Search Results (761)

Dengue infection remains a major global health concern, with a subset of patients progressing from self-limited dengue fever to severe disease characterised by plasma leakage, shock, and organ dysfunction. The dengue non-structural protein 1 (NS1), a multifunctional glycoprotein expressed on infected cells and secreted into circulation, has emerged as a key mediator linking viral infection to immune-driven vascular pathology. This review synthesises experimental, animal, and human clinical evidence on NS1-driven immunopathogenesis, focusing on mechanisms leading to endothelial dysfunction and increased vascular permeability. NS1 modulates the complement system in a context-dependent manner, contributing to immune evasion by inhibiting terminal complement complex formation, while also promoting antibody-dependent complement activation associated with severe disease. Additionally, NS1 directly disrupts endothelial barrier integrity through disruption of adherens and tight junction architecture, Ang-2/Tie2 imbalance, activation of RhoA/ROCK (RhoA/Rho-associated coiled-coil-containing protein kinase) signalling, and enzymatic degradation of the endothelial glycocalyx, with further amplification through inflammatory mediators. In addition, evidence shows that NS1 activates innate immune signalling, perturbs platelet biology and haemostasis, and forms pro-inflammatory complexes with lipoproteins. Moreover, anti-NS1 antibodies may be both protective and pathogenic. Collectively, these data position NS1-linked pathways as rational targets for adjunctive therapies and next-generation vaccines aimed at preventing vascular leakage and severe dengue infection. Full article

Dengue fever, with a high proportion of asymptomatic infections, poses a major global public health challenge that traditional surveillance systems frequently underestimate. Wastewater-based epidemiology (WBE) has emerged as a promising approach to monitoring infectious diseases beyond enteric viruses. Dengue virus is shed in urine, feces, and saliva, providing a biological basis for wastewater detection alongside clinical surveillance. This systematic review and meta-analysis synthesize current evidence on dengue virus (DENV) detection in wastewater and evaluate methodological factors influencing detection success in WBE. A systematic literature search using selected databases and predetermined keywords, followed by eligibility screening, resulted in ten studies being included, covering community surveillance and experimental trials. DENV ribonucleic acids (RNA) were most consistently detected and enriched in wastewater solids, indicating this matrix as the most reliable for surveillance. Among concentration methods, ultrafiltration achieved the highest viral recovery efficiency, while reverse transcription digital polymerase chain reaction (RT-dPCR) demonstrated superior sensitivity and precision compared to those of reverse transcription quantitative polymerase chain reaction (RT-qPCR), particularly at low viral concentrations. Storage at −80 °C was critical for preserving RNA integrity. The meta-analysis yielded a pooled DENV positivity rate of 24% (95% CI: 20–28%) after exclusion of outliers. Overall, solid-phase analysis combined with RT-dPCR represents the most sensitive methodological approach across the included studies. Harmonized protocols are needed to support future translation of dengue WBE into community surveillance as current evidence mainly demonstrates methodological feasibility and provides a technical foundation for future public health integration. Therefore, further longitudinal and multi-site validation is required to establish its broader applicability for dengue surveillance. Full article

Dengue virus (DENV) and SARS-CoV-2 are emerging viral pathogens that share overlapping clinical features, including fever, fatigue, and respiratory symptoms, complicating differential diagnosis in endemic regions. Their co-circulation has increased the risk of co-infections, which may result in unpredictable disease progression, increased morbidity, and mortality. This overlap presents a significant challenge in managing outbreaks, as both viruses pose a major public health threat. Vaccines and direct-acting antivirals may be rendered ineffective by viral mutations, making it difficult to address evolving strains. Host-directed antivirals offer a promising alternative, potentially maintaining efficacy against a multitude of variants. Both DENV and SARS-CoV-2 rely on host proteases for viral maturation and entry, with furin playing a crucial role in viral glycoprotein cleavage. In DENV, furin cleaves the prM protein, facilitating virion maturation, while in SARS-CoV-2, the polybasic furin cleavage site in the spike protein enhances viral entry. This makes furin a compelling pan-viral target, where inhibiting furin could reduce viral fitness without relying on viral mutations. This review highlights the therapeutic rationale for targeting furin and discusses luteolin, a furin inhibitor showing antiviral activity against both viruses. Furin-targeted therapies may offer a durable antiviral strategy effective across DENV serotypes, SARS-CoV-2 variants, and co-infection settings. Full article

