10 research outputs found

    Recombinant Modified Vaccinia Virus Ankara Expressing Glycoprotein E2 of Chikungunya Virus Protects AG129 Mice against Lethal Challenge

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    Chikungunya virus (CHIKV) infection is characterized by rash, acute high fever, chills, headache, nausea, photophobia, vomiting, and severe polyarthralgia. There is evidence that arthralgia can persist for years and result in long-term discomfort. Neurologic disease with fatal outcome has been documented, although at low incidences. The CHIKV RNA genome encodes five structural proteins (C, E1, E2, E3 and 6K). The E1 spike protein drives the fusion process within the cytoplasm, while the E2 protein is believed to interact with cellular receptors and therefore most probably constitutes the target of neutralizing antibodies. We have constructed recombinant Modified Vaccinia Ankara (MVA) expressing E3E2, 6KE1, or the entire CHIKV envelope polyprotein cassette E3E26KE1. MVA is an appropriate platform because of its demonstrated clinical safety and its suitability for expression of various heterologous proteins. After completing the immunization scheme, animals were challenged with CHIV-S27. Immunization of AG129 mice with MVAs expressing E2 or E3E26KE1 elicited neutralizing antibodies in all animals and provided 100% protection against lethal disease. In contrast, 75% of the animals immunized with 6KE1 were protected against lethal infection. In conclusion, MVA expressing the glycoprotein E2 of CHIKV represents as an immunogenic and effective candidate vaccine against CHIKV infections

    Recombinant Modified Vaccinia Virus Ankara Expressing Glycoprotein E2 of Chikungunya Virus Protects AG129 Mice against Lethal Challenge

    Get PDF
    Chikungunya virus (CHIKV) infection is characterized by rash, acute high fever, chills, headache, nausea, photophobia, vomiting, and severe polyarthralgia. There is evidence that arthralgia can persist for years and result in long-term discomfort. Neurologic disease with fatal outcome has been documented, although at low incidences. The CHIKV RNA genome encodes five structural proteins (C, E1, E2, E3 and 6K). The E1 spike protein drives the fusion process within the cytoplasm, while the E2 protein is believed to interact with cellular receptors and therefore most probably constitutes the target of neutralizing antibodies. We have constructed recombinant Modified Vaccinia Ankara (MVA) expressing E3E2, 6KE1, or the entire CHIKV envelope polyprotein cassette E3E26KE1. MVA is an appropriate platform because of its demonstrated clinical safety and its suitability for expression of various heterologous proteins. After completing the immunization scheme, animals were challenged with CHIV-S27. Immunization of AG129 mice with MVAs expressing E2 or E3E26KE1 elicited neutralizing antibodies in all animals and provided 100% protection against lethal disease. In contrast, 75% of the animals immunized with 6KE1 were protected against lethal infection. In conclusion, MVA expressing the glycoprotein E2 of CHIKV represents as an immunogenic and effective candidate vaccine against CHIKV infections

    Detection of antigen expression.

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    <p>BHK-21 cells were infected with the respective candidate MVA vaccines and 24 hours later cells were fixed in methanol/acetone (1∶1) and stained for specific expression of CHIKV E1 (upper panel), E2 (middle panel) or MVA antigens (lower panel). The respective antigens were detected using rabbit polyclonal serum specific against E1, E2, and MVA as indicated. The staining confirmed the specific expression of the respective antigens and their purity. *Images were contrast enhanced in Adobe Photoshop.</p

    Histopathology of several tissues staining positive for CHIKV antigen.

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    <p>Panels A–E show representative staining of the liver, spleen, and brain of CHIKV infected AG129 mice. Hematoxylin and eosin-stained sections of the liver from all groups showed no abnormalities (A; 40× objective). Endothelial and Kupffer cells stained positive with anti-CHIKV capsid antibody (B, 40× objective). Massive depletion of lymphocytes was observed in the spleen of animals that died after challenge with CHIKV (C; HE staining, 40× objective). Antigen was mainly located in endothelial cells in the spleen (D). Epithelia cells of the choroid plexus (E) in the brain were scarcely stained and no antigen was found in the neuropil of the brain. Examples of positively stained cells are indicated by block arrows.</p

    Survival of mice after vaccination and challenge infection with CHIKV.

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    <p>(<b>A</b>). Mice (n = 8) were immunized intra-muscularly with MVA-6KE1, MVA-E3E2, MVA-E3E26KE1 or MVA-wt. Subsequently, the mice were challenged intra-peritoneally with 1000 TCID<sub>50</sub> CHIKV-S27. The survival rates of the mice after challenge are depicted as Kaplan-Meier curves. Differences between the curves were determined by the log-rank test. (<b>B, C, D</b>). Vial RNA copies were determined in spleen (B), liver (C) and brain (D) samples of animals that succumbed to the infection and survivors (day 14 post challenge). (<b>E</b>) Neutralizing antibody titers were determined on day 0, 21, 63, 70, and 77. Animals were immunized on day 0 and 21 and challenged on day 63. A clear booster response is seen after challenge, where a higher response was measured in MVA-6KE1 immunized group. The results are expressed as TCID<sub>50</sub> equivalents per gram of tissue; *indicates a statistically significant result (<i>P</i><0.05) and ** indicates highly significant results (<i>P</i><0.001) as determined by the <i>Student's t test</i>.</p

    Artificial intelligence outperforms pulmonologists in the interpretation of pulmonary function tests

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    The interpretation of pulmonary function tests (PFTs) to diagnose respiratory diseases is built on expert opinion that relies on the recognition of patterns and the clinical context for detection of specific diseases. In this study, we aimed to explore the accuracy and interrater variability of pulmonologists when interpreting PFTs compared with artificial intelligence (AI)-based software that was developed and validated in more than 1500 historical patient cases.120 pulmonologists from 16 European hospitals evaluated 50 cases with PFT and clinical information, resulting in 6000 independent interpretations. The AI software examined the same data. American Thoracic Society/European Respiratory Society guidelines were used as the gold standard for PFT pattern interpretation. The gold standard for diagnosis was derived from clinical history, PFT and all additional tests.The pattern recognition of PFTs by pulmonologists (senior 73%, junior 27%) matched the guidelines in 74.4±5.9% of the cases (range 56-88%). The interrater variability of κ=0.67 pointed to a common agreement. Pulmonologists made correct diagnoses in 44.6±8.7% of the cases (range 24-62%) with a large interrater variability (κ=0.35). The AI-based software perfectly matched the PFT pattern interpretations (100%) and assigned a correct diagnosis in 82% of all cases (p<0.0001 for both measures).The interpretation of PFTs by pulmonologists leads to marked variations and errors. AI-based software provides more accurate interpretations and may serve as a powerful decision support tool to improve clinical practice.status: publishe
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