scholarly journals Pathology of multifocal purple spots, a nonspecific lesion morphology of Caribbean sea fans Gorgonia spp.

2020 ◽  
Vol 141 ◽  
pp. 79-89
Author(s):  
MM Dennis ◽  
AAMJ Becker ◽  
MA Freeman
Keyword(s):  
Coral Disease ◽  
Caribbean Sea ◽  
Disease Diagnosis ◽  
Case Definition ◽  
Molecular Techniques ◽  
Coral Diseases ◽  
Gorgonia Ventalina ◽  
Lesion Pattern ◽  
Lesion Morphology

Disease is contributing to the decline of coral reefs globally, but the cause and pathogenesis of most coral diseases are poorly understood. Using Gorgonia ventalina and G. flabellum as a model for coral disease diagnosis, we histologically and microbiologically examined 45 biopsies of lesions resembling Gorgonia multifocal purple spots (MFPS) with the aim of forming a comprehensive case definition based on gross and microscopic morphologic descriptions and associated etiologies. Macroscopically, all lesions were small circular areas of purple pigmentation. Gross morphologies included pigmentation only (4/45, 9%), or pigmentation with branchlet expansion and fusion (19/45, 22%), sessile masses (17/45, 38%), or hard nodules (5/45, 9%). Histological morphologic diagnoses included amoebocyte encapsulation (9/45, 20%), coenenchymal amoebocytosis (6/45, 13%), melanin (17/45, 38%), and gorgonin deposition (13/45, 29%). Sixty-four percent of instances of fungi and 86% of labyrinthulomycetes were localized to grossly normal portions of the biopsy, whereas barnacles were only within lesions, and 87% of instances of algae and 82% of cyanobacteria were within lesioned area of the biopsy. Penicillium (n = 12) was the predominant genus of fungi isolated from biopsies. Barnacles were identified as Conopea sp. using molecular techniques. The pathology and etiology underlying MFPS lesions are diverse, consistent with a highly nonspecific lesion pattern rather than a specific disease. This study demonstrates the importance of microscopic examination of tissues for accurate classification of coral diseases and lesion patterns.

A Study on Multi Class Classification from Breast Cancer Images using Ensemble Network and Transfer Learning

2020 ◽  
Vol 14 ◽  
Author(s):  
Lahari Tipirneni ◽  
Rizwan Patan
Keyword(s):  
Breast Cancer ◽  
Neural Network ◽  
Convolutional Neural Network ◽  
Binary Classification ◽  
Disease Diagnosis ◽  
Feature Descriptors ◽  
Histopathological Images ◽  
Viable Approach ◽  
Multi Class Classification

Abstract:: Millions of deaths all over the world are caused by breast cancer every year. It has become the most common type of cancer in women. Early detection will help in better prognosis and increases the chance of survival. Automating the classification using Computer-Aided Diagnosis (CAD) systems can make the diagnosis less prone to errors. Multi class classification and Binary classification of breast cancer is a challenging problem. Convolutional neural network architectures extract specific feature descriptors from images, which cannot represent different types of breast cancer. This leads to false positives in classification, which is undesirable in disease diagnosis. The current paper presents an ensemble Convolutional neural network for multi class classification and Binary classification of breast cancer. The feature descriptors from each network are combined to produce the final classification. In this paper, histopathological images are taken from publicly available BreakHis dataset and classified between 8 classes. The proposed ensemble model can perform better when compared to the methods proposed in the literature. The results showed that the proposed model could be a viable approach for breast cancer classification.

scholarly journals Time-frequency time-space long short-term memory networks for image classification of histopathological tissue

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tuan D. Pham
Keyword(s):  
Image Analysis ◽  
Short Term Memory ◽  
Disease Diagnosis ◽  
Short Term ◽  
Term Memory ◽  
Time Frequency ◽  
Time Space ◽  
Histopathological Images ◽  
Long Short Term Memory

AbstractImage analysis in histopathology provides insights into the microscopic examination of tissue for disease diagnosis, prognosis, and biomarker discovery. Particularly for cancer research, precise classification of histopathological images is the ultimate objective of the image analysis. Here, the time-frequency time-space long short-term memory network (TF-TS LSTM) developed for classification of time series is applied for classifying histopathological images. The deep learning is empowered by the use of sequential time-frequency and time-space features extracted from the images. Furthermore, unlike conventional classification practice, a strategy for class modeling is designed to leverage the learning power of the TF-TS LSTM. Tests on several datasets of histopathological images of haematoxylin-and-eosin and immunohistochemistry stains demonstrate the strong capability of the artificial intelligence (AI)-based approach for producing very accurate classification results. The proposed approach has the potential to be an AI tool for robust classification of histopathological images.

