Search

Introduction: Recent literature suggests that dual or multiple virus infections may affect disease severity. However, few studies have investigated the effect of co-infection with influenza A viruses., Objectives: To identify the association between influenza A and respiratory viruses co-infections with disease outcome., Methodology: Data for samples from North West England tested between January 2007 and June 2011 was analysed for patterns of co-infection between influenza A viruses and eight respiratory viruses. Risk of hospitalisation to ICU or general ward in single versus co-infections was assessed using logistic regression., Results: Of the 25,596 samples analysed for respiratory viruses 40·7% (10,501) were positive for any virus. Co-infections were detected in 4·7% (137/2879) of all patients with influenza A(H1N1)pdm09, and 7·3% (57/779) of those with other influenza A virus infections. Co-infection between seasonal influenza A viruses and influenza B virus was associated with a significant increase in the risk of admission to ICU/death (OR: 22·0, 95% CI: 2·21-219·8, P=0·008). Respiratory syncytial virus/influenza A (RSV/Flu A) co-infection also increased this risk but was not statistically significant. For influenza A(H1N1)pdm09, RSV and AdV co-infection increased risk of hospitalisation to general ward whereas Flu B increased risk of admission to ICU, but none of these were statistically significant., Conclusion: Co-infection is a significant predictor of disease outcome; combined treatment, introduction of an integrated vaccine for all respiratory viruses and development of multi-target rapid diagnostic tests is recommended. Integration of respiratory viruses' co-infections into public health reports could also contribute to the accumulation of evidence., (© 2012 John Wiley & Sons Ltd.)

Enterovirus (EV) is commonly associated with central nervous system (CNS) syndromes. Recently, gastroenteric viruses, including rotavirus (RVA), human astrovirus (HAstV), and norovirus (NoV), have also been associated with CNS neurological disorders. The aim of the present study was to investigate the presence of EV, RVA, HAst, and NoV associated to CNS infections with undiagnosed etiology in Northwest region of São Paulo State, Brazil, and to conduct the molecular characterization of the positive samples detected. A total of 288 cerebrospinal fluid samples collected from July to December 2017 were tested for EV and NoV by quantitative real-time polymerase chain reaction (RT-qPCR), HAstV by conventional RT-PCR, and RVA by enzyme-linked immunosorbent assay. Positive-EV samples were inoculated in cells lines, amplified by RT-PCR and sequenced. RVA, NoV, and HAstV were not detected. EV infection was detected in 5.5% (16/288), and five samples successful genotyped: echovirus 3 (E3) (1/5), coxsackie virus A6 (CVA6) (1/5), and coxsackie virus B4 (CVB4) (3/5). Meningitis was the main syndrome observed (12/16; 75%). CVA6, CVB4, and E3 were identified associated with aseptic meningitis. Reports of CVA6 associated with aseptic meningitis are rare, E3 had not been previously reported in Brazil, and epidemiological data on CVB4 in the country is virtually unknown. The present investigation illustrates the circulation of diverse EV types in a small regional sample set and in a short period of time, highlighting the importance of an active EV surveillance system in CNS infections. Enhanced understanding of undiagnosed CNS infections will assist in public health and health care planning., (© 2020 Wiley Periodicals LLC.)

Published data support the hypothesis that viruses could be trigger agents of multiple sclerosis onset. This link is based on evidence of early exposure to viral agents in patients affected by this neurologic disease. JC (JC polyomavirus [JCPyV]), BK (BKPyV), and simian virus 40 (SV40) neurotropic polyomavirus footprints have been detected in brain tissue specimens and samples from patients affected by different neurological diseases. In this investigation, serum samples from patients affected by multiple sclerosis and other inflammatory and noninflammatory neurologic diseases, as well as healthy subjects representing the control, were investigated for immunoglobulin G (IgG) antibodies against JCPyV. To this end, an immunologic approach was employed, which consists of employing indirect enzyme-linked immunosorbent assay testing with synthetic peptides mimicking viral capsid protein 1 antigens. A significantly lower prevalence of IgG antibodies against JCPyV VP1 epitopes, with a low titer, was detected in serum samples from patients with multiple sclerosis (MS) and other neurologic diseases than in healthy subjects. Our study indicates that the prevalence of JCPyV antibodies from patients with multiple sclerosis is 50% lower than in healthy subjects, suggesting specific immune impairments. These results indicate that patients affected by neurological diseases, including MS, respond poorly to JCPyV VP1 antigens, suggesting specific immunologic dysfunctions., (© 2020 Wiley Periodicals, Inc.)

