvironment. DSP utilizes the unlimited multiplexing capability of modern genomic approaches, while simultaneously providing spatial context of protein and RNA to examine biological questions based on analyte location and distribution.

scholarly journals Accurate and Robust Alignment of Differently Stained Histologic Images Based on Greedy Diffeomorphic Registration

2021 ◽  
Vol 11 (4) ◽  
pp. 1892
Author(s):  
Ludovic Venet ◽  
Sarthak Pati ◽  
Michael D. Feldman ◽  
MacLean P. Nasrallah ◽  
Paul Yushkevich ◽  
...  
Keyword(s):  
Immune Cell ◽  
Tissue Sample ◽  
Disease Process ◽  
Spatial Arrangement ◽  
General Purpose ◽  
Growth Patterns ◽  
Histological Image ◽  
Target Registration Error ◽  
Diffeomorphic Registration ◽  
3D Information

Histopathologic assessment routinely provides rich microscopic information about tissue structure and disease process. However, the sections used are very thin, and essentially capture only 2D representations of a certain tissue sample. Accurate and robust alignment of sequentially cut 2D slices should contribute to more comprehensive assessment accounting for surrounding 3D information. Towards this end, we here propose a two-step diffeomorphic registration approach that aligns differently stained histology slides to each other, starting with an initial affine step followed by estimating a deformation field. It was quantitatively evaluated on ample (n = 481) and diverse data from the automatic non-rigid histological image registration challenge, where it was awarded the second rank. The obtained results demonstrate the ability of the proposed approach to robustly (average robustness = 0.9898) and accurately (average relative target registration error = 0.2%) align differently stained histology slices of various anatomical sites while maintaining reasonable computational efficiency (<1 min per registration). The method was developed by adapting a general-purpose registration algorithm designed for 3D radiographic scans and achieved consistently accurate results for aligning high-resolution 2D histologic images. Accurate alignment of histologic images can contribute to a better understanding of the spatial arrangement and growth patterns of cells, vessels, matrix, nerves, and immune cell interactions.

A rapid and non-destructive method for detecting the water-holding capacity of pork using composite film

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Xing Li ◽  
Xiaodan Wang ◽  
Dengyong Liu ◽  
Yanli Dong ◽  
Feng Hu
Keyword(s):  
Service Life ◽  
Composite Film ◽  
Water Holding Capacity ◽  
Detection Methods ◽  
Important Indicator ◽  
Discriminant Model ◽  
Fisher Discriminant ◽  
Water Holding ◽  
Non Destructive ◽  
Pork Samples

Abstract Water-holding capacity (WHC) is an important indicator of pork quality, but the existing detection methods of WHC are either expensive or time-consuming. In this study, a new method of pork WHC detection was developed by a composite film. The preparation method, mechanical properties and service life of the composite film were studied. The result showed that composite film was 0.46 ± 0.06 mm thick and had a service life of 21 days, tensile strength of 7.72 ± 0.11 MPa and the elongation at break of 28.54 ± 0.15%. Thirty groups of pork samples were randomly selected to build the model and another twenty groups were used to verify the model accuracy. Results showed that the accuracy of composite film coupled with Fisher discriminant model to detect the WHC of pork is 90%. This study demonstrates the high value of composite film as a detection tool to classify WHC of pork.

scholarly journals A Review of Non-Destructive Damage Detection Methods for Steel Wire Ropes

2019 ◽  
Vol 9 (13) ◽  
pp. 2771 ◽  
Author(s):  
Ping Zhou ◽  
Gongbo Zhou ◽  
Zhencai Zhu ◽  
Zhenzhi He ◽  
Xin Ding ◽  
...  
Keyword(s):  
Damage Detection ◽  
Detection Method ◽  
Steel Wire ◽  
Guided Wave ◽  
Detection Methods ◽  
Wire Ropes ◽  
Intelligent Sensors ◽  
Detection Technology ◽  
Damage States ◽  
Non Destructive

As an important load-bearing component, steel wire ropes (WRs) are widely used in complex systems such as mine hoists, cranes, ropeways, elevators, oil rigs, and cable-stayed bridges. Non-destructive damage detection for WRs is an important way to assess damage states to guarantee WR’s reliability and safety. With intelligent sensors, signal processing, and pattern recognition technology developing rapidly, this field has made great progress. However, there is a lack of a systematic review on technologies or methods introduced and employed, as well as research summaries and prospects in recent years. In order to bridge this gap, and to promote the development of non-destructive detection technology for WRs, we present an overview of non-destructive damage detection research of WRs and discuss the core issues on this topic in this paper. First, the WRs’ damage type is introduced, and its causes are explained. Then, we summarize several main non-destructive detection methods for WRs, including electromagnetic detection method, optical detection method, ultrasonic guided wave detection method, and acoustic emission detection method. Finally, a prospect is put forward. Based on the review of papers, we provide insight about the future of the non-destructive damage detection methods for steel WRs to a certain extent.

