Diagnosis Of Dengue Virus Infection Research Articles

A study on evaluation and correlation of serological methods and platelet count for diagnosis of dengue virus infection.

Dengue is arthropod-borne, acute potentially fatal viral infection, endemic in many tropical and sub-tropical countries having public health threat globally in recent era. Effective and prompt diagnosis is very essential to reduce morbidity and mortality associated with severe form. Diagnosis by dengue-specific markers like Non-Structural protein 1 antigen or IgM/IgG antibody by serological method is the choice of investigation and the most widely used non-specific biomarker is platelet count. To evaluate and correlate results of two serological diagnostic methods (Dengue NS1 Antigen and Dengue IgM antibodies by Enzyme-Linked Immunosorbent Assay) and with platelet count for diagnosis of Dengue infection. Retrospective cross-sectional study for duration of 6 months from April 2022 to September 2022. Total 4063 serum samples of dengue suspected patients were tested according to duration of illness by ELISA for presence of NS1 Ag (≤5 days of illness) or IgM antibody (>5 days of illness). 393/4063 were detected positive by either method (NS1/IgM) and majority of patients were diagnosed between 3-8 days of illness. 248/2250 were tested positive for dengue NS1-Ag only, while 145/1813 were seropositive by dengue IgM only. Thrombocytopenia (platelet counts <100000/mm3) found in 301/393 seropositive cases which was also observed in NS1 (207/248 cases) and IgM (94/145 cases) seropositive patients. Dengue specific parameters (NS1/IgM detection) in combination with platelet count helps in accurate, timely diagnosis and better monitoring in clinical management of patients.

Development and assessment of a multiepitope synthetic antigen for the diagnosis of Dengue virus infection

Immunodiagnostic tests for detecting dengue virus infections encounter challenges related to cross-reactivity with other related flaviviruses. Our research focuses on the development of a synthetic multiepitope antigen tailored for dengue immunodiagnostics. Selected dengue epitopes involved structural linearity and dissimilarity from the proteomes of Zika and Yellow fever viruses which served for computationally modeling the three-dimensional protein structure, resulting in the design of two proteins: rDME-C and rDME-BR. Both proteins consist of seven epitopes, separated by the GPGPG linker, and a carboxy-terminal 6 × -histidine tag. The molecular weights of the final proteins rDME-C and rDME-BR are 16.83 kDa and 16.80 kDa, respectively, both with an isoelectric point of 6.35. The distinguishing factor between the two proteins lies in the origin of their epitope sequences, where rDME-C is based on the reference dengue proteome, while rDME-BR utilizes sequences from prevalent Dengue genotypes in Brazil from 2008 to 2019. PyMol analysis revealed exposure of epitopes in the secondary structure. Successful expression of the antigens was achieved in soluble form and fluorescence experiments indicated a disordered structure. In subsequent testing, rDME-BR and rDME-C antigens were assessed using an indirect Elisa protocol against Dengue infected serum, previously examined with a commercial diagnostic test. Optimal concentrations for antigens were determined at 10 µg/mL for rDME-BR and 30 µg/mL for rDME-C, with serum dilutions ranging from 1:50 to 1:100. Both antigens effectively detected IgM and IgG antibodies in Dengue fever patients, with rDME-BR exhibiting higher sensitivity. Our in-house test showed a sensitivity of 77.3 % and 82.6 % and a specificity of 89.4 % and 71.4 % for rDME-C and rDEM-BR antigens. No cross-reactivity was observed with serum from Zika-infected mice but with COVID-19 serum samples. Our findings underscore the utility of synthetic biology in crafting Dengue-specific multiepitope proteins and hold promise for precise clinical diagnosis and monitoring responses to emerging Dengue vaccines.

