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Longitudinally extensive transverse myelitis is a rare neurological manifestation caused by dengue infection. Here, we describe the uncommon presentation of a 24-year-old male with fever and maculopapular rash followed by flaccid quadriparesis with acute urinary retention. Magnetic resonance imaging of the whole spine with contrast revealed a long-segment ill-defined hyperintense signal noted in the cord. The patient was managed conservatively with intravenous steroids and later intravenous immunoglobulins. The patient is on regular follow-up and doing well. Currently, the patient is on tablet prednisolone with a tapering dose.

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UNASSIGNED: Dengue fever is rapidly becoming Malaysia\'s most pressing health concern, as the reported cases have nearly doubled over the past decade. Without efficacious antiviral medications, vector control remains the primary strategy for battling dengue, while the recently introduced tetravalent immunization is being evaluated. The most significant and dangerous risk increasing recently is vector-borne illnesses. These illnesses induce significant human sickness and are transmitted by blood-feeding arthropods such as fleas, parasites, and mosquitos. A thorough grasp of various factors is necessary to improve prediction accuracy and typically generate inaccurate and unstable predictions, as well as machine learning (ML) models, weather-driven mechanisms, and numerical time series.
UNASSIGNED: In this research, we propose a novel method for forecasting vector-borne disease risk using Radial Basis Function Networks (RBFNs) and the Darts Game Optimizer (DGO) algorithm.
UNASSIGNED: The proposed approach entails training the RBFNs with historical disease data and enhancing their parameters with the DGO algorithm. To prepare the RBFNs, we used a massive dataset of vector-borne disease incidences, climate variables, and geographical data. The DGO algorithm proficiently searches the RBFN parameter space, fine-tuning the model\'s architecture to increase forecast accuracy.
UNASSIGNED: RBFN-DGO provides a potential method for predicting vector-borne disease risk. This study advances predictive demonstrating in public health by shedding light on effectively controlling vector-borne diseases to protect human populations. We conducted extensive testing to evaluate the performance of the proposed method to standard optimization methods and alternative forecasting methods.
UNASSIGNED: According to the findings, the RBFN-DGO model beats others in terms of accuracy and robustness in predicting the likelihood of vector-borne illness occurrences.

BACKGROUND: Dengue fever continues to pose significant health challenges globally, with recent outbreaks in Bihar, India, prompting a search for effective therapeutic interventions. This study assesses the effectiveness of Montelukast, traditionally used for asthma, in mitigating the severity of dengue fever symptoms and its progression to dengue shock syndrome (DSS).
OBJECTIVE: To evaluate the impact of Montelukast on the prevalence of dengue warning signs and the incidence of DSS in adult patients.
METHODS: A prospective observational study was conducted at the Indira Gandhi Institute of Medical Sciences (IGIMS), Patna, India, from August 2022 to October 2023, enrolling 500 patients diagnosed with dengue fever. Participants were divided into two groups. About 250 were treated with Montelukast and 250 received standard care. Outcomes measured included the incidence of warning signs, DSS, length of hospital stay, and 30-day mortality.
RESULTS: The Montelukast group exhibited a 24% lower prevalence of dengue warning signs compared to the control group, with 90 out of 250 patients (36%) in the Montelukast group versus 150 out of 250 patients (60%) in the control group (p < 0.001). The incidence of DSS was significantly reduced in the Montelukast group, with 4 out of 250 patients (1.6%) compared to 21 out of 250 patients (8.4%) in the control group (odds ratio: 0.178, p < 0.001). Furthermore, Montelukast users experienced shorter hospital stays (average 4.52 days vs. 6.54 days, T-statistic: -7.59, p = 1.58×10-13) and a reduced 30-day mortality rate, with 5 out of 250 patients (2%) in the Montelukast group versus 12 out of 250 patients (5%) in the control group (p < 0.03).
CONCLUSIONS: Montelukast significantly lowers the incidence of dengue warning signs and DSS, shortens hospital stays, and decreases mortality rates among dengue patients, supporting its potential integration into existing dengue treatment protocols. This study highlights the need for further clinical trials to confirm these findings and fully understand the therapeutic mechanisms of Montelukast in dengue management.

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.

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.