scholarly journals Non-Destructive Technologies for Detecting Insect Infestation in Fruits and Vegetables under Postharvest Conditions: A Critical Review

Foods ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 927 ◽  
Author(s):  
Akinbode A. Adedeji ◽  
Nader Ekramirad ◽  
Ahmed Rady ◽  
Ali Hamidisepehr ◽  
Kevin D. Donohue ◽  
...  
Keyword(s):  
Food Quality ◽  
Fruits And Vegetables ◽  
New Technologies ◽  
Fresh Produce ◽  
Detection Methods ◽  
Future Research ◽  
Insect Infestation ◽  
Noninvasive Methods ◽  
Synthetic Chemicals ◽  
Non Destructive

In the last two decades, food scientists have attempted to develop new technologies that can improve the detection of insect infestation in fruits and vegetables under postharvest conditions using a multitude of non-destructive technologies. While consumers’ expectations for higher nutritive and sensorial value of fresh produce has increased over time, they have also become more critical on using insecticides or synthetic chemicals to preserve food quality from insects’ attacks or enhance the quality attributes of minimally processed fresh produce. In addition, the increasingly stringent quarantine measures by regulatory agencies for commercial import–export of fresh produce needs more reliable technologies for quickly detecting insect infestation in fruits and vegetables before their commercialization. For these reasons, the food industry investigates alternative and non-destructive means to improve food quality. Several studies have been conducted on the development of rapid, accurate, and reliable insect infestation monitoring systems to replace invasive and subjective methods that are often inefficient. There are still major limitations to the effective in-field, as well as postharvest on-line, monitoring applications. This review presents a general overview of current non-destructive techniques for the detection of insect damage in fruits and vegetables and discusses basic principles and applications. The paper also elaborates on the specific post-harvest fruit infestation detection methods, which include principles, protocols, specific application examples, merits, and limitations. The methods reviewed include those based on spectroscopy, imaging, acoustic sensing, and chemical interactions, with greater emphasis on the noninvasive methods. This review also discusses the current research gaps as well as the future research directions for non-destructive methods’ application in the detection and classification of insect infestation in fruits and vegetables.

A new method for gene expression analysis of pure lymphocytes recovered from heterogeneous fixed mouse tissue.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e23089-e23089
Author(s):  
Jennifer Chow ◽  
Ana Paula Galvão Da Silva ◽  
Gianni Medoro ◽  
Nicolò Manaresi ◽  
Paul David Lira ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Tissue Sample ◽  
Critical Role ◽  
Rna Extraction ◽  
Response To Treatment ◽  
Mouse Tissue ◽  
Fixed Tissue ◽  
Mouse Splenocytes

e23089 Background: Tumor infiltrating lymphocytes (TILs) are biomarkers that play a critical role in cancer diseases, including differential diagnosis, determination of prognosis, prediction of response to treatment, and evaluation of disease progression. Gene expression analysis in TILs derived from fresh tissue may not accurately depict the gene profile of the tissue microenvironment as it can change aggressively during lymphocyte isolation and RNA extraction. In addition, tissue sample size can limit the isolation of TILs with current technologies. In this study, we demonstrate the use of the DEPArray™platform to isolate pure populations of lymphocytes from a fixed mouse tissue for RNA analysi. Methods: Mouse splenocytes were activated in vitro with anti-CD3 and -CD28 for 72hs. Cells were harvested, fixed with 2% paraformaldehyde (PFA) for 20 min at RT, and stained for either CD4 or CD8 expression. Gene expression analysis of CD45, ADORA2A, GLS and GAPDH was performed in CD4+ and CD8+ DEPArray™sorted cells using the TaqMan PreAmp Cells-to-Ct kit. Results: The table below summarizes the Ct values for CD45, ADORA2A, GLS and GAPDH expression in 300 fixed unsorted control and DEPArray™sorted lymphocytes. Conclusions: We have demonstrated the feasibility of gene expression analysis on pure populations of CD4+ and CD8+ cells isolated from a fixed tissue using the DEPArray™ platform. The advantage of this approach is the DEPArray’s ability to identify and isolate subpopulations of cells from complex heterogeneous samples and/or specimens that are limited by size or content. This methodology will be applied for isolation of TILs in syngeneic and xenograft models of cancers for downstream RNA applications. [Table: see text]