Bio-inspired graphene nanocomposite enabled electrochemical immunosensor for detection and quantification of NS1 protein of dengue virus

Dengue is a serious illness that affects a large portion of the global population. Infection with the dengue virus may have been silent or symptomatic, making identification crucial for tracking the virus's propagation and protecting society from its catastrophic consequences. The non-structural dengue protein NS1 has been used as a biomarker in the diagnosis of dengue because it circulates widely in the blood during the acute phase of the infection and is associated with viremia. In this study, we have reported the development of an electrochemical immunosensor using nanobio-inspired platform composed of ternary nanocomposite of reduced graphene oxide (rGO), polydopamine (pDA) and gold nanoparticles (AuNPs) immobilized with Anti-NS1 antibodies for the detection of NS1 protein. The nanocomposite formation and antibody immobilization are confirmed using various microscopic, spectroscopic and electrochemical techniques. The differential pulse voltammetry (DPV) has been used to investigate the detailed electrochemical properties and immunosensing response of the developed immunosensor device. The designed immunosensor showed linear detection response for NS1 protein from 1 ng ml−1 to 100 µg ml−1 with a sensitivity of 1.78 ng ml−1 mA−1 and good shelf life. This developed immunosensor with exceptionally low detection limit revealed its potential for early diagnosis of dengue virus infection.

A Review on Epidemiology, Clinical Manifestation and Diagnostic Approach of Dengue in Bangladesh Perspective

Background: Dengue is an arboviral disease caused by dengue virus; single positive stranded RNA virus of the family Flaviviridae. Symptomatic dengue infection causes a wide range of clinical manifestations; from mild dengue fever (DF) to potentially fatal disease, such as dengue hemorrhagic fever (DHF) or dengue shock syndrome (DSS). Dengue is endemic in Bangladesh with recurrent outbreak and is one of the major public health concerns in current period. Therefore; we conducted a literature review to analyze demography, epidemiology, pathogenesis, clinical feature and diagnosis of dengue virus infection. Methods: According to the PRISMA guidelines, the references were selected from PubMed, Web of Science and Google Scholar database using search strings containing a combination of terms that included ”dengue”, “Bangladesh”, “epidemiology”, “outbreak”,” pathogenesis”, “clinical manifestation”, “demography “and “diagnosis”. Quality of references was evaluated by independent contributors. Results: About 167,700 confirmed dengue cases were reported at 16’september’2023 in Bangladesh. Although dengue is endemic in Bangladesh, the current dengue surge is unusual in terms of seasonality and the early sharp increase in comparison to previous years, where the surge started around –late June. Plasma leakages are the main pathophysiological hallmark that distinguishes DHF from DF. Severe plasma leakage can result in hypovolemic shock. Various factors are thought to impact disease presentation and severity. Virus segregation in cell cultures, nucleic acid demonstration by polymerase chain reaction (PCR), and serological detection of viral antigens (such as NS1) or particular antibodies are the preferred microbiological assays for dengue detection. Currently, no specific drugs and licensed vaccines are available to treat dengue disease in any of its clinical presentations for all age group. Conclusion: Understanding the clinical manifestation of dengue infection, prompt diagnosis, appropriate treatment, active and continuous surveillance of cases and vectors are the essential determinants for dengue prevention, control and reducing fatality rate. J Bangladesh Coll Phys Surg 2023; 41: 69-81

Comparison of clinical and laboratory parameters of primary vs secondary dengue fever in travellers.

Dengue fever (DF), caused by the dengue virus (DENV), is the most common arboviral disease in travellers worldwide. It is hypothesized that compared with primary DF, secondary DF may result in antibody-dependent enhancement of the immune response, resulting in more severe disease. We aimed to compare clinical and laboratory parameters in travellers with primary and secondary DF to determine whether secondary DF is associated with markers of severe disease. We conducted a retrospective cohort study, which included all patients diagnosed with DF at the Central Virology Laboratory of the Israeli Ministry of Health during 2008-19. Clinical, laboratory and virological data were extracted from laboratory and patient records. A diagnosis of DENV infection was based on a positive nonstructural protein 1 (NS1) test, polymerase chain reaction or serology testing for immunoglobulin M (IgM) and immunoglobulin G (IgG). Primary and secondary infections were classified based on travel history, NS1 result and IgM/IgG ratio. Severe DF was defined according to WHO classification. We identified 245 DF cases: 210 (86%) primary and 35 (14%) secondary. Whilst fever duration was significantly longer in secondary compared with primary infections (6.4 vs 5.3days, P = 0.027), mean Aspartate aminotransferase levels were significantly higher in primary compared with secondary cases (146 vs 65U/L, P < 0.001), and no other clinical or laboratory parameter differed significantly between the groups. Of note, only four patients had severe DF, all had primary infections and none died. In a cohort of returning travellers with DF, secondary infection, compared with primary infection, was not associated with a consistent trend towards greater severity of the clinical and laboratory markers examined in this study.

