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Chikungunya Fever

Chikungunya Fever: A debilitating viral disease characterized by sudden onset of fever, severe joint pain, and rash.
Caused by the Chikungunya virus, transmitted by Aedes mosquitoes.
Symptoms typically appear 3-7 days after infection and can last weeks or months.
Chronic joint pain is a common complication.
Effective management strategies and research into new treatments are crucial to improve patient outcomes.

Most cited protocols related to «Chikungunya Fever»

1
Quantifying ZIKV Genome in Biological Samples
To discard co-infection of ZIKV with dengue and/or chikungunya viruses, we analyzed the urine, saliva samples and the viral strains isolated from Vero cell using he NAT- Dengue, Zika and Chikungunya discriminatory kit (Instituto de Biologia Molecular do Paraná and Fundação Oswaldo Cruz, Brazil). To measure genomic ZIKV load, viral RNA was reverse transcribed and amplified using the TaqMan Fast Virus 1-Step Master Mix (Applied Biosystems) in an Applied Biosystems StepOnePlus Instrument. For each reaction we used 400 nM forward primer (5’-CTTGGAGTGCTTGTGATT-3’, genome position 3451–3468), 600 nM reverse primer (5’-CTCCTCCAGTGTTCATTT-3’, genome position 3637–3620) and 250 nM probe (5’FAM- AGAAGAGAATGACCACAAAGATCA-3’TAMRA, genome position 3494–3517). The sequences of this primer set were kindly provided by Isabelle Lepark-Goffart (French National Reference Centre for Arboviruses, IRBA, Marseille, France). Samples were run in duplicate. The reverse transcription was performed at 50°C for 5 minutes. The qPCR conditions were 95°C for 20 seconds, followed by 40 amplification cycles of 95°C for 15 seconds and 60°C for 1 minute. Copy numbers of ZIKV genomic RNA were calculated by absolute quantitation using a standard curve for each run. To construct a standard curve, we cloned an amplicon comprising the genomic region 3085–4032 of the isolate Rio-U1 using pGEM-T Easy Vector (Promega) to serve as a template for in vitro transcription. The RNA transcript was made with mMessage mMachine High Yield Capped RNA Transcription Kit (Invitrogen) using T7 enzyme and purified using MEGAclear Kit (Ambion) according to manufacturer’s instructions. The purity of the transcript was verified using NanoDrop 8000 Spectrophotometer (Thermo Scientific), the integrity was analyzed using 2100 Bioanalyzer (Agilent) using the RNA 6000 Nano Kit (Agilent), and the concentration of the RNA was accessed using Qubit 2.0 Fluorometer (Invitrogen). The standard curve was generated by a ten-fold dilution (ranging from 10 to 109 copies/reaction) of the transcript. The limit of detection under standard assay conditions was approximately 40 viral RNA copies/mL.
Bonaldo M.C., Ribeiro I.P., Lima N.S., dos Santos A.A., Menezes L.S., da Cruz S.O., de Mello I.S., Furtado N.D., de Moura E.E., Damasceno L., da Silva K.A., de Castro M.G., Gerber A.L., de Almeida L.G., Lourenço-de-Oliveira R., Vasconcelos A.T, & Brasil P. (2016). Isolation of Infective Zika Virus from Urine and Saliva of Patients in Brazil. PLoS Neglected Tropical Diseases, 10(6), e0004816.
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Publication 2016
Arboviruses Biological Assay Chikungunya Fever Chikungunya virus Cloning Vectors Dengue Fever Enzymes Genome Neoplasm Metastasis Oligonucleotide Primers Promega prostaglandin M Reverse Transcription RNA, Viral RNA Caps Saliva Strains Technique, Dilution Transcription, Genetic Urine Vero Cells Virus Zika Virus Zika Virus Infection
2
Chikungunya Outbreak Survival Analysis
Data was collected in a spreadsheet using Microsoft Excel®. Frequencies, summary statistics and other descriptive analyses were calculated for the variables under study using the statistical software EpiInfo™, version 7.2.0.1. A p-value < 0.05 was considered statistically significant. Rates of incidence, epidemic curves and survival curves were calculated to analyze the temporal evolution of the outbreak of Chikungunya in the two neighbouring towns affected. Survival analysis used the Kaplan-Meier model [21 (link)], which is a non-parametric, analytical and graphic technique that estimates the probability of survival by the maximum likelihood method; the response variable is the time of survival or time-to-event, corresponding to the time elapsed since the initial moment until the occurrence of a certain event; when the event of interest is not observed it is defined as censoring.