Madin–Darby canine kidney (MDCK) cells are commonly used to produce cell-based influenza vaccines. However, the role of the low-serum medium on the proliferation of MDCK cells and the propagation of the influenza virus has not been well studied. In the present study, we used 5 of 15 culture methods with different concentrations of a mixed medium and neonatal bovine serum (NBS) to determine the best culture medium. We found that a VP:M199 ratio of 1:2 (3% NBS) was suitable for culturing MDCK cells. Furthermore, the stable growth of MDCK cells and the production of the influenza virus were evaluated over long-term passaging. We found no significant difference in terms of cell growth and virus production between high and low passages of MDCK cells under low-serum culture conditions, regardless of influenza virus infection. Lastly, we performed a comparison of the transcriptomics and proteomics of MDCK cells cultured in VP:M199 = 1:2 (3% NBS) with those cultured in VP:M199 = 1:2 (5% NBS) before and after influenza virus infection. The transcriptome analysis showed that differentially expressed genes were predominantly enriched in the metabolic pathway and MAPK signaling pathway, indicating an activated state. This suggests that decreasing the concentration of serum in the medium from 5% to 3% may increase the metabolic activity of cells. Proteomics analysis showed that only a small number of differentially expressed proteins could not be enriched for analysis, indicating minimal difference in the protein levels of MDCK cells when the serum concentration in the medium was decreased from 5% to 3%. Altogether, our findings suggest that the screening and application of a low-serum medium provide a background for the development and optimization of cell-based influenza vaccines. [ABSTRACT FROM AUTHOR]

Introduction: Acute respiratory infections (ARI) are the most common infections in the general population and are mainly caused by respiratory viruses. Detecting several viruses in a respiratory sample is common. To better understand these viral codetections and potential interferences, we tested for the presence of viruses and developed quantitative PCR (Polymerase Chain Reaction) for the viruses most prevalent in coinfections: human rhinovirus (HRV) and respiratory syncytial virus (RSV), and quantified their viral loads according to coinfections and health status, age, cellular abundance and other variables. Materials and methods: Samples from two different cohorts were analyzed: one included hospitalized infants under 12 months of age with acute bronchiolitis (n=719) and the other primary care patients of all ages with symptoms of ARI (n = 685). We performed Multiplex PCR on nasopharyngeal swabs, and quantitative PCR on samples positive for HRV or/and RSV to determine viral loads (VL). Cellular abundance (CA) was also estimated by qPCR targeting the GAPDH gene. Genotyping was performed either directly from first-line molecular panel or by PCR and sequencing for HRV. Results: The risks of viral codetection were 4.1 (IC95[1.8; 10.0]) and 93.9 1 (IC95 [48.7; 190.7]) higher in infants hospitalized for bronchiolitis than in infants in primary care for RSV and HRV respectively (p<0.001). CA was higher in samples positive for multiple viruses than in mono-infected or negative samples (p<0.001), and higher in samples positive for RSV (p<0.001) and HRV (p<0.001) than in negative samples. We found a positive correlation between CA and VL for both RSV and HRV. HRV VL was higher in children than in the elderly (p<0.05), but not RSV VL. HRV VL was higher when detected alone than in samples coinfected with RSV-A and with RSV-B. There was a significant increase of RSV-A VL when codetecting with HRV (p=0.001) and when co-detecting with RSV-B+HRV versus RSV-A+ RSV-B (p=0.02). Conclusions: Many parameters influence the natural history of respiratory viral infections, and quantifying respiratory viral loads can help disentangle their contributions to viral outcome. [ABSTRACT FROM AUTHOR]