Diagnosis of Dengue Virus Infections Imported to Hungary and Phylogenetic Analysis of Virus Isolates

Dengue virus is one of the most important arbovirus infections of public health concern. Between 2017 and June 2022, 75 imported dengue infections were confirmed by laboratory diagnostic methods in Hungary. Our study aimed to isolate the imported Dengue strains and characterize them by whole-genome sequencing. Laboratory diagnosis of imported infections was carried out using both serological and molecular methods. Virus isolation was attempted on Vero E6 cell lines. An in-house amplicon-based whole-genome sequencing method was applied for the detailed molecular characterization of the isolated virus strains. From 75 confirmed Dengue infected patients, 68 samples were used for virus isolation. Isolation and whole-genome sequencing were successful in the case of eleven specimens. Isolated strains belonged to Dengue-1,-2,-3 serotypes. The isolated strains corresponded to the circulating genotypes of the visited geographic area, and some of the genotypes were linked with more severe DENV cases in the literature. We found that multiple factors, including viral load, specimen type, and patient antibody status, influence the isolation efficacy. Analysis of imported DENV strains can help estimate the outcomes of a possible local DENV transmission in Hungary, a threat from the near future.

Strategies in the optimization of DNA hybridization conditions and its role in electrochemical detection of dengue virus (DENV) using response surface methodology (RSM).

In recent years, limited research has been conducted on enhancing DNA hybridization-based biosensor approaches using statistical models. This study explores the application of response surface methodology (RSM) to improve the performance of a DNA hybridization biosensor for dengue virus (DENV) detection. The biosensor is based on silicon nanowires decorated with gold nanoparticles (SiNWs/AuNPs) and utilizes methylene blue as a redox indicator. The DNA hybridization process between the immobilized DNA probe and the target DENV gene was monitored using differential pulse voltammetry (DPV) based on the reduction of methylene blue. Fourier-transform infrared spectroscopy (FTIR) and electrochemical impedance spectroscopy (EIS) were employed to confirm successful DNA hybridization events on the modified screen-printed gold electrode (SPGE) surface. Several parameters, including pH buffer, NaCl concentration, temperature, and hybridization time, were simultaneously optimized, with NaCl concentration having the most significant impact on DNA hybridization events. This study enhances the understanding of the role of each parameter in influencing DNA hybridization detection in electrochemical biosensors. The optimized biosensor demonstrated the ability to detect complementary oligonucleotide and amplified DENV gene concentrations as low as 0.0891 ng µL-1 (10 pM) and 2.8 ng µL-1, respectively. The developed biosensor shows promise for rapid clinical diagnosis of dengue virus infection.

Comparative Study of Antigen Detection and Viral Nucleic Acid Assay for Early Detection of Dengue Infection

Background : Differentiating dengue patients from other acute febrile illness patients is a great challenge among physicians. Thus early and rapid diagnosis of dengue virus infection is of top most importance. The present study was designed to establish an early and rapid diagnosis of dengue virus infection from single serum samples with comparison between two methods-antigen detection by Immunochromatographic test (ICT) and nucleic acid assay by Real time RT –PCR.&#x0D; Materials and methods : This cross sectional study was carried out in the Department of Microbiology, Chittagong Medical College and Chevron Laboratory in Chattogram during the period of January 2012 to December 2012. A total 115 clinically suspected dengue patient of all ages and both sexex from indoor and Out Patient Department (OPD) of Chittagong Medical College Hospital were enrolled in this study.&#x0D; Results : These test were done in 2-7 days of fever. Blood samples from 115 clinically suspected dengue cases had been taken. Among them, NS1 antigen by ICT were found positive in 78(67.8 %) cases and DENV RNA by realtime RT-PCR in 64 (55.7% ) cases. Among 64 dengue PCR positive cases, dengue ICT was found positive in 61 (95.30%) cases &amp; not detectable in 03 (4.65%) cases and in 51 PCR negative cases, 17 were found positive by ICT. The difference in diagnosing dengue by ICT and PCR was found highly significant, p &lt; 0.001. Highest positivity of both test were observed in 2nd to 4th days. In this study, dengue ICT was detected 19 (70%) cases in • 5 days of fever where as PCR was detected only 02 (6.80%) cases. The sensivity , specificity , positive predictive value , negative predictive value of ICT in comparison to PCR were found 95.3% , 66.7%, 78.2 %, 91.9% respectively.&#x0D; Conclusion : In the comparative evaluation, NS1 Antigen was found to be far more sensitive than Real time RT-PCR 1.&#x0D; IAHS Medical Journal Vol 4(2), December 2021; 60-65