In this study the epidemiological event was the presence of clinically suspected cases of Chikungunya and the survival (time-to-event) time was the time it took people to get sick from the appearance of the first case of Chikungunya in the two towns. The Kaplan-Meier estimator was applied using the Survival Analysis package in the statistical software R.
For the survival analysis an additional database was built in which each affected individual living in the houses was characterized according to his/her status for censoring, time of disease and town to which he/she belongs. Individuals who were not ill were considered to be censored data. The log-rank test was used to compare the curves of Chikungunya survival in the towns of Ovejas and Corozal; this test calculate the Chi-square for each time of each event in each group, adds the results and compare between them [18 (link)]. In addition, and through contingency tables assessed the possible association between socioeconomic factors and preventive measures that could explain the differences between the survival curves of the two towns.
Oviedo-Pastrana M., Méndez N., Mattar S., Arrieta G, & Gomezcaceres L. (2017). Epidemic outbreak of Chikungunya in two neighboring towns in the Colombian Caribbean: a survival analysis. Archives of Public Health, 75, 1.
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Publication 2017
Biological Evolution Chikungunya Fever Epidemics
3
Antiviral and Cytotoxicity Screening of Compounds

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Publication 2017
Alamar Blue Antiviral Agents Cell Culture Techniques Cells Chikungunya Fever Colorimetry Cytotoxin Dengue Fever Dengue Virus Dyes Fluorescence Fluorometry Junin virus Luminescence neuro-oncological ventral antigen 2, human Psychological Inhibition Technique, Dilution Vero Cells Virus Virus Diseases
4
Estimating Zika-Related Microcephaly Risk
We estimated the probability of a microcephaly case given a Zika infection during the first trimester of pregnancy, as the proportion of the Zika-related microcephaly births among all births to mothers infected with Zika during the first trimester of pregnancy [15 (link)]. Our web tool also has the flexibility to adjust the duration of risk during pregnancy, as reports emerge suggesting that the risk could extend beyond early pregnancy.
Birth counts are totaled for the outbreak in Northeast Brazil, where Zika was first confirmed to have reached Latin America in mid-April 2015 [1 , 16 (link)] and where cases have already begun to decline [17 ]. Given our assumption that only first-trimester Zika infections can cause microcephaly, we expect Zika-liked microcephaly to begin arising around October 15, 2015, six months after the first infection. Cumulative case data on suspected and confirmed microcephaly cases were obtained for Northeast Brazil until April 2, 2016, with the first report containing cumulative case counts from November 15, 2015 [17 ]. To forecast the microcephaly cases yet to arise, we applied a linear regression over the weekly reported cases for 2016 in Northeast Brazil [17 ].
Excess microcephaly cases, above what would be expected for Northeast Brazil during this time period, were assumed to be linked to Zika infection. This excess is calculated as the difference between the estimated total microcephaly cases during the outbreak in Northeast Brazil and the expected non-Zika related microcephaly births for the same duration and region. To estimate the total microcephaly births for the Northeast Brazil outbreak, we took into account the reporting sensitivity, i.e., the proportion of confirmed cases from among all investigated microcephaly cases in the region [17 ] and the expected total reported microcephaly births. The estimated total reported microcephaly births is then the sum of our forecast of newly reported microcephaly cases for the remaining outbreak in Northeast Brazil and the latest available reported microcephaly cases for Northeast Brazil (5,380 as of April 2, 2016).