scholarly journals IMPORTANCE OF CLASSICAL MORPHOLOGY IN THE DIAGNOSIS OF MYELODYSPLASTIC SYNDROME

2015 ◽  
Vol 7 ◽  
pp. e2015035 ◽  
Author(s):  
Rosangela Invernizzi ◽  
Federica Quaglia ◽  
Matteo Giovanni Della Porta
Keyword(s):  
Molecular Techniques ◽  
Classification Systems ◽  
World Health ◽  
Hematopoietic Stem ◽  
Morphological Alterations ◽  
Diagnosis And Classification ◽  
The Moment ◽  
Health Organization ◽  
Selection Of

Myelodysplastic syndromes (MDS) are hematopoietic stem cell disorders characterized by dysplastic, ineffective, clonal and neoplastic hematopoiesis. MDS represent a complex hematological problem: differences in disease presentation, progression and outcome  have necessitated the use of classification systems to improve diagnosis, prognostication and treatment selection. However, since a single biological or genetic reliable diagnostic marker has not yet been discovered for MDS, quantitative and qualitative dysplastic morphological alterations of bone marrow precursors and of peripheral blood cells are still fundamental for diagnostic classification. In this paper World Health Organization (WHO) classification refinements and current minimal diagnostic criteria proposed by expert panels are highlighted and related problematic issues are discussed. The recommendations should facilitate diagnostic and prognostic evaluations in MDS and selection of patients for new effective targeted therapies. Although in the future morphology should be supplemented with new molecular techniques, the morphological approach, at least for the moment, is still the cornerstone for the diagnosis and classification of these disorders.

scholarly journals Characterization of Five New Earthworm Mitogenomes (Oligochaeta: Lumbricidae): Mitochondrial Phylogeny of Lumbricidae

Diversity ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 580
Author(s):  
Hongyi Liu ◽  
Yufeng Zhang ◽  
Wei Xu ◽  
Yu Fang ◽  
Honghua Ruan
Keyword(s):  
Phylogenetic Trees ◽  
Mitochondrial Gene ◽  
Morphological Characteristics ◽  
Molecular Techniques ◽  
Phylogenetic Studies ◽  
Octolasion Tyrtaeum ◽  
Eisenia Nordenskioldi ◽  
Novel Strategy

Identification based on conventional morphological characteristics is typically difficult and time-consuming. The development of molecular techniques provides a novel strategy that relies on specific mitochondrial gene fragments to conduct authentication. For this study, five newly sequenced partial mitogenomes of earthworms (Bimastos parvus, Dendrobaena octaedra, Eisenia andrei, Eisenia nordenskioldi, and Octolasion tyrtaeum) with lengths ranging from 14,977 to 15,715 were presented. Each mitogenome possessed a putative control region that resided between tRNA-Arg and tRNA-His. All of the PCGs were under negative selection according to the value of Ka/Ks. The phylogenetic trees supported the classification of Eisenia and Lumbricus; however, the trees based on cox1 did not. Through various comparisons, it was determined that cox1 fragments might be more suitable for molecular identification. These results lay the foundation for further phylogenetic studies on Lumbricidae.

scholarly journals Rapid Identification, Differentiation, and Proposed New Taxonomic Classification of Bifidobacterium lactis

2002 ◽  
Vol 68 (12) ◽  
pp. 6429-6434 ◽  
Author(s):  
Marco Ventura ◽  
Ralf Zink
Keyword(s):  
Pcr Primers ◽  
Rapid Identification ◽  
Molecular Techniques ◽  
Rrna Gene ◽  
Specific Detection ◽  
Bifidobacterium Lactis ◽  
Bifidobacterium Animalis ◽  
Subspecies Level ◽  
Internally Transcribed Spacer

ABSTRACT Identification of Bifidobacterium lactis and Bifidobacterium animalis is problematic because of phenotypic and genetic homogeneities and has raised the question of whether they belong to one unique taxon. Analysis of the 16S-23S internally transcribed spacer region of B. lactis DSM10140T, B. animalis ATCC 25527T, and six potential B. lactis strains suggested two distinct clusters. Two specific 16S-23S spacer rRNA gene-targeted primers have been developed for specific detection of B. animalis. All of the molecular techniques used (B. lactis or B. animalis PCR primers, enterobacterial repetitive intergenic consensus PCR) demonstrated that B. lactis and B. animalis form two main groups and suggest a revision of the strains assigned to B. animalis. We propose that B. lactis should be separated from B. animalis at the subspecies level.