Development of multivariate classification models for the diagnosis of dengue virus infection

The dengue virus (DENV) infection is a worldwide cause of serious illness and death. Early and efficient prediction of disease may help in proper medical management to control disease. Keeping this in view, multivariate classification models by combining with Raman spectroscopy have been developed for the diagnosis of DENV infection in human blood sera. For study design, a statistical analysis is performed to select the sample size for training of models. Total 1240 Raman spectra have been acquired from 39 DENV infected and 23 healthy sera samples. Prior to model development, Raman spectra were examined using ANOVA test for significant differences present in the intensities of newly appeared Raman bands at 622, 645, 700, 746, 800, 814, 873, 890, 948, 1002, 1018, 1080, 1235, 1250, 1272, 1386, 1404, 1446, 1609 and 1645 cm−1. The significant differences and characteristic patterns of Raman bands induced by disease played decisive role and are exploited for development of multivariate model. Classification models are developed by utilizing principal component analysis (PCA) to extract discriminant features from multidimensional Raman spectral dataset and followed by support vector machines (SVM) with Polynomial of 5, RBF, and liner kernels. The proposed model for this study is built using 10-fold cross validation technique and evaluated on independent dataset to demonstrate its robustness. PCA-SVM (poly-5) model successfully yielded high diagnostic accuracy of 99.52%, sensitivity of 99.75%, specificity of 99.09% for classification of unknown suspected samples. For comparison, PCA discriminant analysis (PCA-DA), partial least squares regression (PLSR) are PLS-DA have been compared. It is found that PCA-SVM (poly-5) approach is more effective and robust compared to other state-of-the-art approaches and it can be used for clinical prediction of DENV infection in human blood sera.

Korelasi Nilai Hematokrit dan Jumlah Trombosit dengan Antibodi IgG dan IgM Dengue

Dengue virus infection can affect blood cells, one of which is the number of platelets so that it decreases, due to the formation of viral antibody complexes that stimulate platelet aggregation. DHF is characterized by plasma leakage with an increase in hematocrit &gt;20%. Diagnosis of dengue virus infection is supported by examination of IgG and IgM antibodies, platelet count, and hematocrit. The purpose of this study was to determine the correlation between hematocrit and platelet counts with IgG and IgM antibodies to DHF. Research method: cross-sectional. Laboratory data were processed using the SPSS Chi-Square test software. The results of the statistical test of the correlation between IgG/IgM antibody results with platelet count p = 0.375 and IgG/IgM antibody results on hematocrit p = 0.487 so that it has a significance value of &gt; 0.05. Conclusion: there is no correlation between hematocrit value and platelet count with dengue IgG and IgM antibodies.

Diagnosis of dengue virus infection using spectroscopic images and deep learning.

Dengue virus (DENV) infection is one of the major health issues and a substantial epidemic infectious human disease. More than two billion humans are living in dengue susceptible regions with annual infection mortality rate is about 5%–20%. At initial stages, it is difficult to differentiate dengue virus symptoms with other similar diseases. The main objective of this research is to diagnose dengue virus infection in human blood sera for better treatment and rehabilitation process. A novel and robust approach is proposed based on Raman spectroscopy and deep learning. In this regard, the ResNet101 deep learning model is modified by exploiting transfer learning (TL) concept on Raman spectroscopic data of human blood sera. Sample size was selected using standard statistical tests. The proposed model is evaluated on 2,000 Raman spectra images in which 1,200 are DENV-infected of human blood sera samples, and 800 are healthy ones. It offers 96.0% accuracy on testing data for DENV infection diagnosis. Moreover, the developed approach demonstrated minimum improvement of 6.0% and 7.0% in terms of AUC and Kappa index respectively over the other state-of-the-art techniques. The developed model offers superior performance to capture minute Raman spectral variations due to the better residual learning capability and generalization ability compared to others deep learning models. The developed model revealed that it might be applied for diagnosis of DENV infection to save precious human lives.