The expected microcephaly cases attributable to causes other than Zika were based on prevalence estimates of microcephaly prior to the outbreak from Brazil (0.5 per 10,000 births) [18 (link)] and the highest reported prevalence from the US (12 per 10,000 births) [19 ] to account for possible underreporting before the outbreak. These prevalence values were multiplied by expected births during the Zika-related microcephaly outbreak in Northeast Brazil to estimate expected microcephaly from other causes. The expected births during the outbreak in Northeast Brazil were estimated from the fraction of the Brazilian population in Northeast Brazil (28%) [20 ], the Brazilian population [21 ], and the Brazilian birth rate (14.931 per 1000 population) [22 ].
Since the attack rate in Northeast Brazil is unknown, to estimate the births by mothers infected in their first trimester, we used attack rates ranging from 23.5% (reported for the latest outbreak in Puerto Rico of chikungunya [23 (link)], a related arbovirus transmitted by the same mosquito species) to 77% (upper bound for Zika outbreak in Yap Island, Micronesia in 2007 [24 (link)]). The 2013–2014 French Polynesia Zika outbreak had an attack rate between those two bounds (66% [95%CI: 62–70] [15 (link)]). The supplement provides a table of the parameters used and their sources, as well as a flow diagram of the equations underlying our calculations of the probability of microcephaly given a Zika infection during the first trimester of pregnancy (S1 Table and S1 Fig).
The probability of microcephaly given Zika infection, in the absence of interventions targeted towards pregnant women, is estimated by multiplying the probability of microcephaly given a Zika infection in the first trimester of pregnancy, the geographic-specific birth rate, and the risk period divided by 365 days.
Alfaro-Murillo J.A., Parpia A.S., Fitzpatrick M.C., Tamagnan J.A., Medlock J., Ndeffo-Mbah M.L., Fish D., Ávila-Agüero M.L., Marín R., Ko A.I, & Galvani A.P. (2016). A Cost-Effectiveness Tool for Informing Policies on Zika Virus Control. PLoS Neglected Tropical Diseases, 10(5), e0004743.
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Publication 2016
Arboviruses Chikungunya Fever Childbirth Culicidae Dietary Supplements Hypersensitivity Infection Microcephaly Mothers Pregnancy Pregnant Women Zika Virus
5
Preparing Datasets for Comparative Analysis
Datasets used in Figure 1 were either obtained directly from authors (VAST44 (link) and Cyclists43 (link) datasets) or downloaded from publications42 (link) (SISA dataset) and R packages (Zeller dataset from the MetagenomicData46 (link) and LIHC from the GSEABenchmarkeR47 (link)) with help from the authors. The SISA dataset contains data from 543 individuals hospitalized due to arboviral infection with dengue, chikungunya, or Zika virus from a surveillance study in Ecuador collected from 2013 to 2017. In the SISA dataset we excluded columns with high level of missing values (pregnancy, “WomPreg,” and complete blood count test, which was not performed for all donors and includes the columns “PLT_count,” “Lymphocytes,” “CBC_N%,” “WBC_calc,” and “CBC_HCT”). In addition, nine donors with missing values were removed. The final SISA dataset after removal of columns and rows with missing values is available as Table S2. The Cyclists dataset contains data from the immune responses of 120 elderly individuals with a high-level of physical activity, i.e., master cyclists, and 75 age-matched controls with a low level of physical activity (non-cyclists) analyzed using flow cytometry (Table S4). The VAST dataset contains data from 72 individuals enrolled in the clinical study to evaluate humoral responses in a typhoid vaccine efficacy trial in a controlled human infection model. Only day 0 (day of the challenge) log-transformed data were used and are available for download as Table S5. Individuals were vaccinated with either a purified Vi-PS vaccine (35 individuals) or the Vi-TT vaccine (37 individuals) 1 month prior to oral challenge with live Salmonella Typhi. Of 72 individuals, 26 developed an acute typhoid infection following challenge. The Zeller dataset contains information on the microbiome species abundance in healthy individuals and colorectal cancer patients (Table S8). The data were accessed through the MetagenomicData package. In total 184 individuals were included, of which 93 were healthy controls and 91 colorectal cancer patients. The LIHC dataset obtained from the GSEABenchmarkeR package contains RNA expression data from 374 LIHC cells and 50 adjacent normal cells (Table S9).