Endoplasmic reticulum (ER) stress and the unfolded protein response (UPR) represent fundamental cellular adaptive mechanisms that maintain protein homeostasis and metabolic balance. Many RNA viruses, particularly flaviviruses such as dengue virus (DENV), Zika virus (ZIKV), West Nile virus (WNV), yellow fever virus (YFV), and Japanese encephalitis virus (JEV), extensively remodel the ER to establish replication compartments and assemble progeny virions. This massive reorganization disrupts ER homeostasis, leading to UPR activation. Emerging evidence reveals that flaviviruses not only trigger but also manipulate the three UPR branches—PERK, IRE1, and ATF6—to optimize viral translation, replication, and egress. In parallel, flavivirus infection profoundly alters host lipid metabolism and promotes dynamic changes in lipid droplets (LDs), key organelles that mediate lipid storage and serve as scaffolds for viral replication and assembly. The UPR intimately connects to LD biogenesis through transcriptional and translational programs mediated by XBP1, ATF4, and ATF6, thereby coupling ER stress responses to lipid remodeling and energy homeostasis. This intricate crosstalk between UPR and LDs creates a metabolic and structural niche favorable for viral replication but detrimental to host cell integrity. This review provides a comprehensive analysis of the molecular mechanisms by which flaviviruses exploit ER stress and the UPR to reprogram lipid metabolism and LD dynamics. We highlight the dual role of UPR signaling in promoting adaptive lipid synthesis and initiating cell death under prolonged stress, discuss recent insights into ER–LD interactions during flavivirus infection, and explore therapeutic opportunities targeting UPR–lipid metabolic pathways as broad-spectrum antiviral strategies. Understanding this interconnected network will advance our knowledge of viral pathogenesis and identify new avenues for host-directed antiviral intervention. Full article

Background/Objectives: Febrile illness in returning travelers presents a diagnostic and operational challenge for emergency medicine clinicians as early symptoms of high-consequence tropical infections often overlap with common viral syndromes. This review synthesizes current evidence to guide frontline clinicians in the systematic evaluation, diagnosis, and management of internally acquired febrile illnesses with a focus on pathogen of greatest relevance to United States (US) emergency departments (ED). Methods: We conducted a narrative review of the literature addressing epidemiology, clinical presentation, diagnostic testing, and management strategies for key travel-associated infections. Special consideration was given to rapid diagnostic modalities, pediatric risk factors, and infections most frequently implicated in returning travelers, including chikungunya (CHIK), dengue virus (DENV) disease, Ebola virus (EBV) disease, malaria, Mpox, typhoid fever (TF), yellow fever (YF), and Zika virus (ZIKV) disease. Results: Effective evaluation begins with a detailed travel and exposure history, recognition of epidemiologic and clinical red flags, and targeted use of rapid diagnostic tests. Malaria remains the most common life-threatening cause of post-travel fever and the only pathogen with reliable Food and Drug Administration (FDA)-cleared rapid testing available in the ED. Arboviral infections such as DENV, CHIK, ZIKV, and YFrequire region-specific consideration and phase-appropriate molecular or serologic evaluation. Emerging and high-consequence pathogens, including Mpox and EBV, necessitate strict infection control measures and coordination with public health authorities. Pediatric travelers, particularly those visiting friends and relatives, face disproportionate risk for severe systemic infections and often require broader diagnostic testing. Conclusions: A structured approach integrating travel history, focused examination, rapid diagnostics, and early recognition of high-risk features is essential to improving outcomes for febrile returning travelers. Strengthened vector control, enhanced vaccination uptake, and global surveillance are critical to reducing future disease burden. Full article

