Influenza

Hybrid neural network models for time series disease prediction confronted by spatiotemporal dependencies

In infectious disease outbreak modeling, there remains a gap in addressing spatiotemporal challenges present in established models. This study addresses this gap by evaluating four established hybrid neural network models for predicting influenza outbreaks. These models were analyzed by employing time series data from eight different countries to challenge the models with imposed spatial difficulties, in a month-on-month structure. The models' predictions were compared using MAPE, and RMSE, as well as graphical representations generated by employed models. The SARIMA-LSTM model excelled in achieving the lowest average RMSE score of 66.93 as well as reporting the lowest RMSE score for three out of eight countries studied. In this case also, GA-ConvLSTM-CNN model comes in second place with an average RMSE score of 68.46. Considering these results and the ability to follow the seasonal trends of the actual values, this study suggests the SARIMA-LSTM model to be more robust to spatiotemporal challenges compared with the other models under examination. This study•Evaluated established methods with unique imposed difficulty.•Addressed spatiotemporal characteristics of the data.•Proposed the SARIMA-LSTM model based on evaluation metrics.

Exploring Bioactive Phytomedicines for Advancing Pulmonary Infection Management: Insights and Future Prospects

Pulmonary infections have a profound influence on global mortality rates. Medicinal plants offer a promising approach to address this challenge, providing nontoxic alternatives with higher levels of public acceptance and compliance, particularly in regions where access to conventional medications or diagnostic resources may be limited. Understanding the pathophysiology of viruses and bacteria enables researchers to identify biomarkers essential for triggering diseases. This knowledge allows the discovery of biological molecules capable of either preventing or alleviating symptoms associated with these infections. In this review, medicinal plants that have an effect on COVID-19, influenza A, bacterial and viral pneumonia, and tuberculosis are discussed. Drug delivery has been briefly discussed as well. It examines the effect of bioactive constituents of these plants and synthesizes findings from in vitro, in vivo, and clinical studies conducted over the past decade. In conclusion, many medicinal plants can be used to treat pulmonary infections, but further in-depth studies are needed as most of the current studies are only at preliminary stages. Extensive investigation and clinical studies are warranted to fully elucidate their mechanisms of action and optimize their use in clinical practice.

Evolutionary analysis of Hemagglutinin and neuraminidase gene variation in H1N1 swine influenza virus from vaccine intervention in China

Influenza poses a significant threat to the global economy and health. Inactivated virus vaccines were introduced in China for prevention in 2018. In this study, three pairs of hemagglutinin (HA) and neuraminidase (NA) gene sequences were obtained from three Swine influenza virus (IAV-S) inactivated vaccine strains that were marketed in China in 2018. Phylogenetic analysis was carried out with HA and NA gene sequences to investigate the relationship between vaccine use and virus genetic drift. The findings showed that the evolutionary rate of HA remained relatively stable from 2012 to 2017, with an average genetic distance of approximately 0.020731195. However, following the introduction of the swine influenza vaccine, there was a notable acceleration in the evolutionary rate of HA, accompanied by a significant increase in the genetic distance. In 2018, the value was 0.111750269, while in 2019 it was 0.176389393. In contrast, the evolution of NA was relatively smooth, with an average genetic distance of approximately 0.030386708. Finally, we demonstrated that commercial vaccines are weak neutralizers of wild strains through immunization experiments in animals. Thus, we have reason to believe that mutations in the virus favor virus evasion of vaccine immunity. Our findings suggest that vaccine use may significantly impact the evolution of the influenza virus by potentially stimulating mutations. The selection pressure of vaccine antibodies played a role in regulating the variation of IAV-S-H1N1.