Tomic A., Tomic I., Waldron L., Geistlinger L., Kuhn M., Spreng R.L., Dahora L.C., Seaton K.E., Tomaras G., Hill J., Duggal N.A., Pollock R.D., Lazarus N.R., Harridge S.D., Lord J.M., Khatri P., Pollard A.J, & Davis M.M. (2021). SIMON: Open-Source Knowledge Discovery Platform. Patterns, 2(1), 100178.
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Publication 2021
Aged Arbovirus Infections Cells Chikungunya Fever Colorectal Carcinoma Dengue Fever Donors Flow Cytometry Hematologic Tests Homo sapiens Infection Lymphocyte Microbiome Patients Pregnancy Response, Immune Salmonella typhi Transcription, Genetic Typhoid Fever Vaccines Vaccines, Typhoid Zika Virus

Most recents protocols related to «Chikungunya Fever»

1
SARS-CoV-2, Chikungunya, and Other Viral Infections
MRC-5 cells (human lung fibroblasts, ATCC-CCL-171) were cultured essentially as described previously [30 (link)]. Vero E6 cells (African green monkey kidney epithelial cells), 293/ACE2 cells (originally described to be derived from human HEK293 cells [95 (link)], but most likely from nonhuman primate origin [14 (link)]) and BHK-21 cells (baby hamster kidney fibroblasts) were cultured essentially as described previously [21 (link)]. Vero cells (ATCC-CCL81) cells were cultured essentially as described previously [96 (link)]. All culture media contained 100 IU/ml penicillin and 100 ug/ml streptomycin unless otherwise specified.
CHIKV LS3 is a synthetic Chikungunya virus based on the consensus sequence of E1-226V isolates [21 (link)]. Infections with CHIKV LS3 and LS3-GFP were performed essentially as described previously [21 (link)]. The Chikungunya replicon was derived from CHIKV LS3 by replacing the structural genes with a puromycin resistance/foot-and-mouth disease virus 2A oligopeptide/green fluorescent protein (PAC-2A-GFP) reporter gene. The sequence of the 2A oligopeptide contains an amino acid motif that prevents formation of the peptide bond between glycine and the final proline of the sequence which allows expression of multiple proteins from a single ORF [97 (link),98 (link)].
Vero E6 cells were infected with the Sindbis virus (SINV) HR-strain [99 (link)], Semliki Forest virus (SFV) strain SFV4 [100 (link)] or VEEV vaccine strain TC-83 [101 (link)] at a multiplicity of infection (MOI) of 5 or 10. Vero E6 cells were infected with a GFP-expressing recombinant human adenovirus type 5 (HAdV-GFP/LUC; [102 (link)]) at an MOI of 5 and with a GFP-expressing recombinant coxsackie B3 virus (CVB3) (a kind gift from prof. dr. Frank van Kuppeveld, Utrecht University) at an MOI of 1. BHK-21 cells were infected with the equine arteritis virus (EAV) Bucyrus strain at MOI 5 at 39.5°C essentially as described previously [103 (link)].
Treffers E.E., Tas A., Scholte F.E., de Ru A.H., Snijder E.J., van Veelen P.A, & van Hemert M.J. (2023). The alphavirus nonstructural protein 2 NTPase induces a host translational shut-off through phosphorylation of eEF2 via cAMP-PKA-eEF2K signaling. PLOS Pathogens, 19(2), e1011179.