Viral co-infections, in which a host is infected with multiple viruses simultaneously, are common in the human population. Human viral co-infections can lead to complex interactions between the viruses and the host immune system, affecting the clinical outcome and posing challenges for treatment. Understanding the types, mechanisms, impacts, and identification methods of human viral co-infections is crucial for the prevention and control of viral diseases. In this review, we first introduce the significance of studying human viral co-infections and summarize the current research progress and gaps in this field. We then classify human viral co-infections into four types based on the pathogenic properties and species of the viruses involved. Next, we discuss the molecular mechanisms of viral co-infections, focusing on virus–virus interactions, host immune responses, and clinical manifestations. We also summarize the experimental and computational methods for the identification of viral co-infections, emphasizing the latest advances in high-throughput sequencing and bioinformatics approaches. Finally, we highlight the challenges and future directions in human viral co-infection research, aiming to provide new insights and strategies for the prevention, control, diagnosis, and treatment of viral diseases. This review provides a comprehensive overview of the current knowledge and future perspectives on human viral co-infections and underscores the need for interdisciplinary collaboration to address this complex and important topic. [ABSTRACT FROM AUTHOR]

Influenza A virus (IAV) infections represent a substantial global health challenge and are often accompanied by coinfections involving secondary viruses or bacteria, resulting in increased morbidity and mortality. The clinical impact of coinfections remains poorly understood, with conflicting findings regarding fatality. Isolating the impact of each pathogen and mechanisms of pathogen synergy during coinfections is challenging and further complicated by host and pathogen variability and experimental conditions. Factors such as cytokine dysregulation, immune cell function alterations, mucociliary dysfunction, and changes to the respiratory tract epithelium have been identified as contributors to increased lethality. The relative significance of these factors depends on variables such as pathogen types, infection timing, sequence, and inoculum size. Mathematical biological modeling can play a pivotal role in shedding light on the mechanisms of coinfections. Mathematical modeling enables the quantification of aspects of the intra-host immune response that are difficult to assess experimentally. In this narrative review, we highlight important mechanisms of IAV coinfection with bacterial and viral pathogens and survey mathematical models of coinfection and the insights gained from them. We discuss current challenges and limitations facing coinfection modeling, as well as current trends and future directions toward a complete understanding of coinfection using mathematical modeling and computer simulation. [ABSTRACT FROM AUTHOR]

Background Multiple viruses cocirculate and contribute to the burden of respiratory disease. Virus-virus interactions can decrease susceptibility to infection and this interference can have an epidemiological impact. As humans are normally exposed to a community of cocirculating respiratory viruses, experimental coinfection studies are necessary to understand the disease mechanisms of multipathogen systems. We aimed to characterize interactions within the respiratory tract between severe acute respiratory syndrome virus 2 (SARS-CoV-2) and 2 major respiratory viruses: influenza A virus (IAV), and respiratory syncytial virus (RSV). Methods We performed single infections and coinfections with SARS-CoV-2 combined with IAV or RSV in cultures of human bronchial epithelial cells. We combined microscopy with quantification of viral replication in the presence or absence of an innate immune inhibitor to determine changes in virus-induced pathology, virus spread, and virus replication. Results SARS-CoV-2 replication is inhibited by both IAV and RSV. This inhibition is dependent on a functional antiviral response and the level of inhibition is proportional to the timing of secondary viral infection. Conclusions Infections with other respiratory viruses might provide transient resistance to SARS-CoV-2. It would therefore be expected that the incidence of coronavirus disease 2019 (COVID-19) may decrease during periods of high circulation of IAV and RSV. [ABSTRACT FROM AUTHOR]

Respiratory viral infections are a leading global cause of disease with multiple viruses detected in 20–30% of cases, and several viruses simultaneously circulating. Some infections with unique viral copathogens result in reduced pathogenicity, while other viral pairings can worsen disease. The mechanisms driving these dichotomous outcomes are likely variable and have only begun to be examined in the laboratory and clinic. To better understand viral–viral coinfections and predict potential mechanisms that result in distinct disease outcomes, we first systematically fit mathematical models to viral load data from ferrets infected with respiratory syncytial virus (RSV), followed by influenza A virus (IAV) after 3 days. The results suggest that IAV reduced the rate of RSV production, while RSV reduced the rate of IAV infected cell clearance. We then explored the realm of possible dynamics for scenarios that had not been examined experimentally, including a different infection order, coinfection timing, interaction mechanisms, and viral pairings. IAV coinfection with rhinovirus (RV) or SARS-CoV-2 (CoV2) was examined by using human viral load data from single infections together with murine weight-loss data from IAV-RV, RV-IAV, and IAV-CoV2 coinfections to guide the interpretation of the model results. Similar to the results with RSV-IAV coinfection, this analysis shows that the increased disease severity observed during murine IAV-RV or IAV-CoV2 coinfection was likely due to the slower clearance of IAV-infected cells by the other viruses. The improved outcome when IAV followed RV, on the other hand, could be replicated when the rate of RV infected cell clearance was reduced by IAV. Simulating viral–viral coinfections in this way provides new insights about how viral–viral interactions can regulate disease severity during coinfection and yields testable hypotheses ripe for experimental evaluation. [ABSTRACT FROM AUTHOR]