Background/Objectives: Since 2023, a significant increase in measles cases has been reported worldwide, and Italy has been among the most affected European countries. In this context, the integration of laboratory and epidemiological data enables timely case classification and helps distinguish between imported and indigenous cases, supporting disease control. However, most studies address only selected aspects of surveillance. Therefore, this study aimed to provide an integrated analysis of virological and epidemiological surveillance activities conducted between November 2023 and December 2025 by the Regional Reference Laboratory in the Emilia-Romagna Region (ERR). Methods: A total of 806 clinical samples (269 urine, 267 oral fluids—saliva or oropharyngeal swabs—and 270 sera) from 291 suspected measles cases were tested by molecular and/or serological methods, and MV genotyping was performed. Samples from discarded cases were also analysed for parvovirus B19 (B19V), human herpesvirus 6 (HHV-6), enterovirus (EV), and varicella zoster virus (VZV), chikungunya virus (CHIKV) and dengue virus (DENV). Results: Of 291 suspected cases, 176 (60.5%) were confirmed. Median age was 33 years, with 46% in the 15–39 year group. Vaccination status was available for 165: 90.3% were unvaccinated, 5.4% had one dose, and 4.2% had two doses. Notably, over half of confirmed cases occurred in areas with vaccine-hesitant communities. MV strain characterisation was performed in 99.4% of MV-RNA positive cases, with 84.3% genotype D8 and 15.6% genotype B3; 83% of strains were of indigenous origin, suggesting an ongoing endemic circulation. Clinical data showed complications in 19.3%, mainly pneumonia and diarrhoea. Additionally, differential diagnosis enabled the identification of the etiological agent in 37.5% of measles/rubella discarded cases, and 37.6% (29/77) tested positive for B19V. Conclusions: The study results highlight that effective measles surveillance must be supported by integrating timely virological diagnosis, molecular and epidemiological investigations, and differential diagnosis, to achieve the WHO goals of eliminating measles transmission. Full article

Dengue fever (DF) is an acute mosquito-borne infectious disease caused by dengue virus (DENV), primarily transmitted by Aedes aegypti and Aedes albopictus. Nearly 4 billion people worldwide are at risk of infection, and the 2024 epidemic reached an unprecedented scale. Severe cases can lead to hemorrhage, shock, and even death, prompting the WHO to classify it as a potential pandemic pathogen. Current prevention and control measures face prominent bottlenecks, including limited applicable populations for vaccines, lack of specific antiviral drugs, and increasing insecticide resistance in mosquito vectors. Notably, susceptible animal models serve as core tools for elucidating the pathogenic mechanisms of dengue virus, screening antiviral drugs, and evaluating vaccine protective efficacy, holding irreplaceable significance. This review systematically summarizes the characteristics, application scenarios, and research progress of mainstream and potential susceptible animal models, including non-human primates, mice, pigs, tree shrews, and bats. It covers model systems with different immune statuses, genetically modified types, and species-specific traits. Among these, mouse models are the most widely used due to their high flexibility and controllable cost, while non-human primate models have become key carriers for preclinical vaccine evaluation by virtue of their high homology with human immune responses. However, current models generally suffer from core bottlenecks, such as incomplete simulation of core severe phenotypes, insufficient restoration of immune mechanisms, unclear viral receptor mechanisms, and lack of unified standards for inoculation doses and evaluation indicators. These limitations make it difficult to accurately replicate key severe disease mechanisms, including antibody-dependent enhancement (ADE) and cytokine storms. Future model development should focus on core requirements—including intact immunity, broad-spectrum susceptibility, and accurate simulation of clinical pathological features—prioritize solving the simulation challenges of ADE and cytokine storms, and establish standardized experimental systems and evaluation criteria. By comprehensively summarizing the advantages and limitations of the existing models, this review provides a systematic reference for the optimization and upgrading of dengue virus-susceptible animal models. It also holds important guiding significance for promoting the in-depth development of basic dengue research, innovation in prevention and control technologies, and clinical transformation and application. Full article