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Publication 2023
ACE2 protein, human Adenoviruses, Human Cells Cercopithecus aethiops Chikungunya Fever Chikungunya virus Consensus Sequence Coxsackievirus Infections Culture Media Epithelial Cells Equine Arteritis Virus Fibroblasts Foot-and-Mouth Disease Virus Genes Genes, Reporter Glycine Hamsters HEK293 Cells Homo sapiens Infant Infection Kidney Lung Oligopeptides Penicillins Peptide Biosynthesis Proline Proteins Puromycin Replicon Reproduction Semliki forest virus Sindbis Virus Strains Streptomycin Vaccines Vero Cells
2
Comprehensive Research Protocol Database
General information on the diseases (see Section 2.2.2) was provided to MSs to assist them in getting familiar with the more exotic diseases from the list and those they had only limited knowledge of yet. Therefore, ready‐to‐use fact‐sheets and technical cards were retrieved from the websites of different international organisations: Centers for Disease Control and Prevention (CDC), Center for Food Security and Public Health (CFSPH), European Association of Zoo and Wildlife Veterinarians (EAZWV), ECDC, EFSA, FAO, World Health Organization (WHO). For Eastern equine encephalitis and glanders, the American Association of Equine Practitioners (AAEP) was consulted. For Ebola virus disease and Hendra virus infection, more information was retrieved from the Australian Capital Territory8 and New South Wales9 government. Additional literature searches in PubMed and Web of Science were conducted for diseases for which no or only few fact‐sheets or technical cards were available: Chikungunya fever, Eastern equine encephalitis, erysipelothricosis, Helvetica spotted fever, Mediterranean spotted fever, murine typhus, Omsk haemorrhagic fever, Powassan virus infection, Scrub typhus, Shuni virus infection, Sindbis fever, St. Louis encephalitis, Thogoto virus infection, tick‐borne encephalitis, Usutu virus infection, Venezuelan equine encephalitis, Wesselsbron virus infection, Western equine encephalitis. Those literature searches aimed at retrieving recent review articles by using the name of the disease in the search string and filtering by article type. An additional literature search was performed for Flaviviruses in general. All references were collected, downloaded and made available to MSs with the note not to rely exclusively on the information provided by EFSA. Relevant information to answer the questions in Table 2 included in those references was highlighted to save time and facilitate MSs' work with the documents.
For the last question on ‘impact on biodiversity’, EFSA, through an external contractor, conducted a review of endangered wildlife species that may be affected by the 45 selected diseases (ENETWILD consortium, 2022b (link)). Those wildlife species were classified as near threatened, vulnerable, endangered and critically endangered, based on the International Union for Conservation of Nature (IUCN) Red List of Threatened Species.10 In addition, their endemicity status for both EU and Europe was indicated. The information presented included the exact taxonomic level of pathogen detection, whether animals living in the wild or in zoos were affected, and the clinical signs they displayed. To answer the respective question, MSs had to verify whether those wildlife species were present in their country or not.
In addition, MSs were requested to refer to their own country‐specific data and expert opinion (e.g. on disease impacts), whenever relevant, for assessing the different diseases according to pathogen‐related criteria.
Berezowski J., de Balogh K., Dórea F.C., Rüegg S., Broglia A., Gervelmeyer A, & Kohnle L. (2023). Prioritisation of zoonotic diseases for coordinated surveillance systems under the One Health approach for cross‐border pathogens that threaten the Union. EFSA Journal, 21(3), e07853.
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Publication 2023
Animals Boutonneuse Fever Chikungunya Fever Encephalitis Encephalomyelitis, Eastern Equine Encephalomyelitis, Western Equine Endangered Species Endemic Flea-Borne Typhus Equus caballus Europeans Fever Flavivirus Glanders Hemorrhagic Fever, Ebola Hemorrhagic Fever, Omsk Hendra Virus Infection pathogenesis Powassan virus Scrub Typhus Shuni orthobunyavirus Spotted Fever Group Rickettsiosis Strains Thogoto virus Threatened Species Tick-Borne Encephalitis Usutu virus Venezuelan Equine Encephalomyelitis Veterinarian Virus Diseases
3
Placental Analysis of Zika-Infected Pregnant Women
This study enrolled pregnant women with and without overweight/obesity, divided into groups of non-infected and Zika-infected, to access placental samples at the time of delivery.
In total, 39 non-infected pregnant women, based on the antenatal body mass index (BMI), were determined not to have obesity (BMI 18.5–24.9; n = 11) and to have overweight/obesity (BMI 25–39.9; n = 28). The women were selected from 34 public health units in Araraquara city, São Paulo, from a Cohort Study, coordinated by Prof Patricia Rondó, University of São Paulo. An informed consent form approved by the Ethics Committee, number: 59787216.2.0000.5421, was collected from the women. Samples of normal delivery or cesarean section, from women older than 18 years and with a gestational age above 37 weeks, were included. The exclusion criteria were positive serology for syphilis, HIV-1, hepatitis B, C, and toxoplasmosis, as well as clinical or obstetric complications associated with increased postoperative complications. Placentas and samples from preterm and post-term deliveries were also excluded.