Incidence of Dengue fever, serotypes, clinical features, and laboratory markers: a case study of 2019 outbreak at district Shangla, KP, Pakistan.

Dengue is a widely spread mosquito-borne infection in humans, which in recent decades declared is public health problem globally. The dengue virus contains 4 different serotypes (DENV-1, DENV-2, DENV-3, and DENV-4) which belong to the genus Flavivirus. A descriptive experimental study was conducted to determine the epidemiology, types of Dengue serotypes, clinical features, laboratory probe, and markers for primary diagnosis of dengue virus infection in hospitalized patients. A total of 691 suspects were diagnosed from August to October 2019 in district Shangla KP, Pakistan. Serological tests were used for nonstructural protein-1 antigen (NS1), and antibodies (immunoglobulin-M (IgM) & Immunoglobulin-G (IgG)) while real-time PCR was used to confirm the cases. The data was statistically analyzed using IBM-SPSS Statistics 20 version. The dengue virus infection was more prevalent in the male group (68.09%) than the female group (31.1%). A large number of patients were from rural areas (63.5%) while from urban areas were (36.4%), whereas Besham tehsil was found the most affected compared to other regions. The most prevalent serotype observed in our study was DENV-3 (56.60%) while DENV-4 was the least prevalent serotype (1.88%). Among the age-wise analysis of dengue-virus-infected individuals, the age group of 19-37 years (64.07%) was found the most affected group. The month-wise analysis revealed that the highest number of infections (49.8%) were recorded in September. Significant differences were noticed among blood parameters. The possible reasons for the dengue overwhelming in the study area could be less or lack of awareness particularly regarding the transmission of viral infections, improper sewage management, and no effective vector control strategies that lead the dengue outbreaks in the study population.

Analisis Survival dengan Menggunakan Metode Kaplan Meier pada Penderita Penyakit Demam Berdarah Dengue (DBD)

The Kaplan Meier method is one of the methods in survival analysis that is used to find out how big the chances of survival of a person suffering from a certain disease. The Kaplan Meier method calculates the patient's life by providing a definite survival proportion. The purpose of this study was to determine the relationship between age and length of treatment and patient status. The life chances of DHF patients using the Kaplan Meier method at the Lasinrang District Hospital. Pinrang. The results showed that there was no relationship between age and length of treatment as well as the status of DHF patients in Lasinrang Hospital Kab. Pinrang. The conclusion of this study is that the chance of survival of DHF patients before a patient dies is 100%. However, the chance of patient survival after 1 patient died during the observation was 99.1%. It is recommended that clinical monitoring should always be carried out, to predict the correct diagnosis of Dengue Virus Infection. And sero-epidemiological studies should continue to be carried out in many island capitals in Indonesia.

A novel anti-NS2BNS3pro antibody-based indirect ELISA test for the diagnosis of dengue virus infections.

Dengue virus reportedly circulates as four genetically distinct serotypes for which there is no widely accepted vaccine or drug at present. Morbidity and mortality caused by this virus are alarming for the possible increased threat to human health. A suitable diagnostic test is the prerequisite for designing and developing control measures. But, the tests being employed at present possess one or the other drawback for this disease diagnosis. During the dengue virus infections, NS2B is essential for the stability and catalytic activity of the NS3 protease. N-terminal 185 amino acids of NS3 protease domain along with hydrophilic portion of NS2B (NS2BNS3pro) is being used to screen dengue inhibitors but not for diagnosis until now. In the present study, we have used purified NS2BNS3pro as an antigen to trap anti-NS2BNS3pro antibodies of the clinical samples. Antibodies were detected successfully in both Western blot analysis and enzyme-linked immunosorbent assay (ELISA) tests. In ELISA, antibodies were detected in both primary and secondary infections of all serotypes. Interestingly, 17 samples declared as other febrile infections by NS1 and IgM/IgG tests were found to be positive in present test, which were further confirmed by reverse-transcription polymerase chain reaction. In silico studies suggested the absence of conserved epitopes between NS2BNS3pro and the counterpart in JEV, Zika, and CHIKV, indicating less possibility of crossreaction, which was in turn confirmed by using synthetic peptides representing the above epitopes. Statistical analysis with 76% specificity, 87% sensitivity, and 95% concordance also supported the present test as a suitable test for large scale diagnosis of dengue virus infections.