Influenza virus infection is a common cause of self‐limiting respiratory tract infection (RTI), however immunocompromised patients are at an increased risk for a severe course of disease or fatal outcome. We therefore aimed to gain a better understanding of the molecular epidemiology of influenza viruses from patients with haematological disorders and their impact on the clinical course of disease. Molecular analysis using polymerase chain reaction (PCR) of nasopharyngeal swabs was performed for influenza virus in haematological patients at the Heidelberg University Hospital. Clinical data was evaluated to identify associated risk factors. For phylogenetic analysis, the hemagglutinin (HA) gene was sequenced. Out of 159 influenza positive patients, 117 patients developed upper RTI (influenza A: n = 73; influenza B: n = 44). Lower RTI was observed in n = 42 patients (26%), n = 22/42 patients developed severe disease and n = 16/159 (10.1%) patients died. Risk factors for lower RTI were nosocomial infection (p = 0.02), viral shedding for ≥14 days (p = 0.018), IgG levels <6 g/dL (p = 0.046), bacterial/fungal co‐infections (p < 0.001). Risk factors for fatal outcome were age ≥65 years (p = 0.032), bacterial/fungal (p≤0.001) co‐infections and high viral load (p = 0.026). Sequencing of the HA gene (n = 115) revealed subtype A(H3N2) (n = 46), A(H1N1)pdm09 (n = 24), B/Victoria (n = 34), B/Yamagata (n = 11). There was no correlation between influenza (sub)type and lower RTI. Influenza infection in haematological patients is associated with significant morbidity and mortality, the risk for aggravating co‐infections, prolonged viral shedding and nosocomial transmission emphasizing the need for infection control. [ABSTRACT FROM AUTHOR]

In nature, viral coinfection is as widespread as viral infection alone. Viral coinfections often cause altered viral pathogenicity, disrupted host defense, and mixed-up clinical symptoms, all of which result in more difficult diagnosis and treatment of a disease. There are three major virus–virus interactions in coinfection cases: viral interference, viral synergy, and viral noninterference. We analyzed virus–virus interactions in both aspects of viruses and hosts and elucidated their possible mechanisms. Finally, we summarized the protocol of viral coinfection studies and key points in the process of virus separation and purification. [ABSTRACT FROM AUTHOR]

Background: Neurological complications due to chikungunya virus (CHIKV) infection have been described in different parts of the world, with children being disproportionately affected. However, the burden of CHIKV-associated neurological disease in Africa is currently unknown and given the lack of diagnostic facilities in routine care it is possible that CHIKV is an unrecognized etiology among children with encephalitis or other neurological illness.Methods and Findings: We estimated the incidence of CHIKV infection among children hospitalized with neurological disease in Kilifi County, coastal Kenya. We used reverse transcriptase polymerase chain reaction (RT-PCR) to systematically test for CHIKV in cerebrospinal fluid (CSF) samples from children aged <16 years hospitalized with symptoms of neurological disease at Kilifi County Hospital between January 2014 and December 2018. Clinical records were linked to the Kilifi Health and Demographic Surveillance System and population incidence rates of CHIKV infection estimated. There were 18,341 pediatric admissions for any reason during the 5-year study period, of which 4,332 (24%) had CSF collected. The most common clinical reasons for CSF collection were impaired consciousness, seizures, and coma (47%, 22%, and 21% of all collections, respectively). After acute investigations done for immediate clinical care, CSF samples were available for 3,980 admissions, of which 367 (9.2%) were CHIKV RT-PCR positive. Case fatality among CHIKV-positive children was 1.4% (95% CI 0.4, 3.2). The annual incidence of CHIKV-associated neurological disease varied between 13 to 58 episodes per 100,000 person-years among all children <16 years old. Among children aged <5 years, the incidence of CHIKV-associated neurological disease was 77 per 100,000 person-years, compared with 20 per 100,000 for cerebral malaria and 7 per 100,000 for bacterial meningitis during the study period. Because of incomplete case ascertainment due to children not presenting to hospital, or not having CSF collected, these are likely minimum estimates. Study limitations include reliance on hospital-based surveillance and limited CSF sampling in children in coma or other contraindications to lumbar puncture, both of which lead to under-ascertainment of incidence and of case fatality.Conclusions: In this study, we observed that CHIKV infections are relatively more common than cerebral malaria and bacterial meningitis among children hospitalized with neurological disease in coastal Kenya. Given the wide distribution of CHIKV mosquito vectors, studies to determine the geographic extent of CHIKV-associated neurological disease in Africa are essential. [ABSTRACT FROM AUTHOR]