In total, 30 Zika-infected women, enrolled in the Clinical Cohort Study of ZIKV pregnant women and their infants at a maternal and child hospital (Instituto Nacional de Saúde da Mulher, da Criança e do Adolescente Fernandes Figueira, Fiocruz) in Rio de Janeiro, Brazil, collected in the period of 2015–2016, (IRB/CAAE: 52675616.0.000.5269) were included in the study. Congenital infection by ZIKV was confirmed during pregnancy by the positive PCR of urine, blood, or placenta samples. We accessed placentas from the women without obesity (BMI 18.5–24.9; n = 14) and with overweight/obesity (BMI 25–39.9; n = 16). The samples from the mothers were tested and excluded for HIV, evidence of past Dengue virus, and Chikungunya virus (CHIKV) infection. This cohort included pregnant adult women >18 years of age, and the exclusion criteria included maternal HIV infection and pregnancies complicated by other congenital infections, known to cause infant neurologic damage (e.g., TORCH, CHIKV). Placentas and samples from preterm and post-term deliveries were also excluded. The placental samples were collected at the time of delivery from the umbilical cord insertion region. The clinical data of infants who had an adverse neurologic outcome at the time of birth, such as microcephaly (head-circumference z score of less than −2), were used in this study.
Branco A.C., De Oliveira E.A., Pereira N.Z., Alberca R.W., Duarte-Neto A.N., Da Silva L.F., Luiz F.G., Pereira N.V., Sotto M.N., Dejani N.N., Rondó P.H., Avvad-Portari E., De Vasconcelos Z.F., Duarte A.J., Azamor T, & Sato M.N. (2023). Obesity Induces an Impaired Placental Antiviral Immune Response in Pregnant Women Infected with Zika Virus. Viruses, 15(2), 320.
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Publication 2023
Adult Adverse Birth Outcomes BLOOD Cesarean Section Chikungunya Fever Chikungunya virus Child Dengue Virus Ethics Committees Gestational Age Head Hepatitis B HIV-1 HIV Infections Index, Body Mass Infant Infection Microcephaly Mothers Obesity Obstetric Delivery Placenta Postoperative Complications Pregnancy Pregnant Women Syphilis Serodiagnosis Systems, Nervous Toxoplasmosis Trauma, Nervous System Umbilical Cord Urine Woman Zika Virus Zika Virus Infection
4
Multiplex detection of parasitic and arboviral pathogens
For Leishmania detection in mammal samples and phlebotomine sand flies, PCR was performed with the primers LITSR and L5.8S, which specifically amplify a fragment of 350-bp of ITS gene [22 (link)]. The positive samples by ITS were typing for hsp70 gene, following the protocol and sequencing algorithm designed by Van der Auwera et al. (2013) [23 (link)] and modifications described by Hoyos et al. (2022) [24 (link)]. Assays for detection of Plasmodium were performed in Anopheles mosquitoes. A nested PCR using ribosomal primers that amplify a fragment of 205 pb for Plasmodium falciparum and 117 pb for Plasmodium vivax was performed, following the protocol of Snounou et al. (1993) [25 (link)].
Trypanosoma cruzi DNA (kinetoplastid and satellite) was detected [26 (link)] in triatomines and mammal samples. Amplified fragments of 330 bp were considered positive for kinetoplastid and of 166 bp for satellite DNA. For T. cruzi genotyping, the amplification of the mini-exon gene was performed using PCR protocols described by Leon et al. (2019) [26 (link)]. Amplified fragments of 350 bp were considered positive for TcI and of 300 bp for TcII. We used the SL-IR region to discriminate TcI Dom and TcI Sylvatic genotypes, following PCR protocols described by Leon et al. (2015) [27 (link)].