Aedes aegypti is a primary vector for globally significant arboviruses such as dengue virus (DENV). The mosquito’s metavirome, particularly its insect-specific virus (ISV) component, is recognized as a key modulator of arboviral transmission. However, the natural ecology of these interactions in populations remains poorly understood. This study presents the first comparative analysis of the metavirome in wild-caught A. aegypti from Vietnam based on natural DENV infection status. Metaviromic analysis was performed on 69 DENV-positive pools from six central provinces. The results obtained were compared with previously obtained metaviromic data from 7 DENV-negative pools (from the same region). Analysis suggests the presence of a stable ‘core metavirome’ of 11 ISVs present in both groups. Interestingly, six ISVs were detected only in DENV-negative mosquitoes, which may suggest potential antagonistic interactions requiring further investigation. Conversely, five ISVs were found only in DENV-positive pools, including Aedes partiti-like virus 1 and Aedes anphevirus. The latter may suggest possible synergistic relationships that facilitate arboviral replication. Phylogenetic analysis of prevalent ISVs, such as Phasi Charoen-like phasivirus (PCLV) and Chaq-like virus, revealed patterns of both local circulation and genetic diversity. The findings describe distinct ISV profiles associated with DENV infection in a natural setting, providing a data-driven foundation for hypothesizing specific virus–virus interactions. The data underscores the complexity of the mosquito metavirome. Here, we identified several candidate ISVs for future experimental studies aimed at understanding potential functional impact on arboviral vector competence. Full article

Dengue virus (DENV), an important mosquito-borne orthoflavivirus, represents a growing global threat due to its geographic expansion and recent outbreaks worldwide. In resource-limited endemic settings, the development of affordable diagnostic assays is needed. In this study, we developed and validated a colorimetric reverse transcription loop-mediated isothermal amplification assay (RT-LAMP) for the detection of DENV type 3 (DENV-3) using 95 previously diagnosed clinical samples from Southeastern Mexico. Primers targeting the 3′ untranslated region (3′ UTR) of DENV-3 were designed, and assay conditions were standardized. The colorimetric RT-LAMP DENV-3 system achieved a preliminary limit of detection of 1 × 10³ copies per reaction, with 90.7% sensitivity and 100% specificity. The colorimetric format enabled visual readout without specialized equipment, supporting its potential applicability in point-of-care and resource-limited settings. The developed colorimetric RT-LAMP detection for DENV-3 is intended as a rapid screening/triage tool that can trigger confirmatory testing or public-health actions. Full article

Background: Dengue virus (DENV) does not have any effective antiviral therapy. The Cinnamomum verum has cinnamic acid and oleic acid that could inhibit important viral proteins. Aim: To compare their inhibitory capacity with the key DENV proteins through molecular docking, molecular dynamics and in silico ADMET. Methods: Phytochemical profiling of the ethanolic extract of the bark was done by GCMS. AutoDock Vina (version 1.2.0) was used to dock cinnamic acid and oleic acid to key proteins of DENV (NS5, NS3, and envelope) in the presence of ribavirin as the reference. The best complexes were then subjected to 50 ns of molecular dynamics simulation and stability measured by RMSD, RMSF, Rg, SASA, hydrogen bonding and RDF. Validated in silico tools were used to predict the ADMET properties. Results: Analysis of GC–MS revealed cinnamic acid (85.92%) and oleic acid (5.33%). The outcome of docking was that the cinnamic acid had the greatest affinity with NS5 (−5.970 kcal/mol) and the capsid protein (−5.755 kcal/mol), and oleic acid showed the highest affinity with the capsid (−6.150 kcal/mol) and then with NS5 (−5.209 kcal/mol). Both ligands had a relatively weak interaction with NS3. Simulation of the molecular dynamics showed the stability of the top complexes, especially the cinnamic acid–NS5 complex, that retained low RMSD (1.6–1.9 A), stable Rg and SASA profiles, and continued hydrogen bonding during the 50 ns period. The use of cinnamic acid in ADMET projections was more preferable, as it was more soluble, orally bioavailable (0.91), and drug-like (QED 0.65), but oleic acid revealed higher lipophilicity and lower drug-like properties (QED 0.29). Conclusions: Cinnamic acid showed specificity towards the NS5 proteins with the help of stable dynamics and good predicted pharmacokinetics, which are features that make it a promising multi-target anti-DENV scaffold. Oleic acid exhibited poor affinity and poor pharmacokinetic properties. The findings are predictive and must be validated using biochemical, cellular, and toxicological means to prove the antiviral efficacy and safety. Full article