Kaempferol: A Review of Current Evidence of Its Antiviral Potential

Kaempferol and its derivatives are flavonoids found in various plants, and a considerable number of these have been used in various medical applications worldwide. Kaempferol and its compounds have well-known antioxidant, anti-inflammatory and antimicrobial properties among other health benefits. However, the antiviral properties of kaempferol are notable, and there is a significant number of experimental studies on this topic. Kaempferol compounds were effective against DNA viruses such as hepatitis B virus, viruses of the alphaherpesvirinae family, African swine fever virus, and pseudorabies virus; they were also effective against RNA viruses, namely feline SARS coronavirus, dengue fever virus, Japanese encephalitis virus, influenza virus, enterovirus 71, poliovirus, respiratory syncytial virus, human immunodeficiency virus, calicivirus, and chikungunya virus. On the other hand, no effectiveness against murine norovirus and hepatitis A virus could be determined. The antiviral action mechanisms of kaempferol compounds are various, such as the inhibition of viral polymerases and of viral attachment and entry into host cells. Future research should be focused on further elucidating the antiviral properties of kaempferol compounds from different plants and assessing their potential use to complement the action of antiviral drugs.

Antimicrobial Properties of Capsaicin: Available Data and Future Research Perspectives

Capsaicin is a phytochemical derived from plants of the genus Capsicum and subject of intensive phytochemical research due to its numerous physiological and therapeutical effects, including its important antimicrobial properties. Depending on the concentration and the strain of the bacterium, capsaicin can exert either bacteriostatic or even bactericidal effects against a wide range of both Gram-positive and Gram-negative bacteria, while in certain cases it can reduce their pathogenicity by a variety of mechanisms such as mitigating the release of toxins or inhibiting biofilm formation. Likewise, capsaicin has been shown to be effective against fungal pathogens, particularly Candida spp., where it once again interferes with biofilm formation. The parasites Toxoplasma gondi and Trypanosoma cruzi have been found to be susceptible to the action of this compound too while there are also viruses whose invasiveness is significantly dampened by it. Among the most encouraging findings are the prospects for future development, especially using new formulations and drug delivery mechanisms. Finally, the influence of capsaicin in somatostatin and substance P secretion and action, offers an interesting array of possibilities given that these physiologically secreted compounds modulate inflammation and immune response to a significant extent.

A rapid and efficient platform for antiviral crRNA screening using CRISPR-Cas13a-based nucleic acid detection

Introduction

Rapid and high-throughput screening of antiviral clustered regularly interspaced short palindromic repeat (CRISPR) RNAs (crRNAs) is urgently required for the CRISPR-Cas13a antiviral system. Based on the same principle, we established an efficient screening platform for antiviral crRNA through CRISPR-Cas13a nucleic acid detection.

Method

In this study, crRNAs targeting PA, PB1, NP, and PB2 of the influenza A virus (H1N1) were screened using CRISPR-Cas13a nucleic acid detection, and their antiviral effects were confirmed by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The RNA secondary structures were predicted by bioinformatics methods.

Results

The results showed that crRNAs screened by CRISPR-Cas13a nucleic acid detection could effectively inhibit viral RNA in mammalian cells. Besides, we found that this platform for antiviral crRNA screening was more accurate than RNA secondary structure prediction. In addition, we validated the feasibility of the platform by screening crRNAs targeting NS of the influenza A virus (H1N1).

Discussion

This study provides a new approach for screening antiviral crRNAs and contributes to the rapid advancement of the CRISPR-Cas13a antiviral system.

The epidemiological pattern of seasonal influenza in four sentinel sites in Iraq

Introduction

Influenza is an acute viral infection with significant morbidity and mortality. It occurs annually each winter, which is called seasonal influenza, and is preventable through safe vaccine.

Aim

The aim of this work is to know the epidemiological pattern of patients with seasonal influenza in Iraqi sentinel sites.

Methods

A cross-sectional study was carried out on records of patients who attended four sentinel sites and registered to have influenza-like illness (ILI) or severe acute respiratory infection (SARI), and laboratory investigated.

Results

The total number of cases was 1124; 36.2% of them aged 19-39 years; 53.9% were female; 74.9% lived in urban areas; 64.3% diagnosed as ILI; and 35.7% as SARI; 15.9% had diabetes, 12.7% had heart disease, 4.8% had asthma, 3% had a chronic lung disease, and 2% had hematological disease; 94.6% did not get influenza vaccine. About COVID-19 vaccine, 69.4% were not vaccinated, 3.5% got only one dose, and 27.1% completed two doses. Only the SARI cases needed admission; among them, 95.7% were cured. 6.5% were diagnosed with influenza-A virus, 26.1% had COVID-19, and 67.5% were negative. Among those with influenza, 97.3% had H3N2 subtype and 2.7% had H1N1 pdm09.