Detection of arbovirus (Zika, dengue, and chikungunya viral RNA) was performed in Ae. aegypti mosquitoes and organ tissue samples using ZDC Multiplex RT-PCR Assay (Ref. 12,003,818 Bio-Rad), according to manufacturer’s instructions, as described by Carrasquilla et al. (2021) [28 (link)]. Amplification curves were evaluated by each probe, and the threshold line was placed above the background signal. Amplification curves with CT values of ≥ 37 were considered negative.
Carrasquilla M.C., Ortiz M.I., Amórtegui-Hernández D., García-Restrepo S., León C., Méndez-Cardona S, & González C. (2023). Pathogens, reservoirs, and vectors involved in the transmission of vector-borne and zoonotic diseases in a Colombian region. Brazilian Journal of Microbiology, 54(2), 1145-1156.
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Publication 2023
Anopheles Arboviruses Biological Assay Chagas Disease Chikungunya Fever Culicidae Dengue Fever DNA, Satellite Gene Amplification Genes Genes, vif Genotype Heat-Shock Proteins 70 Leishmania Mammals Mini-Exon Multiplex Polymerase Chain Reaction Nested Polymerase Chain Reaction Oligonucleotide Primers Phlebotominae Plasmodium Plasmodium falciparum Plasmodium vivax Ribosomes RNA, Viral Tissues Trypanosoma cruzi Zika Virus
5
Chikungunya Virus Inactivation Protocol
CHIKV BR_2015/15010 was isolated from the serum of a patient with chikungunya disease from Northeast Brazil in 2015. The virus was amplified, titrated by foci-forming assay in C6/36 cells [28 (link)], and inactivated using β-propiolactone (0.025%, 72 h, 4 °C). The inactivated virus was concentrated by PEG 7%/NaCl 2.3% precipitation and purified using a sucrose cushion. A noninfected control (Mock) was prepared in the same manner from β-propiolactone inactivated C6/36 cell-culture supernatant.
Segato-Vendrameto C.Z., Zanluca C., Zucoloto A.Z., Zaninelli T.H., Bertozzi M.M., Saraiva-Santos T., Ferraz C.R., Staurengo-Ferrari L., Badaro-Garcia S., Manchope M.F., Dionisio A.M., Pinho-Ribeiro F.A., Borghi S.M., Mosimann A.L., Casagrande R., Bordignon J., Fattori V., dos Santos C.N, & Verri W.A. (2023). Chikungunya Virus and Its Envelope Protein E2 Induce Hyperalgesia in Mice: Inhibition by Anti-E2 Monoclonal Antibodies and by Targeting TRPV1. Cells, 12(4), 556.
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Publication 2023
Biological Assay Cell Culture Techniques Cells Chikungunya Fever Patients Propiolactone Serum Sodium Chloride Sucrose Virus

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More about "Chikungunya Fever"

Chikungunya is a debilitating viral disease characterized by sudden onset of fever, severe joint pain, and rash.
It is caused by the Chikungunya virus, which is transmitted by Aedes mosquitoes.
Symptoms typically appear 3-7 days after infection and can last for weeks or even months.
Chronic joint pain is a common complication of Chikungunya fever.
Effective management strategies and research into new treatments are crucial to improve patient outcomes.
The QIAamp Viral RNA Mini Kit and the RealStar Chikungunya RT-PCR Kit 2.0 are commonly used for detecting the Chikungunya virus.
Fetal bovine serum (FBS) and Vero cells are also often utilized in Chikungunya research.
The RealStar® Chikungunya RT-PCR Kit is another diagnostic tool that can be used to detect the presence of the virus.
Minimum Essential Medium (MEM) is a cell culture medium that may be used in Chikungunya studies.
The QIAmp Viral RNA Mini Kit and Diethyl pyrocarbonate (DEPC) water are also important components in the process of extracting and analyzing viral RNA.
Sodium citrate is a compound that can be used in the purification and stabilization of Chikungunya virus samples.
Optimizing research workflows and making data-driven decisions with tools like PubCompare.ai can help advance our understanding and management of this debilitating viral disease.