Dengue virus (DENV) is a mosquito-borne RNA virus that causes serious illness in humans, ranging from mild fever to severe clinical manifestations, with dengue virus type 2 (DENV-2) being the most virulent among its four serotypes. Despite extensive research, no specific antiviral therapy is currently available, making the host-directed method an appealing therapeutic approach. Evidence shows that DENV manipulates host kinase-driven phosphorylation pathways to control viral pathogenesis. Using the kinase–substrate phosphomotif approach, we predicted phosphorylation sites across the DENV proteome and their potential human kinases. The predicted kinase–substrate interactions were systematically integrated with DENV-2-induced human phosphoproteome datasets, protein–protein interactions, and experimentally-validated viral phosphosites. The therapeutic relevance of the identified host kinases was corroborated by the impact of their inhibitors on DENV-2 infection. Among the 359 potential human kinases predicted to phosphorylate DENV-2 proteins, based on human phosphoproteome and kinase–viral protein interaction analyses, CDK9 emerged as a central hub kinase. Molecular docking analyses further revealed that the host kinases CDK9, EEF2K, HASPIN, and TNNI3K form stable interactions with the viral capsid and NS5 proteins. Additionally, a conservation analysis suggested that the predicted phosphorylation sites are evolutionarily conserved across DENV-2 strains. Computational prediction tools supported the predicted kinase–substrate interactions, underscoring the role of host kinases as key regulators of DENV infection, which may act as potential therapeutic targets. This study highlights the interplay between dengue viral and host proteins, providing insights into host-directed therapeutic strategies for DENV-2 infection and their potential to address the current lack of effective antiviral interventions. Full article

Dengue is a mosquito-borne viral disease which is predominantly endemic in tropical and subtropical countries. In Bangladesh, 321,179 dengue cases were reported in 2023, followed by 101,214 cases in 2024, which highlights a severe and ongoing public health challenge. Dengue transmission risks are shaped by climatic variability, rapid urbanization, socio-economic vulnerability, and healthcare strain. But existing dengue surveillance models remain limited in their ability to capture district-level disparities in Bangladesh. This study aimed to develop a district-level dengue early warning system that integrates climatic, socio-demographic, economic, healthcare, and environmental determinants to generate accurate and interpretable predictions. We examined dengue cases across all 64 districts in Bangladesh from 2017 to 2024, integrating Directorate General of Health Services (DGHS) case records with climate, socio-demographic, economic, and healthcare indicators. Machine learning and deep learning approaches, including Multi-Layer Perceptron (MLP) and Convolutional Long Short-Term Memory (ConvLSTM), were combined with SHAP (Shapley Additive Explanations)-based explainable artificial intelligence. We also used Bayesian spatio-temporal models to capture spatial clustering, temporal dependence, and the lagged transmission effects of dengue. Dengue outbreaks peaked in September 2023, with Dhaka recording 113,233 cases. DENV-4 (Dengue Virus type 4) emerged in 2022, accounting for 27% of infections in 2023. Climate was the strongest predictor of dengue transmission (humidity SHAP = 0.314; minimum temperature SHAP = 0.146; rainfall RR = 1.303). Poverty (SHAP = 0.193) and healthcare capacity (nursing/midwifery density SHAP = 0.073) mostly contributed to dengue prediction. The MLP model achieved the best yearly performance (accuracy = 0.93; ROC-AUC = 0.99), ConvLSTM was the best model in monthly prediction (recall = 0.88; ROC-AUC = 0.81), and Bayesian BYM2_RW2 with lagged effects improved predictive fit (DIC = 3671.055). Our integrated framework delivers transparent, interpretable predictions and district-level early warnings, supporting adaptive dengue outbreak preparedness and resource allocation in Bangladesh. Full article

