Integrated serum proteomic and N-glycoproteomic characterization of dengue patients.

Dengue fever is a mosquito-borne viral disease caused by the dengue virus (DENV). It poses a public health threat globally and, while most people with dengue have mild symptoms or are asymptomatic, approximately 5% of affected individuals develop severe disease and need hospital care. However, knowledge of the molecular mechanisms underlying dengue infection and the interaction between the virus and its host remains limited. In the present study, we performed a quantitative proteomic and N-glycoproteomic analysis of serum from 19 patients with dengue and 11 healthy people. The results revealed distinct proteomic and N-glycoproteomic landscapes between the two groups. Notably, we report for the first time the changes in the serum N glycosylation pattern following dengue infection and provide abundant information on glycoproteins, glycosylation sites, and intact N-glycopeptides using recently developed site-specific glycoproteomic approaches. Furthermore, a series of key functional pathways in proteomic and N-glycoproteomic were identified. Collectively, our findings significantly improve understanding of host and DENV interactions and the general pathogenesis and pathology of DENV, laying a foundation for functional studies of glycosylation and glycan structures in dengue infection.

Co-Infection of Dengue in a Pregnant Woman With COVID-19 Disease.

The pandemic due to severe respiratory syndrome coronavirus 2 (SARS-Cov-2) was one of the most damaging healthcare emergencies the world has ever seen. Co-infection with dengue virus in COVID-19-positive patients is an additional challenge especially in dengue-endemic areas. Both dengue and COVID-19 infection cause increased morbidity and adverse outcomes in pregnant women, and simultaneous infection of these two illnesses can be further detrimental and sometimes fatal in pregnant women. Here, we present a case of a pregnant woman in her early second trimester with co-infection of dengue and moderate COVID-19 disease who was managed successfully and had a favorable outcome.

Simultaneous quantitation of neutralizing antibodies against all four dengue virus serotypes using optimized reporter virus particles.

Serum-neutralizing antibody titers are a critical measure of vaccine immunogenicity and are used to determine flavivirus seroprevalence in study populations. An effective dengue virus (DENV) vaccine must confer simultaneous protection against viruses grouped within four antigenic serotypes. Existing flavivirus neutralization assays, including the commonly used plaque/focus reduction neutralization titer (PRNT/FRNT) assay, require an individual assay for each virus, serotype, and strain and easily become a labor-intensive and time-consuming effort for large epidemiological studies or vaccine trials. Here, we describe a multiplex reporter virus particle neutralization titer (TetraPlex RVPNT) assay for DENV that allows simultaneous quantitative measures of antibody-mediated neutralization of infection against all four DENV serotypes in a single low-volume clinical sample and analyzed by flow cytometry. Comparative studies confirm that the neutralization titers of antibodies measured by the TetraPlex RVPNT assay are similar to FRNT/PRNT assay approaches performed separately for each viral strain. The use of this high-throughput approach enables the careful serological study in DENV endemic populations and vaccine recipients required to support the development of a safe and effective tetravalent DENV vaccine. IMPORTANCE: As a mediator of protection against dengue disease and a serological indicator of prior infection, the detection and quantification of neutralizing antibodies against DENV is an important "gold standard" tool. However, execution of traditional neutralizing antibody assays is often cumbersome and requires repeated application for each virus or serotype. The optimized RVPNT assay described here is high-throughput, easily multiplexed across multiple serotypes, and targets reporter viral particles that can be robustly produced for all four DENV serotypes. The use of this transformative RVPNT assay will support the expansion of neutralizing antibody datasets to answer research and public health questions often limited by the more cumbersome neutralizing antibody assays and the need for greater quantities of test serum.

Forecasting and mapping dengue fever epidemics in China: a spatiotemporal analysis.