Dengue fever is a viral illness, mainly transmitted by Aedes aegypti and Aedes albopictus. With climate change and urbanisation, more urbanised areas are becoming suitable for the survival and reproduction of dengue vector, consequently are becoming suitable for dengue transmission in China. Chongqing, a metropolis in southwestern China, has recently been hit by imported and local dengue fever, experiencing its first local outbreak in 2019. However, the genetic evolution dynamics of dengue viruses and the spatiotemporal patterns of imported and local dengue cases have not yet been elucidated. Hence, this study implemented phylogenetic analyses using genomic data of dengue viruses in 2019 and 2023 and a spatiotemporal analysis of dengue cases collected from 2013 to 2022. We sequenced a total of 15 nucleotide sequences of E genes. The dengue viruses formed separate clusters and were genetically related to those from Guangdong Province, China, and countries in Southeast Asia, including Laos, Thailand, Myanmar and Cambodia. Chongqing experienced a dengue outbreak in 2019 when 168 imported and 1,243 local cases were reported, mainly in September and October. Few cases were reported in 2013-2018, and only six were imported from 2020 to 2022 due to the COVID-19 lockdowns. Our findings suggest that dengue prevention in Chongqing should focus on domestic and overseas population mobility, especially in the Yubei and Wanzhou districts, where airports and railway stations are located, and the period between August and October when dengue outbreaks occur in endemic regions. Moreover, continuous vector monitoring should be implemented, especially during August-October, which would be useful for controlling the Aedes mosquitoes. This study is significant for defining Chongqing\'s appropriate dengue prevention and control strategies.

Dengue fever (DF) and tuberculosis (TB) present significant global health challenges, often with overlapping clinical features, especially when complicated by conditions like dengue encephalopathy. We present a case study involving an 84-year-old male with a complex medical history, encompassing pulmonary tuberculosis reactivation, who subsequently developed dengue encephalitis. This underscores the complexity of managing such cases in the geriatric population. Dengue encephalitis, once considered non-neurotropic, is increasingly recognized, necessitating consideration as a potential differential diagnosis in patients with neurological symptoms, particularly in endemic regions. Our patient exhibited typical DF symptoms alongside manifestations of encephalopathy. Concurrently, secondary TB reactivation was observed, emphasizing the intricate interplay between these diseases. Additionally, lower respiratory tract infection (LRTI) further complicated the clinical picture. Timely recognition and comprehensive management are crucial, as demonstrated in our case, where prompt reporting and conservative measures led to a favorable outcome.

Introduction Dengue fever, caused by the dengue virus transmitted by Aedes aegypti mosquitoes, is a significant public health concern globally. Its resurgence in recent years, particularly in low- and middle-income countries, has led to increased morbidity and mortality rates. Atypical manifestations, involving the cardiac, liver, gut, renal, blood, bone, nervous, and respiratory systems, in dengue, can complicate both diagnosis and management. This study aimed to investigate the incidence of lung manifestations in dengue-infected individuals and their correlation with patient outcomes. Background The prevalence of dengue fever has risen dramatically over the past two decades, with Asia bearing the brunt of the burden, particularly India. The pathophysiology of lung complications in dengue remains unclear but is thought to be related to capillary leak syndrome and thrombocytopenia. Studies suggest that respiratory symptoms may be associated with severe cases and increased mortality rates. Despite limited research in India, understanding lung manifestations in dengue is crucial for improving diagnostic accuracy and patient care. Methods A retrospective study was conducted at K.S. Hegde Hospital, a tertiary care facility located in Mangalore, India, involving patients aged 18 years and above diagnosed with dengue fever between January and December 2019. Data gathered comprised patient demographics, clinical symptoms, laboratory findings, imaging results including radiographs, computed tomography (CT) scans of the chest (if accessible), ultrasound examinations of the chest and abdomen, and 2D echocardiograms, as well as patient outcomes. Diagnosis of lung manifestation was established through clinical assessment, chest X-ray interpretation, and ultrasound of the chest. Statistical analysis was conducted using SPSS Statistics (version 20), with a significance set at p<0.05. Results Out of 255 dengue cases, 10.19% (n=26) exhibited pulmonary manifestations, with pleural effusion being the most common. Older age (>50 years) and comorbidities were associated with a higher incidence of lung involvement. Respiratory symptoms, such as breathlessness, were more prevalent in patients with pulmonary complications. Laboratory parameters indicated distinct profiles in patients with lung manifestations, including elevated total count, urea, bilirubin, and liver enzymes, and reduced platelet counts. Mortality rates were higher in patients with lung involvement, older age, and comorbidities. Discussion The study findings highlight the importance of recognizing respiratory symptoms in dengue fever, particularly in older patients and those with underlying health conditions. The association between pulmonary involvement and adverse outcomes underscores the need for early detection and appropriate management strategies. Future research should focus on elucidating the pathophysiology of lung complications in dengue and developing targeted interventions to improve patient outcomes. Conclusion Lung manifestations in dengue fever represent a significant clinical challenge and are associated with increased morbidity and mortality. Early recognition of respiratory symptoms, along with prompt diagnostic evaluation and appropriate management, is essential for improving patient prognosis. Further studies are warranted to deepen our understanding of lung involvement in dengue and optimize therapeutic approaches to mitigate its impact on patient outcomes.