Dengue fever is a major public health problem in several countries, including Thailand. The development of an effective dengue vaccine against all four serotypes is important for controlling the disease. An attenuated dengue-3 vaccine candidate, namely, DENV3-MBU-1, was derived from full-length cDNA-assembled segments based on the sequence of a prototype DENV3 vaccine candidate originating from the DENV3 strain 16562, which was passaged 30 times in primary green monkey kidney cells and four times in primary dog kidney cells. Compared to the parental DENV3-16562 sequence, this DENV3-MBU-1 contains seven nonsynonymous mutations in the premembrane (prM), envelope (E), and nonstructural proteins (NS2A, NS3, NS4). In this study, we aimed to characterize the mutations contributing to attenuation by generating different DENV3 mutants and evaluating their properties, including plaque formation and neurovirulence in mice. The DENV3-MBU-1 mutants, in which the NS proteins were reverted to those of the parental virus, exhibited an altered phenotype, manifested by changes in plaque size and virulence, resembling that of the parental virus. This suggests the important role of the NS segment in attenuation. Interestingly, the mutants of DENV3-MBU-1, in which only the structural proteins, but not the NS proteins were altered, showed changes in phenotype toward increased plaque size and neurovirulence. This suggests that attenuation may be influenced by specific combinations of mutations rather than single-point mutations. These findings, along with the attenuated DENV3 viruses generated, provide useful information for the development of a dengue vaccine.

The present study was undertaken with the objective of performing comparative sequence analysis of the envelope (E) gene of Kyasanur forest disease virus (KFDV) vaccine strain P9605 with the circulating field strains. The study was taken up as the currently used KFDV vaccine strain, KFDV P9605, was isolated in the 1960s. For this study, we designed two sets of primers targeting the complete amplification of the E gene of KFDV. The sequencing was performed by the Sanger method, and the deduced sequence of the vaccine virus was deposited in GenBank with accession number PX067005. This sequence obtained for the vaccine virus was aligned and compared with sequences of GenBank-deposited circulating field strains. We also performed comparative sequence analysis of the Kyasanur forest disease (KFD) vaccine seed virus having passaged twice in mouse brain with the vaccine seed virus passaged six times in mouse brain to investigate whether multiple passages in mouse brain will lead to genetic mutation in the immunologically important E gene. The phylogenetic analysis revealed seven amino acid mutations in the field strains at positions A123T, S158N, D178E, D239N, A313S, M429I, and G479A when compared with the vaccine strain. We did not find any mutations at the critical fusogenic segment (residues 98-113) in the E gene of currently circulating field strains compared to the vaccine seed virus. The study found no genetic variations in the E gene of the KFD virus passed two times and passed six times in mouse brain. We performed SWISS-MODEL homology modeling, AlphaFold protein analysis, and Ramachandran plot analysis to study the E protein structures and stability. The observations made in this study suggest slow evolutionary drift and conserved structural stability of the envelope gene of KFDV ever since its emergence 7 decades ago; however, the functional implications of these amino acid substitutions need further studies on their roles in viral infectivity, transmission, and impact on immunity.

Coinfection of hepatitis B virus and hepatitis C virus presents great difficulty in treatment procedures, especially in terms of prediction of the response to the direct-acting antiviral therapy. In view of this, developing adequate prediction models would play a vital role in ensuring better personalization and effectiveness in terms of treatment. The objective of this paper is to develop and validate prediction models for the identification of patients' responses to direct-acting antiviral therapy in chronic HBV/HCV coinfected patients following treatment completion. This retrospective clinical prediction study involved the use of medical records of 154 patients with HBV/HCV coinfection treated with the help of direct-acting antiviral therapy in Holy Family Hospital, Rawalpindi, Pakistan. Sixteen predictors were used to develop logistic regression models to predict treatment responses at 4 and 12 weeks. In addition, to counter the problems of class imbalance, the synthetic minority oversampling technique was applied to the datasets, while nested stratified cross-validation was used for hyperparameter tuning and model validation. Performance was evaluated through different performance metrics such as ROC-AUC, accuracy, precision, recall, and F1-score. The performance of the two models was very good at each endpoint. For the endpoint of 4 weeks, the ROC-AUC score was 0.858 (95% CI 0.746-0.942), the accuracy was 0.760, and the F1-score was 0.851. In the case of the 12-week endpoint, the ROC-AUC score was 0.850 (95% CI 0.769-0.916), the accuracy was 0.786, and the F1-score was 0.856. The important predictors were HCV genotypes, age, body mass index, hemoglobin, and liver function test results. Good model calibration was evident from the calibration graphs, which showed slight deviation from the ideal calibration line at both endpoints. The current study developed prediction models for treatment response in HBV/HCV coinfected patients based on clinical and laboratory information from baseline. The models showed very good internal validity, but the 12-week model performed slightly better than the 4-week model in terms of classification balance. Such models represent useful tools for decision-making in case of a personalized approach.