BACKGROUND: Dengue fever (DF) has emerged as a significant public health concern in China. The spatiotemporal patterns and underlying influencing its spread, however, remain elusive. This study aims to identify the factors driving these variations and to assess the city-level risk of DF epidemics in China. METHODS: We analyzed the frequency, intensity, and distribution of DF cases in China from 2003 to 2022 and evaluated 11 natural and socioeconomic factors as potential drivers. Using the random forest (RF) model, we assessed the contributions of these factors to local DF epidemics and predicted the corresponding city-level risk. RESULTS: Between 2003 and 2022, there was a notable correlation between local and imported DF epidemics in case numbers (r = 0.41, P < 0.01) and affected cities (r = 0.79, P < 0.01). With the increase in the frequency and intensity of imported epidemics, local epidemics have become more severe. Their occurrence has increased from five to eight months per year, with case numbers spanning from 14 to 6641 per month. The spatial distribution of city-level DF epidemics aligns with the geographical divisions defined by the Huhuanyong Line (Hu Line) and Qin Mountain-Huai River Line (Q-H Line) and matched well with the city-level time windows for either mosquito vector activity (83.59%) or DF transmission (95.74%). The RF models achieved a high performance (AUC = 0.92) when considering the time windows. Importantly, they identified imported cases as the primary influencing factor, contributing significantly (24.82%) to local DF epidemics at the city level in the eastern region of the Hu Line (E-H region). Moreover, imported cases were found to have a linear promoting impact on local epidemics, while five climatic and six socioeconomic factors exhibited nonlinear effects (promoting or inhibiting) with varying inflection values. Additionally, this model demonstrated outstanding accuracy (hitting ratio = 95.56%) in predicting the city-level risks of local epidemics in China. CONCLUSIONS: China is experiencing an increasing occurrence of sporadic local DF epidemics driven by an unavoidably higher frequency and intensity of imported DF epidemics. This research offers valuable insights for health authorities to strengthen their intervention capabilities against this disease.

Pro- and anti-inflammatory cytokines signatures at different severity of dengue infection.

Context: Dengue disease severity and progression are determined by the host immune response, with both pro- and anti-inflammatory cytokines are key mediators. Aims: To study pro- and anti-inflammatory cytokines across dengue severity and as a biomarker for predicting severe dengue infection. Settings and Design: Hospital-based cross-sectional study was conducted on 125 dengue-positive subjects across the 5-60 years age group of either gender in 2022. Methods and Materials: Haematological parameters and blood samples were drawn to measure cytokines IL6, IL-10 and TNF alpha using the ELISA technique. Statistical Analysis: One-way ANOVA and the Kruskal - Wallis test were used to compare the dependent variables across categories of the dengue spectrum. Receiver operating characteristic curve was drawn to calculate the predictability of the cytokines as a predictor of severe dengue. A P < 0.05 was considered significant. Results: 34.4% of cases had severe dengue infection with 53.2% of severe cases reported in >40 years of age. Only IL-6 levels significantly increased (P < 0.01) across the spectrum of dengue infection across age groups >20 years with a consistent and significant fall in platelet levels (P < 0.01). The accuracy of IL-6 to predict severe dengue was 74.4% and platelet count was 16.2%. Conclusions: Only IL-6 cytokine levels were significantly increased across the spectrum of dengue infection observed in age >20 years and can significantly predict the probability of severe dengue by 74% (sensitivity 81.4%). A significant decrease in platelet values is consistent with the severity but is not a good predictor for severe dengue infection.

Epidemiology of Travel-Associated Dengue from 2007 to 2022: A GeoSentinel Analysis.

