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      A Combined Method Based on the FIPV N Monoclonal Antibody Immunofluorescence Assay and RT-nPCR Method for the Rapid Diagnosis of FIP-Suspected Ascites

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          Abstract

          Feline infectious peritonitis (FIP), which is caused by feline infectious peritonitis virus (FIPV), is a fatal and immunologically mediated infectious disease among cats. At present, due to the atypical clinical symptoms and clinicopathological changes, the clinical diagnosis of FIP is still difficult. The gold standard method for the differential diagnosis of FIP is immunohistochemistry (IHC) which is time-consuming and requires specialized personnel and equipment. Therefore, a rapid and accurate clinical diagnostic method for FIPV infection is still urgently needed. In this study, based on the etiological investigation of FIPV in parts of southern China, we attempted to explore a new rapid and highly sensitive method for clinical diagnosis. The results of the etiological investigation showed that the N gene of the FIPV BS8 strain had the highest homology with other strains. Based on this, a specific FIPV BS8 N protein monoclonal antibody was successfully prepared by expression of the recombinant proteins, immunization of mice, fusion and selection of hybridoma cell lines, and screening and purification of monoclonal antibodies. Furthermore, we carried out a time-saving combination method including indirect immunofluorescence assay (IFA) and nested reverse transcription polymerase chain reaction (RT-nPCR) to examine FIP-suspected clinical samples. These results were 100% consistent with IHC. The results revealed that the combined method could be a rapid and accurate application in the diagnosis of suspected FIPV infection within 24 hours. In conclusion, the combination of IFA and RT-nPCR was shown to be a fast and reliable method for clinical FIPV diagnosis. This study will provide insight into the exploitation of FIPV N antibodies for the clinical diagnosis of FIP-suspected ascites samples.

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          Most cited references45

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          Deep learning-enabled breast cancer hormonal receptor status determination from base-level H&E stains

          For newly diagnosed breast cancer, estrogen receptor status (ERS) is a key molecular marker used for prognosis and treatment decisions. During clinical management, ERS is determined by pathologists from immunohistochemistry (IHC) staining of biopsied tissue for the targeted receptor, which highlights the presence of cellular surface antigens. This is an expensive, time-consuming process which introduces discordance in results due to variability in IHC preparation and pathologist subjectivity. In contrast, hematoxylin and eosin (H&E) staining—which highlights cellular morphology—is quick, less expensive, and less variable in preparation. Here we show that machine learning can determine molecular marker status, as assessed by hormone receptors, directly from cellular morphology. We develop a multiple instance learning-based deep neural network that determines ERS from H&E-stained whole slide images (WSI). Our algorithm—trained strictly with WSI-level annotations—is accurate on a varied, multi-country dataset of 3,474 patients, achieving an area under the curve (AUC) of 0.92 for sensitivity and specificity. Our approach has the potential to augment clinicians’ capabilities in cancer prognosis and theragnosis by harnessing biological signals imperceptible to the human eye.
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            Feline coronavirus type II strains 79-1683 and 79-1146 originate from a double recombination between feline coronavirus type I and canine coronavirus.

            Recent evidence suggests that the type II feline coronavirus (FCoV) strains 79-1146 and 79-1683 have arisen from a homologous RNA recombination event between FCoV type I and canine coronavirus (CCV). In both cases, the template switch apparently took place between the S and M genes, giving rise to recombinant viruses which encode a CCV-like S protein and the M, N, 7a, and 7b proteins of FCoV type I (K. Motowaka, T. Hohdatsu, H. Hashimoto, and H. Koyama, Microbiol. Immunol. 40:425-433, 1996; H. Vennema, A. Poland, K. Floyd Hawkins, and N. C. Pedersen, Feline Pract. 23:40-44, 1995). In the present study, we have looked for additional FCoV-CCV recombination sites. Four regions in the pol gene were selected for comparative sequence analysis of the type II FCoV strains 79-1683 and 79-1146, the type I FCoV strains TN406 and UCD1, the CCV strain K378, and the TGEV strain Purdue. Our data show that the type II FCoVs have arisen from double recombination events: additional crossover sites were mapped in the ORF1ab frameshifting region of strain 79-1683 and in the 5' half of ORF1b of strain 79-1146.
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              Diagnosis of Feline Infectious Peritonitis: A Review of the Current Literature

              Feline infectious peritonitis (FIP) is a fatal disease that poses several challenges for veterinarians: clinical signs and laboratory changes are non-specific, and there are two pathotypes of the etiologic agent feline coronavirus (FCoV), sometimes referred to as feline enteric coronavirus (FECV) and feline infectious peritonitis virus (FIPV) that vary fundamentally in their virulence, but are indistinguishable by a number of diagnostic methods. This review focuses on all important steps every veterinary practitioner has to deal with and new diagnostic tests that can be considered when encountering a cat with suspected FIP with the aim to establish a definitive diagnosis. It gives an overview on all available direct and indirect diagnostic tests and their sensitivity and specificity reported in the literature in different sample material. By providing summarized data for sensitivity and specificity of each diagnostic test and each sample material, which can easily be accessed in tables, this review can help to facilitate the interpretation of different diagnostic tests and raise awareness of their advantages and limitations. Additionally, diagnostic trees depict recommended diagnostic steps that should be performed in cats suspected of having FIP based on their clinical signs or clinicopathologic abnormalities. These steps can easily be followed in clinical practice.
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                Author and article information

                Contributors
                Journal
                Transboundary and Emerging Diseases
                Transboundary and Emerging Diseases
                Hindawi Limited
                1865-1682
                1865-1674
                March 28 2023
                March 28 2023
                : 2023
                : 1-12
                Affiliations
                [1 ]College of Veterinary Medicine, South China Agricultural University, Guangzhou, China
                [2 ]Guangdong Provincial Key Laboratory of Prevention and Control for Severe Clinical Animal Diseases, Guangzhou, China
                [3 ]Guangdong Technological Engineering Research Center for Pet, Guangzhou, China
                [4 ]College of Veterinary Medicine, Inner Mongolia Agricultural University/Key Laboratory of Clinical Diagnosis and Treatment Technologyin Animal Disease, Ministry of Agriculture, Hohhot 010018, China
                [5 ]Laboklin Laboratory for Clinical Diagnostics, Guang Zhou 510700, China
                Article
                10.1155/2023/8429106
                dea85b0f-7509-4588-9fd0-a8a5cc594199
                © 2023

                https://creativecommons.org/licenses/by/4.0/

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