Chymase level in dengue virus infection with or without positive Non-Structural 1(NS1)

Thrombocytopenia, leukopenia, and monocytosis are laboratory parameters in the diagnosis of dengue virus infection. In addition to monocyte cells, mast cells also play a role in the innate immune response, where degranulation of mast cells will occur, which will secretion the active vaso mediator, Chymase. Chymase has a role in increasing vascular permeability resulting in plasma leakage in patients with dengue virus infection to determine the number of platelets, leukocytes, monocytes and chymase levels in patients with dengue infection in the acute phase. The platelet count mean in NS1 (+) was 132,140 cells / mm3 and the platelet count in the NS1 group was (-) 176,000 cells / mm3. The mean leukocytes NS1 (+) showed results of 4,350 cells / mm3 and NS1 (-) 5,250 cells / mm3. The mean monocyte NS1 (+) monocyte count was 8.26%, and NS1 (-) group was 8.76%. There were no significant differences in platelet counts, leukocytes and monocytes between NS1 (+) and NS1 (-) (P value&gt; 0.05). The mean Chymase NS1 (+) 23.48, NS1 (-) 23.05 ng / mL and the control group 1.47ng / mL.

Serological point-of-care and label-free capacitive diagnosis of dengue virus infection

Dengue non-structural protein 1 (NS1 DENV) is considered a biomarker for dengue fever in an early stage. A sensitive and rapid assay for distinguishing positive from negative dengue infection samples is imperative for epidemic control and public health in tropical regions because it enables the development of instantaneous updatable databases and effective surveillance systems. Presently, we successfully report, for the first time, the use of the electrochemical capacitive method for the detection of NS1 DENV biomarker in human serum samples. By using a ferrocene-tagged peptide modified surface containing anti-NS1 as the receptor, it was possible to differentiate positive from negative samples with a p < 0.01 in a reagentless and label-free capacitive format. This capacitive assay had a cut-off of 1.36% (confidence interval of 99.99%); it therefore opens new avenues for developing miniature label-free electrochemical devices for infectious diseases.

Horseradish peroxidase-labeled rabbit anti-non-structural protein 1 of dengue virus-2 for the diagnosis of dengue virus infections

BACKGROUND Early diagnosis of dengue virus (DENV) infection is essential for patient management and disease control. Detection of the antigen non-structural protein 1 (NS1) has been proven to provide early diagnosis of DENV infection. Thus, commercial NS1 antigen detection assays have been increasingly used and are becoming thetool of choice among clinicians to confirm DENV infection in Indonesia.&#x0D; METHODS To obtain anti-NS1 DENV antibody, NS1 protein (90 µg/ml) from the collection of the Department of Microbiology, Faculty of Medicine, Universitas Indonesia was injected into a rabbit. The anti-NS1 antibody from the rabbit was then labeled with horseradish peroxidase (HRP) using the periodate oxidation method. Sera were tested by enzyme-linked immunosorbent assay (ELISA) to detect NS1 from DENV-infected patients.&#x0D; RESULTS Serially diluted antibody labeled with HRP tested using the direct ELISA method showed the highest absorbance value at a 1:100 dilution (Mean [SD] = 1.35 [0.35]); even at a dilution as high as 1:3,200 (0.22 [0.15]), antibody labeled with HRP was able to detect the NS1 protein, although the absorbance value did not differ greatly from that of the negative control (0.13 [0.01]).&#x0D; CONCLUSIONS In an attempt to develop an NS1-based diagnostic test, polyclonal anti-NS1 DENV antibody was successfully produced as a diagnostic assay to determine the presence of DENV NS1 antigen in patients’ sera.