BACKGROUND: Dengue is a leading cause of febrile illness among international travellers. We aimed to describe the epidemiology and clinical characteristics of imported dengue in returning travellers evaluated at GeoSentinel sites from 2007-2022. METHODS: We retrieved GeoSentinel records of dengue among travellers residing in non-endemic countries. We considered dengue confirmed when diagnosed by a positive DENV-specific RT-PCR, positive NS-1 antigen, and/or anti-DENV IgG seroconversion, and probable when diagnosed by single anti-DENV IgM or high titre anti-DENV IgG detection. Severe dengue was defined as evidence of clinically significant plasma leakage or bleeding, organ failure, or shock, according to the 2009 WHO guidance. Complicated dengue was defined as either severe dengue or dengue with presence of any warning sign. Analyses were descriptive. RESULTS: This analysis included 5958 travellers with confirmed (n = 4859; 81.6%) or probable (n = 1099; 18.4%) dengue. The median age was 33 years (range: < 1-91); 3007 (50.5%) travellers were female. The median travel duration was 21 days (interquartile range [IQR]: 15-32). The median time between illness onset and GeoSentinel site visit was 7 days (IQR: 4-15). The most frequent reasons for travel were tourism (67.3%), visiting friends or relatives (12.2%), and business (11.0%). The most frequent regions of acquisition were Southeast Asia (50.4%), South-Central Asia (14.9%), the Caribbean (10.9%), and South America (9.2%). Ninety-five (1.6%) travellers had complicated dengue, of whom 27 (0.5%) had severe dengue, and one died. Of 2710 travellers with data available, 724 (26.7%) were hospitalized. The largest number of cases (n = 835) was reported in 2019. CONCLUSIONS: A broad range of international travellers should be aware of the risk of acquiring dengue and receive appropriate pretravel counselling regarding preventive measures. Prospective cohort studies are needed to further elucidate dengue risk by destination and over time, as well as severe outcomes and prolonged morbidity (long-dengue) due to travel-related dengue.

Pyopericardium progressing to cardiac tamponade in a patient with dengue fever.

Pyopericardium is a rare cause of cardiac tamponade. We present a case of a dengue fever patient who presented with cellulitis of the upper limbs, later manifesting cardiac tamponade, which was fatal. Although echocardiography on admission revealed a small pericardial effusion only, it later manifested as tamponade, causing cardiogenic shock. Staphylococcus pyopericardium was found later. Early identification could be possible with bedside point-of-care ultrasonography and echocardiography. Emergent pericardiocentesis or pig tail drain placement is life saving.

Evaluation of assays for nucleic acid testing for the prevention of chikungunya and dengue virus transmission by blood transfusion.

BACKGROUND: The large dengue (DENV) and chikungunya (CHIKV) outbreaks observed during the last decade across the world, as well as local transmissions in non-endemic areas are a growing concern for blood safety. The aim of this study was to evaluate and compare the sensitivity of nucleic acid tests (NAT) detecting DENV and CHIKV RNA. MATERIALS AND METHODS: Using DENV 1 to 4 International Standards, the limits of detection (LODs) calculated by probit analysis of two NAT assays; the cobas CHIKV/DENV assay (Roche Diagnostics) and the Procleix Dengue Virus Assay (Grifols) were compared. In addition, CHIKV-RNA LOD of the cobas CHIKV/DENV assay was evaluated. RESULTS: For dengue, the 95% LOD of the cobas assay ranged between 4.10 [CI95%: 2.70-8.19] IU/mL (DENV-2) and 7.07 [CI95%: 4.34-14.89] IU/mL (DENV-4), and between 2.19 [CI95%: 1.53-3.83] IU/mL (DENV-3) and 5.84 [CI95%: 3.84-10.77] IU/mL (DENV-1) for Procleix assay. The Procleix assay had a significant lower LOD for DENV-3 (2.19 vs. 5.89 IU/mL) when compared to the cobas assay (p = 0.005). The 95% LOD for CHIKV-RNA detection of the cobas assay was 4.76 [CI95%: 3.08-8.94] IU/mL. DISCUSSION: The two NAT assays developed for blood donor screening evaluated in this study demonstrated high and similar analytical performance. Subject to an appropriate risk-benefit assessment, they can be used to support blood safety during outbreaks in endemic areas or in non-endemic areas as an alternative to deferring blood donors during local transmission likely to affect the blood supply. The development of multiplex assays is expected to optimize laboratory organization.