Background: While malaria morbidity and mortality have declined since 2000, viral central nervous system infections appear to be an important, underestimated cause of coma in malaria-endemic Eastern Africa. We aimed to describe the etiology of non-traumatic comas in young children in Benin, as well as their management and early outcomes, and to identify factors associated with death. Methods: From March to November 2018, we enrolled all HIV-negative children aged between 2 and 6 years, with a Blantyre Coma Score ≤ 2, in this prospective observational study. Children were screened for malaria severity signs and assessed using a systematic diagnostic protocol, including blood cultures, malaria diagnostics, and cerebrospinal fluid analysis using multiplex PCR. To determine factors associated with death, univariate and multivariate analyses were performed. Results: From 3244 admissions, 84 children were included: malaria was diagnosed in 78, eight of whom had a viral or bacterial co-infection. Six children had a non-malarial infection or no identified cause. The mortality rate was 29.8% (25/84), with 20 children dying in the first 24 h. Co-infected children appeared to have a poorer prognosis. Of the 76 children who consulted a healthcare professional before admission, only 5 were prescribed adequate antimalarial oral therapy. Predictors of early death were jaundice or increased bilirubin [odd ratio (OR)= 8.6; 95% confidential interval (CI): 2.03–36.1] and lactate > 5 mmol/L (OR = 5.1; 95% CI: 1.49–17.30). Antibiotic use before admission (OR = 0.1; 95% CI: 0.02–0.85) and vaccination against yellow fever (OR = 0.2, 95% CI: 0.05–0.79) protected against mortality. Conclusions: Infections were found in all children who died, and cerebral malaria was by far the most common cause of non-traumatic coma. Missed opportunities to receive early effective antimalarial treatment were common. Other central nervous system infections must be considered in their management. Some factors that proved to be protective against early death were unexpected. [ABSTRACT FROM AUTHOR]

Background: Simultaneous viral infections exhibit the phenomenon of viral interference, but understanding of the effect of one virus on another is limited. Objective: Evaluate and compare clinical characteristics, immune and acute phase response, viral shedding and viral load in pigs singly and doubly inoculated with swine influenza A virus (swIAV) and porcine reproductive and respiratory syndrome virus (PRRSV). Animals Fifty‐four 7‐week‐old piglets. Methods: Clinical status and gross lung lesions were scored. Titration of swIAV was carried out in Madin‐Darby canine kidney cells. The PRRSV RNA was quantified using a commercial qPCR kit. Antibodies were detected by hemagglutination inhibition assay and commercial ELISA. A lymphocyte proliferation assay was used to measure antigen‐specific T‐cell responses. Acute phase proteins were determined using ELISA. Results: No differences were found between mean clinical scores, swIAV and PRRSV shedding, and magnitude of the humoral and T‐cell response between single‐inoculated and dual‐inoculated groups. Concentrations of C‐reactive protein and haptoglobin increased in PRRSV‐inoculated and coinoculated groups, whereas serum amyloid A concentration was increased in groups inoculated or coinoculated with swIAV. Mean swIAV TCID50 titers in the lungs did not differ significantly between coinoculated and swIAV single‐inoculated pigs. A significantly higher mean copy number of PRRSV was found in the lungs of PRRSV only‐inoculated pigs at 2 day postinoculation (DPI). From 4 DPI, no significant differences in PRRSV load were identified. Conclusions and Clinical Importance: Coinfection of pigs with swIAV and PRRSV did not potentiate clinical signs, lung lesions, immune response, and replication of the viruses in the respiratory tract. [ABSTRACT FROM AUTHOR]