scholarly journals Experimental antibiotic treatment identifies potential pathogens of white band disease in the endangered Caribbean coral Acropora cervicornis

2014 ◽  
Vol 281 (1788) ◽  
pp. 20140094 ◽  
Author(s):  
M. J. Sweet ◽  
A. Croquer ◽  
J. C. Bythell
Keyword(s):  
Coral Disease ◽  
Causal Agent ◽  
Acropora Palmata ◽  
Acropora Cervicornis ◽  
Coral Diseases ◽  
White Band ◽  
Disease Causation ◽  
Community Shifts ◽  
White Band Disease ◽  
Experimental Treatments

Coral diseases have been increasingly reported over the past few decades and are a major contributor to coral decline worldwide. The Caribbean, in particular, has been noted as a hotspot for coral disease, and the aptly named white syndromes have caused the decline of the dominant reef building corals throughout their range. White band disease (WBD) has been implicated in the dramatic loss of Acropora cervicornis and Acropora palmata since the 1970s, resulting in both species being listed as critically endangered on the International Union for Conservation of Nature Red list. The causal agent of WBD remains unknown, although recent studies based on challenge experiments with filtrate from infected hosts concluded that the disease is probably caused by bacteria. Here, we report an experiment using four different antibiotic treatments, targeting different members of the disease-associated microbial community. Two antibiotics, ampicillin and paromomycin, arrested the disease completely, and by comparing with community shifts brought about by treatments that did not arrest the disease, we have identified the likely candidate causal agent or agents of WBD. Our interpretation of the experimental treatments is that one or a combination of up to three specific bacterial types, detected consistently in diseased corals but not detectable in healthy corals, are likely causal agents of WBD. In addition, a histophagous ciliate ( Philaster lucinda ) identical to that found consistently in association with white syndrome in Indo-Pacific acroporas was also consistently detected in all WBD samples and absent in healthy coral. Treatment with metronidazole reduced it to below detection limits, but did not arrest the disease. However, the microscopic disease signs changed, suggesting a secondary role in disease causation for this ciliate. In future studies to identify a causal agent of WBD via tests of Henle–Koch's postulates, it will be vital to experimentally control for populations of the other potential pathogens identified in this study.

Molecular techniques used in plant disease diagnosis

2021 ◽  
pp. 405-421
Author(s):  
Swapnil Sapre ◽  
Iti Gontia-Mishra ◽  
Vishwa Vijay Thakur ◽  
Sumana Sikdar ◽  
Sharad Tiwari
Keyword(s):  
Plant Disease ◽  
Disease Diagnosis ◽  
Molecular Techniques ◽  
Plant Disease Diagnosis

scholarly journals Development and application of affordable SNP typing approaches to genotype Mycobacterium tuberculosis complex strains in low and high burden countries

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Irving Cancino-Muñoz ◽  
Ana Gil-Brusola ◽  
Manuela Torres-Puente ◽  
Carla Mariner-Llicer ◽  
John Dogba ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
Low Income ◽  
Sanger Sequencing ◽  
High Resolution Melting ◽  
Mycobacterium Tuberculosis Complex ◽  
Molecular Techniques ◽  
Low Income Countries ◽  
Tuberculosis Complex ◽  
Typing Methods

Abstract The Mycobacterium tuberculosis complex (MTBC) comprises the species that causes tuberculosis (TB) which affects 10 million people every year. A robust classification of species, lineages, and sub-lineages is important to explore associations with drug resistance, epidemiological patterns or clinical outcomes. We present a rapid and easy-to-follow methodology to classify clinical TB samples into the main MTBC clades. Approaches are based on the identification of lineage and sub-lineage diagnostic SNP using a real-time PCR high resolution melting assay and classic Sanger sequencing from low-concentrated, low quality DNA. Thus, suitable for implementation in middle and low-income countries. Once we validated our molecular procedures, we characterized a total of 491 biological samples from human and cattle hosts, representing countries with different TB burden. Overall, we managed to genotype ~95% of all samples despite coming from unpurified and low-concentrated DNA. Our approach also allowed us to detect zoonotic cases in eight human samples from Nigeria. To conclude, the molecular techniques we have developed, are accurate, discriminative and reproducible. Furthermore, it costs less than other classic typing methods, resulting in an affordable alternative method in TB laboratories.

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