Molecular epidemiology of dengue in Malaysia: 2015-2021.

Dengue has been one of the major public health problems in Malaysia for decades. Over 600,000 dengue cases and 1,200 associated fatalities have been reported in Malaysia from 2015 to 2021, which was 100% increase from the cumulative total of dengue cases reported during the preceding 07-year period from 2008 to 2014. However, studies that describe the molecular epidemiology of dengue in Malaysia in recent years are limited. In the present study, we describe the genetic composition and dispersal patterns of Dengue virus (DENV) by using 4,004 complete envelope gene sequences of all four serotypes (DENV-1 = 1,567, DENV-2 = 1,417, DENV-3 = 762 and DENV-4 = 258) collected across Malaysia from 2015 to 2021. The findings revealed that DENV populations in Malaysia were highly diverse, and the overall heterogeneity was maintained through repetitive turnover of genotypes. Phylogeography analyses suggested that DENV dispersal occurred through an extensive network, mainly among countries in South and East Asia and Malaysian states, as well as among different states, especially within Peninsular Malaysia. The results further suggested Selangor and Johor as major hubs of DENV emergence and spread in Malaysia.

Dengue virus exploits autophagy vesicles and secretory pathways to promote transmission by human dendritic cells.

Dengue virus (DENV), transmitted by infected mosquitoes, is a major public health concern, with approximately half the world's population at risk for infection. Recent decades have increasing incidence of dengue-associated disease alongside growing frequency of outbreaks. Although promising progress has been made in anti-DENV immunizations, post-infection treatment remains limited to non-specific supportive treatments. Development of antiviral therapeutics is thus required to limit DENV dissemination in humans and to help control the severity of outbreaks. Dendritic cells (DCs) are amongst the first cells to encounter DENV upon injection into the human skin mucosa, and thereafter promote systemic viral dissemination to additional human target cells. Autophagy is a vesicle trafficking pathway involving the formation of cytosolic autophagosomes, and recent reports have highlighted the extensive manipulation of autophagy by flaviviruses, including DENV, for viral replication. However, the temporal profiling and function of autophagy activity in DENV infection and transmission by human primary DCs remains poorly understood. Herein, we demonstrate that mechanisms of autophagosome formation and extracellular vesicle (EV) release have a pro-viral role in DC-mediated DENV transmission. We show that DENV exploits early-stage canonical autophagy to establish infection in primary human DCs. DENV replication enhanced autophagosome formation in primary human DCs, and intrinsically-heightened autophagosome biogenesis correlated with relatively higher rates of DC susceptibility to DENV. Furthermore, our data suggest that viral replication intermediates co-localize with autophagosomes, while productive DENV infection introduces a block at the late degradative stages of autophagy in infected DCs but not in uninfected bystander cells. Notably, we identify for the first time that approximately one-fourth of DC-derived CD9/CD81/CD63+ EVs co-express canonical autophagy marker LC3, and demonstrate that DC-derived EV populations are an alternative, cell-free mechanism by which DCs promote DENV transmission to additional target sites. Taken together, our study highlights intersections between autophagy and secretory pathways during viral infection, and puts forward autophagosome accumulation and viral RNA-laden EVs as host determinants of DC-mediated DENV infection in humans. Host-directed therapeutics targeting autophagy and exocytosis pathways thus have potential to enhance DC-driven resistance to DENV acquisition and thereby limit viral dissemination by initial human target cells following mosquito-to-human transmission of DENV.

Spatial and temporal analysis on the impact of ultra-low volume indoor insecticide spraying on Aedes aegypti household density.