Non-destructive detection methods for discontinuities of interconnection structures

2016 ◽  
Vol 33 (1) ◽  
pp. 23-35 ◽  
Author(s):  
Tomas Blecha
Keyword(s):  
Transmission Lines ◽  
Printed Circuit Boards ◽  
Characteristic Impedance ◽  
Diagnostic Methods ◽  
Detection Methods ◽  
Circuit Boards ◽  
Content Type ◽  
Multiple Line ◽  
Detection And Localization ◽  
Non Destructive

Purpose – The purpose of this paper is to demonstrate the non-destructive methods for detection and localization of interconnection structure discontinuities based on the signal analysis in the frequency and time domain. Design/methodology/approach – The paper deals with the discontinuity characterization of interconnection structures created on substrates used for electronics, and methods for their detection and localization, based on the frequency analysis of transmitted signals. Used analyses are based on the theoretical approach for the solution of discontinuity electrical parameters and are the base for diagnostic methods of discontinuity identification. Findings – The measurement results of reflection parameters, frequency spectrums of transmitted signals and characteristic impedance values are presented on test samples containing multiple line cracks and their width reduction. Practical implications – Obtained results can be used practically, not only for the detection of transmission lines discontinuities on printed circuit boards but also in other applications, such as the quality assessment of bonded joints. Originality/value – Developed methods allow the quick identification and localization of particular discontinuities without the destruction of tested devices.

scholarly journals Highly Multiplexed Digital Spatial Profiling of the Tumor Microenvironment of Head and Neck Squamous Cell Carcinoma Patients

2021 ◽  
Vol 10 ◽  
Author(s):  
Arutha Kulasinghe ◽  
Touraj Taheri ◽  
Ken O’Byrne ◽  
Brett G. M. Hughes ◽  
Liz Kenny ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Neck Squamous Cell Carcinoma ◽  
Protein Markers ◽  
Spatial Profiling

BackgroundImmune checkpoint inhibitors (ICI) have shown durable and long-term benefits in a subset of head and neck squamous cell carcinoma (HNSCC) patients. To identify patient-responders from non-responders, biomarkers are needed which are predictive of outcome to ICI therapy. Cues in the tumor microenvironment (TME) have been informative in understanding the tumor-immune contexture.MethodsIn this preliminary study, the NanoString GeoMx™ Digital Spatial Profiling (DSP) technology was used to determine the immune marker and compartment specific measurements in a cohort of HNSCC tumors from patients receiving ICI therapy.ResultsOur data revealed that markers involved with immune cell infiltration (CD8 T-cells) were not predictive of outcome to ICI therapy. Rather, a number of immune cell types and protein markers (CD4, CD68, CD45, CD44, CD66b) were found to correlate with progressive disease. Cross platform comparison with the Opal Vectra (Perkin Elmer) for a number of markers across similar regions of interest demonstrated concordance for pan-cytokeratin, CD8, and PD-L1.ConclusionThis study, to our knowledge, represents the first digital spatial analysis of HNSCC tumors. A larger cohort of HNSCC will be required to orthogonally validate the findings.

scholarly journals Benefit of Neural Network for the Optimization of Defect Detection on Composite Material Using Ultrasonic Non Destructive Testing

2021 ◽  
Author(s):  
P. Trouvé-Peloux ◽  
B. Abeloos ◽  
A. Ben Fekih ◽  
C. Trottier ◽  
J.-M. Roche
Keyword(s):  
Defect Detection ◽  
Semantic Segmentation ◽  
Detection Methods ◽  
Learning Approaches ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Experimental Database ◽  
Out Of Plane ◽  
Non Destructive

Abstract This paper is dedicated to out-of-plane waviness defect detection within composite materials by ultrasonic testing. We present here an in-house experimental database of ultrasonic data built on composite pieces with/without elaborated defects. Using this dataset, we have developed several defect detection methods using the C-scan representation, where the defect is clearly observable. We compare here the defect detection performance of unsupervised, classical machine learning methods and deep learning approaches. In particular, we have investigated the use of semantic segmentation networks that provides a classification of the data at the “pixel level”, hence at each C-scan measure. This technique is used to classify if a defect is detected, and to produce a precise localization of the defect within the material. The results we obtained with the various detection methods are compared, and we discuss the drawbacks and advantages of each method.

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