Humans and animals are infected by multiple endogenous and exogenous viruses but few agents cause overt tissue damage. We review the circumstances which favor overt disease expression. These can include intrinsic virulence of the agent, new agents acquired from heterologous species, the circumstances of infection such as dose and route, current infection with other agents which includes the composition of the microbiome at mucosal and other sites, past history of exposure to other infections as well as the immune status of the host. We also briefly discuss promising therapeutic strategies that can expand immune response patterns that minimize tissue damaging responses to viral infections. [ABSTRACT FROM AUTHOR]

Copyright of Proceedings of the Latvian Academy of Sciences. Section B: Natural, Exact & Applied Sciences is the property of Sciendo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Summary: Influenza virus infections are a leading cause of morbidity and mortality worldwide. This is due in part to the continual emergence of new viral variants and to synergistic interactions with other viruses and bacteria. There is a lack of understanding about how host responses work to control the infection and how other pathogens capitalize on the altered immune state. The complexity of multi‐pathogen infections makes dissecting contributing mechanisms, which may be non‐linear and occur on different time scales, challenging. Fortunately, mathematical models have been able to uncover infection control mechanisms, establish regulatory feedbacks, connect mechanisms across time scales, and determine the processes that dictate different disease outcomes. These models have tested existing hypotheses and generated new hypotheses, some of which have been subsequently tested and validated in the laboratory. They have been particularly a key in studying influenza‐bacteria coinfections and will be undoubtedly be useful in examining the interplay between influenza virus and other viruses. Here, I review recent advances in modeling influenza‐related infections, the novel biological insight that has been gained through modeling, the importance of model‐driven experimental design, and future directions of the field. [ABSTRACT FROM AUTHOR]

Background: While it is known that acute respiratory illness (ARI) is caused by an array of viruses, less is known about co-detections and the resultant comparative symptoms and illness burden. This study examined the co-detections, the distribution of viruses, symptoms, and illness burden associated with ARI between December 2012 and March 2013. Methods: Outpatients with ARI were assayed for presence of 18 viruses using multiplex reverse transcriptase polymerase chain reaction (MRT-PCR) to simultaneously detect multiple viruses. Results: Among 935 patients, 60% tested positive for a single virus, 9% tested positive for =1 virus and 287 (31%) tested negative. Among children (<18 years), the respective distributions were 63%, 14%, and 23%; whereas for younger adults (18-49 years), the distributions were 58%, 8%, and 34% and for older adults (=50 years) the distributions were 61%, 5%, and 32% (P < 0.001). Co-detections were more common in children than older adults (P = 0.01), and less frequent in households without children (P = 0.003). Most frequently co-detected viruses were coronavirus, respiratory syncytial virus, and influenza A virus. Compared with single viral infections, those with co-detections less frequently reported sore throat (P = 0.01), missed fewer days of school (1.1 vs. 2 days; P = 0.04), or work (2 vs. 3 days; P = 0.03); other measures of illness severity did not vary. Conclusions: Among outpatients with ARI, 69% of visits were associated with a viral etiology. Co-detections of specific clusters of viruses were observed in 9% of ARI cases particularly in children, were less frequent in households without children, and were less symptomatic (e.g., lower fever) than single infections. [ABSTRACT FROM AUTHOR]

Background: Results from cohort studies evaluating the severity of respiratory viral co-infections are conflicting. We conducted a systematic review and meta-analysis to assess the clinical severity of viral co-infections as compared to single viral respiratory infections. Methods: We searched electronic databases and other sources for studies published up to January 28, 2013. We included observational studies on inpatients with respiratory illnesses comparing the clinical severity of viral co-infections to single viral infections as detected by molecular assays. The primary outcome reflecting clinical disease severity was length of hospital stay (LOS). A random-effects model was used to conduct the meta-analyses. Results: Twenty-one studies involving 4,280 patients were included. The overall quality of evidence applying the GRADE approach ranged from moderate for oxygen requirements to low for all other outcomes. No significant differences in length of hospital stay (LOS) (mean difference (MD) −0.20 days, 95% CI −0.94, 0.53, p = 0.59), or mortality (RR 2.44, 95% CI 0.86, 6.91, p = 0.09) were documented in subjects with viral co-infections compared to those with a single viral infection. There was no evidence for differences in effects across age subgroups in post hoc analyses with the exception of the higher mortality in preschool children (RR 9.82, 95% CI 3.09, 31.20, p<0.001) with viral co-infection as compared to other age groups (I2 for subgroup analysis 64%, p = 0.04). Conclusions: No differences in clinical disease severity between viral co-infections and single respiratory infections were documented. The suggested increased risk of mortality observed amongst children with viral co-infections requires further investigation. [ABSTRACT FROM AUTHOR]