BACKGROUND: Aedes aegypti is the primary mosquito vector for several arboviruses, such as dengue, chikungunya and Zika viruses, which cause frequent outbreaks of human disease in tropical and subtropical regions. Control of these outbreaks relies on vector control, commonly in the form of insecticide sprays that target adult female mosquitoes. However, the spatial coverage and frequency of sprays needed to optimize effectiveness are unclear. In this study, we characterize the effect of ultra-low-volume (ULV) indoor spraying of pyrethroid insecticides on Ae. aegypti abundance within households. We also evaluate the effects of spray events during recent time periods or in neighboring households. Improved understanding of the duration and distance of the impact of a spray intervention on Ae. aegypti populations can inform vector control interventions, in addition to modeling efforts that contrast vector control strategies. METHODS: This project analyzes data from two large-scale experiments that involved six cycles of indoor pyrethroid spray applications in 2 years in the Amazonian city of Iquitos, Peru. We developed spatial multi-level models to disentangle the reduction in Ae. aegypti abundance that resulted from (i) recent ULV treatment within households and (ii) ULV treatment of adjacent or nearby households. We compared fits of models across a range of candidate weighting schemes for the spray effect, based on different temporal and spatial decay functions to understand lagged ULV effects. RESULTS: Our results suggested that the reduction of Ae. aegypti in a household was mainly due to spray events occurring within the same household, with no additional effect of sprays that occurred in neighboring households. Effectiveness of a spray intervention should be measured based on time since the most recent spray event, as we found no cumulative effect of sequential sprays. Based on our model, we estimated the spray effect is reduced by 50% approximately 28 days after the spray event. CONCLUSIONS: The reduction of Ae. aegypti in a household was mainly determined by the number of days since the last spray intervention in that same household, highlighting the importance of spray coverage in high-risk areas with a spray frequency determined by local viral transmission dynamics.

Mathematical analysis and prediction of future outbreak of dengue on time-varying contact rate using machine learning approach.

This article introduces a novel mathematical model analyzing the dynamics of Dengue in the recent past, specifically focusing on the 2023 outbreak of this disease. The model explores the patterns and behaviors of dengue fever in Bangladesh. Incorporating a sinusoidal function reveals significant mid-May to Late October outbreak predictions, aligning with the government's exposed data in our simulation. For different amplitudes (A) within a sequence of values (A = 0.1 to 0.5), the highest number of infected mosquitoes occurs in July. However, simulations project that when ßM = 0.5 and A = 0.1, the peak of human infections occurs in late September. Not only the next-generation matrix approach along with the stability of disease-free and endemic equilibrium points are observed, but also a cutting-edge Machine learning (ML) approach such as the Prophet model is explored for forecasting future Dengue outbreaks in Bangladesh. Remarkably, we have fitted our solution curve of infection with the reported data by the government of Bangladesh. We can predict the outcome of 2024 based on the ML Prophet model situation of Dengue will be detrimental and proliferate 25 % compared to 2023. Finally, the study marks a significant milestone in understanding and managing Dengue outbreaks in Bangladesh.

Estimating dengue burden among family contacts through cluster investigation around probable cases in 2022 and 2023 in the Central Region, Burkina Faso.