Dengue is the leading mosquito-borne viral cause of human illness and death. More than four billion people globally are at risk of dengue virus (DENV) infection, and most infections are asymptomatic or present with a non-specific febrile illness. We characterise the first complete DENV-2 genome from Sierra Leone, recovered from a febrile adult who tested RT-PCR–positive. The sequence was identified as DENV-2 genotype II, lineage F.1.1. Phylogenetically, the Sierra Leone genome formed a well-supported sister lineage with a 2024 USA DENV-2 genome; both were nested within but clearly diverged from Indian DENV-2 sequences (2021–2022) and were distinct from the Réunion DENV-2 clade. The degree of genetic divergence was incompatible with a recent or direct import of a South Asian lineage and was more consistent with diversification in an under-sampled Indian Ocean/South Asia network or outside this region in Africa. With a single Sierra Leone genome, the source and extent of local transmission remain unresolved. These findings underscore the benefits of integrating differential diagnostics and genomics into routine care for febrile illness and sustaining regional arboviral surveillance. Full article

During the 2024/2025 wet season, Townsville had its first sustained autochthonous outbreak of dengue disease caused by dengue virus type 2 (DENV-2), the second locally transmitted outbreak of dengue since 2014 following the introduction of wMel strain Wolbachia-infected mosquitoes, a control strategy for dengue virus (DENV) and other Aedes-transmitted arboviruses. In comparison to two recorded locally acquired cases of dengue in 2020, the 2024/2025 outbreak resulted in sixteen cases in two inner-city suburbs of Townsville during the wet season associated with higher-than-average rainfall. This second dengue outbreak since 2014 highlights that Townsville and other north Queensland communities where Wolbachia mosquito programs have been deployed remain vulnerable to DENV incursions and local disease outbreaks despite the apparent high coverage of Wolbachia-infected mosquitoes. Whilst these control strategies have likely contributed to a reduction in the number and frequency of autochthonous DENV outbreaks in north Queensland, ongoing maintenance and monitoring of Wolbachia-infected mosquito coverage is necessary, together with timely review and improvement in dengue awareness and prevention health promotion activities in the community. Full article

Dengue virus (DENV) serotyping is essential for epidemiological surveillance, clinical risk assessment, and vaccine evaluation, as the four dengue serotypes differ in pathogenicity, immune interactions, and population dynamics. Existing subtyping methods largely rely on sequence alignment and phylogenetic inference, which can be computationally intensive and unreliable for short, fragmented, or error-prone sequences commonly generated in diagnostic and surveillance settings. There is a need for fast, alignment-free serotyping approaches that maintain high accuracy across heterogeneous sequence lengths while remaining scalable, transparent, and suitable for real-world diagnostic inputs. We demonstrate that compact 3-mer composition features are sufficient for highly accurate dengue virus serotyping when coupled with a lineage-aware Random Forest classification framework. Using 64 normalized 3-mer frequency features per sequence with ambiguity masking and enforcing strict cluster-aware validation at both 99% and 95% nucleotide identity thresholds, our approach achieved near-perfect accuracy and macro-F1 scores on held-out internal test sets. To further ensure independence, external validation datasets were filtered to remove exact sequence matches and any sequences sharing ≥99% or ≥95% nucleotide identity with internal data. On these strictly independent external datasets, the model maintained 100% accuracy and macro-F1 performance, confirming robust generalization beyond database redundancy. Robustness analyses showed stable performance under contiguous sequence truncation down to 300 bp and in the presence of ambiguous nucleotides, indicating resilience to realistic diagnostic inputs. These results demonstrate that a lightweight, alignment-free, machine learning approach can rival alignment-dependent methods while maintaining strict lineage-aware evaluation controls. The proposed framework combines high predictive accuracy, probabilistic reliability, computational efficiency, and reproducible validation design, making it well suited for large-scale genomic surveillance, rapid pre-screening, and diagnostic decision-support applications. Full article