Several viruses belonging to the order Mononegavirales are recognized as highly pathogenic in humans and are often associated with lethal disease outcomes. Prominent examples include human respiratory syncytial virus (HRSV), Ebola virus (EBOV), rabies virus (RABV), and Marburg virus (MARV). In addition to their clinical severity, these viruses are considered potential biological threats due to their high transmissibility and virulence. In this study, we performed a metatranscriptomic analysis of Culex and Anopheles mosquitoes collected at the DBB (Diretoria de Biodiversidade e Biotecnologia), São Paulo, Brazil. Our analysis revealed viral sequences associated with two families within Mononegavirales: Lispiviridae and Rhabdoviridae. Phylogenetic analysis of the Lispiviridae sequences identified six variants, designated CxLispV-SP_03, CxLispV-SP_09, CxLispV-SP_12, CxLispV-SP_13, CxLispV-SP_14, and CxLispV-SP_15, that formed a strongly supported monophyletic clade with Canya virus, suggesting the discovery of a putative novel viral lineage. Examination of RNA-dependent RNA polymerase (RdRp) domains in these sequences confirmed the presence of essential catalytic motifs. In contrast, the detected rhabdoviruses exhibited greater genomic structural heterogeneity, including the presence of accessory protein domains. Pairwise comparisons based on RdRp amino acid identity delineated four distinct groups among these sequences, pointing to substantial evolutionary divergence within the sampled rhabdovirus diversity. Together, these findings contribute to the growing characterization of mosquito-associated mononegaviruses and provide a genomic foundation to support future surveillance efforts and public health risk assessments related to vector-borne viruses.

This study presents a new molecular epidemiology dataset on the prevalence of selected viral pathogens, including Feline panleukopenia virus (FPV), feline calicivirus (FCV), and feline coronavirus (FCoV) (systemic feline infectious peritonitis [FIP]), in domestic cats in Sulaymaniyah, Kurdistan region, Iraq. From October 2024 to January 2025, a total of 145 clinically suspected cats aged 2-24 months presented to private veterinary hospitals were analyzed using quantitative PCR (qPCR) and reverse transcription qPCR (RT-qPCR) on blood, feces, oral swabs, and abdominal effusion. Our findings revealed that 86/145 (59.3%) cats were positive for at least one virus: FCoV (including FIP) was detected in 13/25 (52%) samples, FPV in 63/102 (61.8%), and FCV in 10/20 (50%). All categorical comparisons are presented with explicit numerical values (n and %), improving interpretability. Most positive cases were reported among younger cats (2-12 months). Additionally, infection prevalence was higher in nonvaccinated (25.9%) and stray cats (22.5%) compared with vaccinated cats (15.0%). Vaccination status was recorded; however, detailed vaccine type and schedule were not consistently available. These findings suggest a strong association between vaccination status and infection risk, underscoring the importance of immunization programs. This study establishes the first molecular baseline for feline viral infections in Sulaymaniyah and supports the development of targeted surveillance, vaccination strategies, and improved veterinary public health interventions in the region.