BACKGROUND: In 2023, Burkina Faso experienced the largest dengue epidemic ever in Africa. This study aimed to estimate the prevalence of symptomatic, subclinical, and asymptomatic dengue and determine the associated factors among adult contacts of dengue in the Central Region, Burkina Faso. METHODS: This cross-sectional study included contacts of dengue probable cases through cluster sampling in 2022-2023. These suspected cases that tested positive were identified from the five health facilities (Pissy CMA, Saaba CM, Kossodo CMA, Samandin CM, and Marcoussis CSPS) that reported the highest number of cases in 2021 per district. All participants underwent dengue and malaria rapid diagnostic tests (RDT). Samples positive for non-structural 1 protein antigen (AgNS1) and/or immunoglobulin M (IgM) were tested for serotype detection by reverse transcription polymerase chain reaction (RT-PCR). Binary logistic regression was done to identify the determinants of asymptomatic, subclinical, and symptomatic dengue among contacts of probable dengue cases. RESULTS: A total of 484 contacts were included, mostly in 2023 (75.2%). Most participants were females (58.6%), residing (24.3%) and passing their daytime (23.1%) in Saaba. The overall prevalence of dengue was estimated at 15.1% [95% confidence interval (CI): 12.0-18.6%], representing cases not seeking care in hospitals. Asymptomatic cases represented 2.9% (95% CI: 1.6-4.8%). Subclinical and symptomatic cases accounted for 6.0% (95% CI: 4.1-8.5%) and 6.2% (95% CI: 4.2-8.7%), respectively. Of the 58 samples tested by RT-PCR, 10 were confirmed for serotype 3 in 2023. Malaria cases were estimated at 5.6% (95% CI: 3.7-8.0%). After adjustment, participants claiming that a virus transmits dengue were likelier to have asymptomatic dengue [adjusted odds ratio (aOR) = 7.1, 95% CI: 2.4-21.0]. From the multivariable analysis, subclinical dengue was statistically associated with being included in the study in 2023 (aOR = 30.2, 95% CI: 2.0-455.5) and spending the daytime at Arrondissement 4 (aOR = 11.5, 95% CI: 1.0-131.0). After adjustment, symptomatic dengue was associated with living less than 50 m away from cultivated land (aOR = 2.8, 95% CI: 1.1-6.9) and living less than 50 m from a stretch of water (aOR = 0.1, 95% CI: 0.0-0.6). CONCLUSIONS: The overall burden of dengue among populations not seeking care in hospitals was quite high, with few asymptomatic cases. Efforts to manage dengue cases should also target non-hospital cases and raise population awareness. The 2023 epidemic could be due to dengue virus (DENV)-3.

Generalized open-source workflows for atomistic molecular dynamics simulations of viral helicases.

Viral helicases are promising targets for the development of antiviral therapies. Given their vital function of unwinding double-stranded nucleic acids, inhibiting them blocks the viral replication cycle. Previous studies have elucidated key structural details of these helicases, including the location of substrate binding sites, flexible domains, and the discovery of potential inhibitors. Here we present a series of new Galaxy tools and workflows for performing and analyzing molecular dynamics simulations of viral helicases. We first validate them by demonstrating recapitulation of data from previous simulations of Zika (NS3) and SARS-CoV-2 (NSP13) helicases in apo and complex with inhibitors. We further demonstrate the utility and generalizability of these Galaxy workflows by applying them to new cases, proving their usefulness as a widely accessible method for exploring antiviral activity.

Incidence and co-infection with COVID-19 of dengue during the COVID-19 pandemic.

The co-infection of dengue and COVID-19 has been regarded as a public health issue for dengue-endemic countries during the COVID-19 pandemic. Travel restrictions might decrease the chance of mosquitoes biting and, thus, reduce the risk of dengue transmission. However, the spread of dengue was reported to increase with the policies of lockdowns and social distancing in specific areas due to delayed interventions in dengue transmission. Of cases experiencing dengue and COVID-19 co-infection, most recovered after receiving supportive care and/or steroid therapy. However, some episodes of severe or fatal diseases in specific individuals, such as pregnant women, have been reported, and the clinical course of this co-infection is unrecognized or unpredictable. Accordingly, it is crucial to promptly identify predictors of developing severe viral diseases among co-infection patients.

Deep learning guided prediction modeling of dengue virus evolving serotype.