Laser scanning optical investigations of dengue virus infection from antibody fluorescence of human blood

Dengue is the most important arthropod-borne viral disease of public health significance today, and the geographic distribution includes more than 100 countries worldwide. A definite diagnosis of dengue virus infection is based on clinical criteria supported by antibody tests of whole blood. In this study, we report on dengue infected whole blood diagnostics using laser scanning confocal microscopy (LSCM) over a laser excitation of 488, 543 and 633 nm wavelengths. Based on our findings, the system has potential applications in the detection and quantification of dengue virus infected cells, antigens and antibodies in blood in vitro. Analysis of about 100 infected patients shows that the primary organism (or pathogen), characteristic of dengue infection, causes a significant biochemical change in the nature of human blood in which it resides, and, due to which, fluorescence increases in dengue samples. Thus, the use of a reliable and sensitive rapid diagnostic test using LSCM can simultaneously detect the presence of anti-dengue IgG and IgM antibodies, which is a breakthrough in diagnosis and of great clinical use. The antibodies for dengue continue to be distinguishable for a couple of months after infection. This change in blood fluorescence may be a significant contribution from light scattering through antibodies produced against the dengue antigen.

Development of peptide-based chemiluminescence enzyme immunoassay (CLEIA) for diagnosis of dengue virus infection in human

Dengue is the most prevalent mosquito-borne viral disease in tropical and subtropical regions worldwide. Since its clinical symptoms are non-specific and easily mistaken as other kinds of infection, laboratory diagnosis is required to confirm dengue infections. In this study, ten peptides (E1-E10) from the envelope protein of dengue virus (DENV) were first identified using bioinformatic tool. The screened peptides were then synthesized for the peptide-based chemiluminescence enzyme immunoassay (CLEIA). Two peptides, E1 and E7, were found as the best candidate antigen and therefore used as downstream application in the development of low-cost peptide-based anti-DENV immunoglobulin M antibodies (IgM) indirect CLEIA. 176 serum samples were used to study the presence of anti-DENV IgM antibodies to evaluate the diagnostic ability of IgM-CLEIA. Receiver operating characteristic curve (ROC) was used to estimate the diagnostic cut-off value. The sensitivity and the specificity reached 82.5% and 94.6% respectively when peptide E1 was used, but declined to 79.2% and 92.9% respectively when peptide E7 was used. Therefore, the combination of E1 and E7 was used to improve the sensitivity and the specificity to 85.0% and 96.4% respectively in 1.5 h assay time, providing a potentially practical use for the diagnosis of DENV infections in patients' serum.

NILAI DIAGNOSTIK ANTI DENGUE IgA DAN NS1, SERTA IgM/IgG DI INFEKSI VIRUS DENGUE (The Diagnostic Value of Anti Dengue IgA and Anti Dengue IgM/IgG in Dengue Virus Infection)

The clinical manifestations of dengue virus infection are varied and thus a specific diagnostic examination is required. Usually antidengueIgM is often used, but the presence in the circulation is 3−8 months long. NS1 is sensitive in the detection of primary infection,whereas IgG is more better used in secondary infection. The examination of anti-dengue IgA as a new marker is estimated to be ableto detect the acute primary and secondary infection, however the diagnostic value of anti-dengue IgA is not much well known for theIndonesian population. This study was done at the Tropical Infectious Disease Ward of Dr. Soetomo Hospital, Surabaya during February– April 2013. The samples consisted of 37 sera from patients infected by dengue virus and 37 sera from those non one (dengue virusinfection patients). The NS1 serum, anti-dengue IgM and anti dengue IgG were examined by ELISA and anti-dengue IgA was examined byan indirect immunochromatography method using Assure@ Dengue IgA Rapid Test (MP Biomedicals Asia Pacific Pte Ltd). The diagnosticvalue was analyzed by 2x2 table with a confidence interval of (CI) 95%. The used gold standards were from the 1997th WHO criteriaand one of the positive dengue serological tests by ELISA (NS1/anti dengue IgM/anti dengue IgG). AUC and anti-dengue IgA cut-off weredetermined by ROC curve. The Diagnostic value of anti-dengue IgA showed a sensitivity and specificity of 83.8% (67.3 to 93.2) and 81.1%(64.3 to 91.4). A positive predictive value of 81.6% (65.1 to 91.7) and a negative predictive value of 83.3% (66.5 to 93.0) was found. Thepositive likelihood ratio was 4.4 times (2.2 to 8.8) and negative likelihood ratio of only 0.2 times (0.09 to 0.42). The best cut off valueof 0.2 was shown by the area under the curve of 83.5%. Based on this study, the diagnostic value of anti-dengue IgA had a good validityfor the diagnosis of dengue virus infection.