Marek's disease (MD) is a highly contagious neoplastic disorder of poultry caused by MD virus (MDV; gallid alphaherpesvirus 2 [GaAHV2]). Infection results in profound immunosuppression, neurological dysfunction, and the development of malignant T-cell lymphomas. Continued viral evolution has produced increasingly virulent strains capable of partially or fully evading current vaccines, leaving few options for controlling emerging variants. This highlights the importance of identifying new antiviral targets, particularly those involved in the nuclear trafficking events essential for GaAHV2 replication. The UL36 large tegument protein of alphaherpesviruses contains N-terminal nuclear localization signals (NLSs) thought to guide capsid transport to the nuclear pore complex. However, the specific mechanism by which GaAHV2 UL36 engages the host nuclear import machinery remains unclear. In this work, we defined the NLS within the N-terminal region of GaAHV2 UL36 and characterized its interaction with importin proteins. Through high-resolution crystallography and quantitative binding assays, we pinpointed the residues and structural motifs within UL36 that mediate recognition by importin-α (IMPα) and compared their affinities across different IMPα isoforms. Our structural and biochemical data show that the predicted N-terminal NLS of GaAHV2 UL36 is essential for IMPα binding. These findings provide a detailed molecular framework for host-virus interactions during GaAHV2 nuclear entry and offer potential avenues for the development of targeted antiviral strategies.

Kenya, a country with a significant number of human immunodeficiency virus type 1 (HIV-1) infected individuals, has adopted the World Health Organization's (WHO's) "test and treat all" strategy to reduce HIV-related deaths and new infections, aligning with the United Nations' Acquired Immune Deficiency Syndrome (UNAIDS) 95-95-95 targets. In 2019, Kenya adopted the WHO's first-line antiretroviral Therapy (ART) recommendations, which include tenofovir/lamivudine/dolutegravir (TDF + 3TC + DTG) as a cost-effective regimen. Despite these efforts, new HIV infections and AIDS-related mortality continue in developing countries. This cross-sectional study investigated HIV-1 drug resistance mutations and subtypes among patients receiving ART in Nairobi County, Kenya. The study enrolled 227 HIV-1-infected patients for 12 months, with 42 out of the total 227 samples successfully amplified by polymerase chain reaction (PCR). HIV-1 genotypic drug resistance was determined using an in-house sequencing method. Sociodemographic data were analyzed using descriptive statistics to summarize and describe the key characteristics of the dataset. The Stanford University HIV Drug Resistance algorithm was used to analyze drug resistance mutations, and phylogenetic analysis with MEGA 11 software assessed HIV-1 genetic diversity. The study identified key HIV-1 drug resistance mutations, including M184V (13.73%), K103N (9.8%), Y181C (4.9%), T215Y (4.9%), and D67N (4.9%). Phylogenetic analysis of the 42 sequences generated from the study demonstrated significant genetic diversity, with Subtype A being the most dominant at 69%, followed by Subtype D (23.8%), Subtype C (4.8%), and CRF10_CD (2.4%). This study provides crucial insights into the distribution of HIV-1 genotypes and the incidence of drug-resistance mutations among HIV-1 patients in Nairobi. These findings provide critical insights to guide policymakers and healthcare providers in optimizing the management and treatment of HIV-1 patients undergoing ART.

[This retracts the article DOI: 10.1155/2015/675921.].

Common bean (Phaseolus vulgaris L) is Kenya's second most important agricultural product after maize, serving as a vital source of protein for many rural families in Western Kenya. However, viral diseases caused by RNA and DNA viruses greatly impair bean productivity, often leading to yield losses of up to 100%, thus contributing to food insecurity. Global research has isolated 168 viruses of plants that have detrimental effects on common beans; however, no extensive profiling of these viruses has been done in Western Kenya. The scope of this study was to delineate the whole virome that infects common beans through a comprehensive disease diagnostic survey. Sixty-one diseased samples were collected, and nucleic acids were extracted using standard extraction protocols (DNA &RNA Qiagen) and sequenced on the Illumina platform. Metagenomic analysis revealed several DNA-based viruses, such as Badnavirus spp, Caulimovirus maculatractylodei, Pandanus badnavirus, Okra enation leaf curl virus, and Paper mulberry vein-banding virus, while metatranscriptomic analysis uncovered viruses like Tomato leaf curl Cameroon alphasatellite, Physalis Rugose Mosaic Virus, Citrus endogenous paretrovirus, Natevirus nate, and Bracoviriform facetosae. To the best of our knowledge, this study provides a comprehensive inventory of viral entities associated with common beans not documented in Africa. This information is essential for defining plant defense mechanisms, guiding crop protection strategies, lowering agriculture-related risks, strengthening resistance, and advancing resilience.