Evolution remains an incessant process in viruses, allowing them to elude the host immune response and induce severe diseases, impacting the diagnostic and vaccine effectiveness. Emerging and re-emerging diseases are among the significant public health concerns globally. The revival of dengue is mainly due to the potential for naturally arising mutations to induce genotypic alterations in serotypes. These transformations could lead to future outbreaks, underscoring the significance of studying DENV evolution in endemic regions. Predicting the emerging Dengue Virus (DENV) genome is crucial as the virus disrupts host cells, leading to fatal outcomes. Deep learning has been applied to predict dengue fever cases; there has been relatively less emphasis on its significance in forecasting emerging DENV serotypes. While Recurrent Neural Networks (RNN) were initially designed for modeling temporal sequences, our proposed DL-DVE generative and classification model, trained on complete genome data of DENV, transcends traditional approaches by learning semantic relationships between nucleotides in a continuous vector space instead of representing the contextual meaning of nucleotide characters. Leveraging 2000 publicly available DENV complete genome sequences, our Long Short-Term Memory (LSTM) based generative and Feedforward Neural Network (FNN) based classification DL-DVE model showcases proficiency in learning intricate patterns and generating sequences for emerging serotype of DENV. The generated sequences were analyzed along with available DENV serotype sequences to find conserved motifs in the genome through MEME Suite (version 5.5.5). The generative model showed an accuracy of 93 %, and the classification model provided insight into the specific serotype label, corroborated by BLAST search verification. Evaluation metrics such as ROC-AUC value 0.818, accuracy, precision, recall and F1 score, all to be around 99.00 %, demonstrating the classification model's reliability. Our model classified the generated sequences as DENV-4, exhibiting 65.99 % similarity to DENV-4 and around 63-65 % similarity with other serotypes, indicating notable distinction from other serotypes. Moreover, the intra-serotype divergence of sequences with a minimum of 90 % similarity underscored their uniqueness.

Discovery of azaleatin as a potential allosteric inhibitor for dengue NS2B-NS3 protease using in vitro and in silico studies.

The rise in dengue cases in tropical and sub-tropical areas has become a significant health concern. At present, there is no definitive cure for dengue fever, which underscores the importance of identifying potent inhibitors. Dengue NS2B-NS3 protease is the prime drug target due to its vital function for replication. Quercetin, a flavone, has anti-dengue virus properties but is limited by low bioavailability. Previous studies have shown that methoxy substitution in flavones improves bioavailability and metabolic stability. Azaleatin is a derivative of quercetin with a methoxy substitution at the C5 position, however its ability to inhibit dengue is unknown. In this study, azaleatin was investigated for its inhibition against dengue NS2B-NS3 protease using in vitro and in silico techniques. The fluorescence assay was used to determine the IC50 value and inhibition kinetics. The molecular interaction between azaleatin and NS2B-NS3 was studied using CB-Dock2 and AutoDock Vina. The complex's stability was then analysed using GROMACS. Besides, the ADMETlab 2.0 was utilized to predict pharmacokinetic of the azaleatin. Results showed that azaleatin inhibits dengue NS2B-NS3 protease non-competitively with a Ki of 26.82 µg/ml and an IC50 of 38 µg/ml. Molecular docking indicated binding of the azaleatin to the allosteric pocket of NS2B-NS3 with a docking score of -8.2 kcal/mol. Azaleatin was found stable in the pocket along 100 ns, supporting its inhibitory mode. The compound has favourable pharmacokinetic profiles and conformed to Lipinski's Rule of Five. Taken together, azaleatin inhibits NS2B-NS3 protease in a non-competitive mode, suggesting its potential as safer anti-dengue compound.Communicated by Ramaswamy H. Sarma.

An Intriguing Case of Expanded Dengue Syndrome With Co-existing Encephalitis, Pancreatitis, and Hepatitis: The Classic Thalamic "Double-Doughnut" Sign Revisited.