Background: The clinical consequences of co-infection with two or more respiratory viruses are poorly understood. We sought to determine if co-infection with pandemic 2009–2010 influenza A H1N1 (pH1N1) and another respiratory virus was associated with worse clinical outcomes. Methods: A retrospective cohort study was performed of all hospitalized patients with a positive respiratory viral panel (RVP) for two or more viruses within 72 hours of admission at our institution from October 2009 to December 2009. We compared patients infected with one respiratory virus to those with respiratory viral co-infection. Results: We identified 617 inpatients with a positive RVP sample with a single virus and 49 inpatients with a positive RVP sample for two viruses (i.e. co-infection). Co-infected patients were significantly younger, more often had fever/chills, tachypnea, and they more often demonstrated interstitial opacities suggestive of viral pneumonia on the presenting chest radiograph (OR 7.5, 95% CI 3.4–16.5). The likelihood of death, length of stay, and requirement for intensive care unit level of care were similar in both groups, but patients with any respiratory virus co-infection were more likely to experience complications, particularly treatment for a secondary bacterial pneumonia (OR 6.8, 95% CI 3.3–14.2). Patients co-infected with pH1N1 and another respiratory virus were more likely to present with chest radiograph changes suggestive of a viral pneumonia, compared to mono-infection with pH1N1 (OR 16.9, 95% CI 4.5–62.7). By logistic regression using mono-infection with non-PH1N1 viruses as the reference group, co-infection with pH1N1 was the strongest independent predictor of treatment for a secondary bacterial pneumonia (OR 17.8, 95% CI 6.7–47.1). Conclusion: Patients with viral co-infection, particularly with pH1N1, were more likely to have chest radiograph features compatible with a viral pneumonia and complications during their hospital course, particularly treatment for secondary bacterial pneumonia. Despite this, co-infection was not associated with ICU admission. [ABSTRACT FROM AUTHOR]

The recently discovered exchange protein directly activated by cAMP (EPAC), compared with protein kinase A (PKA), is a fairly new family of cAMP effectors. Soon after the discovery, EPAC has shown its significance in many diseases including its emerging role in infectious diseases. In a recent study, we demonstrated that EPAC, but not PKA, is a promising therapeutic target to regulate respiratory syncytial virus (RSV) replication and its associated inflammation. In mammals, there are two isoforms of EPAC—EPAC1 and EPAC2. Unlike other viruses, including Middle East respiratory syndrome coronavirus (MERS-CoV) and Ebola virus, which use EPAC1 to regulate viral replication, RSV uses EPAC2 to control its replication and associated cytokine/chemokine responses. To determine whether EPAC2 protein has a broad impact on other respiratory viral infections, we used an EPAC2-specific inhibitor, MAY0132, to examine the functions of EPAC2 in human metapneumovirus (HMPV) and adenovirus (AdV) infections. HMPV is a negative-sense single-stranded RNA virus belonging to the family Pneumoviridae, which also includes RSV, while AdV is a double-stranded DNA virus. Treatment with an EPAC1-specific inhibitor was also included to investigate the impact of EPAC1 on these two viruses. We found that the replication of HMPV, AdV, and RSV and the viral-induced immune mediators are significantly impaired by MAY0132, while an EPAC1-specific inhibitor, CE3F4, does not impact or slightly impacts, demonstrating that EPAC2 could serve as a novel common therapeutic target to control these viruses, all of which do not have effective treatment and prevention strategies. [ABSTRACT FROM AUTHOR]

An introduction is presented to the article "Risk factors for need of mechanical ventilation in children with influenza A(H1N1)PDM09."