Background: Dengue neuro-infection can present with symptoms ranging from mild to severe. Atypical presentations, such as expanded dengue syndrome, pose diagnostic and therapeutic challenges. Neuroimaging findings, particularly the "double-doughnut" sign on brain magnetic resonance imaging (MRI), have emerged as one of the most valuable aids in diagnosing complex cases of central nervous system infection by dengue virus. Case Presentation: We report the case of a 35-year-old female from rural West Bengal, India, with expanded dengue syndrome. The patient presented with fever, headaches, body aches, and sudden disorientation over minutes, which progressed to a coma. Neurological examination revealed profound unconsciousness and nuchal rigidity. Laboratory findings were consistent with dengue infection, including altered liver and pancreatic enzyme levels. The diagnosis was facilitated by identifying the "double-doughnut" sign on the brain MRI, which suggested dengue encephalitis. This finding and clinical and serological evidence guided the treatment strategy. Discussion: The "double-doughnut" sign, though not exclusive to dengue encephalitis, proved crucial in this case, aiding in differentiating from other causes of encephalitis. Recognition of this sign can be pivotal in diagnosing expanded dengue syndrome, facilitating timely and appropriate intervention, and improving patient outcomes. This case also underscores the importance of considering dengue in the differential diagnosis of encephalitis, especially in endemic areas. Also, this case's excellent outcome (both clinically and radiologically) was noteworthy.

Repurposing of therapeutic antibodies against dengue virus envelope protein receptor binding domain.

Dengue virus (DENV) is the leading cause of numerous deaths every year due to its high infectivity. In this study we have tried to target the DENV envelope protein receptor binding domain, the region crucial for binding to host receptors which leads to membrane fusion and entry of the viral genome into the human host cell. We have taken 13 known FDA approved antiviral therapeutic antibodies from therapeutic antibody database and tried to repurpose them against the DENV envelope protein. Based on the humanness analysis, 10 antibodies were selected against the DENV envelope protein. Computational affinity maturation of the 10 selected antibodies was performed to increase their binding affinity and specificity against the DENV envelope protein which ultimately led to 8 mutant antibodies having better binding affinity than the native ones. Molecular Dynamics (MD) simulation shows that, the stability of the complexes involving both the native and mutant antibodies were found to be the same although the binding energy between the protein and the respective antibodies was seen to improve upon computational affinity maturation. Contact analyses show similar robustness of the interaction for both the mutant and native antibodies during complex formation with the DENV envelope protein. This has led to the selection of total 18 antibodies including 10 natural and 8 affinity matured mutants which have a high probability of interacting with the DENV envelope protein. Finally, based on all these analyses along with heated MD simulation, Bamlanivimab, Etesivimab and Tixagevimab with a mutation of residue 100 of the heavy chain from serine to tyrosine were selected as prospective therapeutic antibodies to combat DENV infection. This study may open a new avenue in designing therapeutics to combat Dengue viral infection.

Dengue Fever Accompanied by Neurological Manifestations: Challenges and Treatment.

Dengue, commonly referred to as 'breakbone fever,' is a mosquito-borne arboviral infection transmitted by Aedes aegypti, featuring an average incubation period of approximately seven days. Key cytokines such as interferon-gamma (IFN-γ), tumor necrosis factor (TNF)-α, and interleukin (IL)-10 are pivotal in the pathogenesis of dengue. Travelers are particularly susceptible to contracting dengue fever, with disease severity often associated with CD8+ T cell response. Without proper hospitalization during severe cases like dengue hemorrhagic fever (DHF)/dengue shock syndrome (DSS), mortality rates can escalate to 50%. Dengue fever can lead to various complications, including neurological manifestations such as encephalopathy, encephalitis, cerebral venous thrombosis, myelitis, posterior reversible encephalopathy syndrome, strokes (both ischemic and hemorrhagic), immune-mediated neurological syndromes (such as mononeuropathy, acute transverse myelitis, Guillain-Barre syndrome, and acute disseminated encephalomyelitis), and neuromuscular complications. Treatment protocols typically involve assessing disease activity using composite indices, pursuing treatment objectives, and administering intravenous fluids according to symptomatology. Given the absence of specific antiviral treatment for dengue, supportive care, particularly hydration, remains paramount during the early stages. It is crucial to recognize that dengue viruses may contribute to the development of neurological disorders, particularly in regions where dengue is endemic. Furthermore, there is a necessity for well-defined criteria for specific neurological complications. Primary prevention strategies primarily revolve around vector control measures, which play a critical role in curtailing the spread of dengue.