Conclusions

The percentage of influenza virus in Iraq is relatively small. The age, classification of case (ILI or SARI), having diabetes, heart disease, or immunological disease, and taking COVID-19 vaccine have a significant association with influenza.

Recommendations

It is needed for similar sentinel sites in other health directorates and for rising health education about seasonal influenza and its vaccine.

Neurological features related to influenza virus in the pediatric population: a 3-year monocentric retrospective study

Influenza virus is generally characterized by fever, myalgia, and respiratory symptoms. Neurological entities have already been described, such as acute necrotizing encephalitis (ANE). We aimed to highlight the non-exceptional nature and explore the clinical spectrum and evolution of neurological features related to influenza virus in children. This monocentric observational study included patients under 18 years old, positive for influenza virus, between January 2017 and April 2019 in a pediatric university hospital. Patients were classified into two groups: those with or without a previous significant neurological or metabolic disorder. Two hundred eighty-nine children were identified with influenza infection. Thirty seven had a neurological manifestation: 14 patients who had previous significant neurological or metabolic disorder and 23 patients with no medical history. We identified several clinical patterns: 22 patients had seizures, 7 behavior disorders, 5 disturbances of consciousness, and 3 motor deficits. Four were diagnosed with a known influenza-associated neurological syndrome: 1 ANE, 1 cytotoxic lesion of the corpus callosum, 1 hemiconvulsion-hemiplegia-epilepsia syndrome, and 1 recurrent encephalitis in the context of a RANBP2 mutation. The neurological outcome was favorable in most cases. None of the patients with previous significant disorder retained sequalae or had a recurrence. Two patients had a fatal outcome, and both had a predisposing disorder.

CONCLUSION

Various neurological manifestations can be associated with influenza virus. Certain entities led to a poor prognosis, but in most cases, symptoms improved within a few days. The severity of the neurological manifestations correlated with previous neurological or metabolic disorders.

WHAT IS KNOWN

• Influenza viruses are well known pathogens with a seasonal epidemic evolution, particularly affecting children. These viruses cause acute fever with respiratory symptoms, associated with myalgia and headaches. Neurological presentation in influenza-virus infection is a well-established possibility as influenza virus is considered to be responsible for 27 to 36% of childhood encephalitis. Some specific and severe entity as acute necrotizing encephalitis, cytotoxic lesion of the corpus callosum, or Hemiconvulsion-hemiplegia-epilepsy syndrome are well described.

WHAT IS NEW

• In a French monocentric cohort of 37 children with influenza-related neurologic manifestations, the majority of these manifestations, including seizure, drowsiness, motor deficiency, hallucination… are self limiting and do not lead to after-effects. In rare cases (4/37), they may reveal severe encephalitis requiring rapid and appropriate treatment. Otherwise, comparison of a group of 14 children with underlying neurological or metabolic disorder with a group of 23 children free of any significant disorder show that the severity of the neurological manifestations was largely related to previous neurological or metabolic disorders highlighting the importance of vaccination in this population.

Hemagglutinin Antibodies in the Polish Population during the 2019/2020 Epidemic Season

The aim of the study was to determine the level of antibodies against hemagglutinin of influenza viruses in the serum of subjects belonging to seven different age groups in the 2019/2020 epidemic season. The level of anti-hemagglutinin antibodies was tested using the hemagglutination inhibition (HAI) test. The tests included 700 sera from all over Poland. Their results confirmed the presence of antibodies against the following influenza virus antigens: A/Brisbane/02/2018 (H1N1)pdm09 (48% of samples), A/Kansas/14/2017/ (H3N2) (74% of samples), B/Colorado/06/ 2017 Victoria line (26% of samples), and B/Phuket/3073/2013 Yamagata line (63% of samples). The level of antibodies against hemagglutinin varied between the age groups. The highest average (geometric mean) antibody titer (68.0) and the highest response rate (62%) were found for the strain A/Kansas/14/2017/ (H3N2). During the epidemic season in Poland, only 4.4% of the population was vaccinated.

Study on the prediction effect of a combined model of SARIMA and LSTM based on SSA for influenza in Shanxi Province, China

BACKGROUND

Influenza is an acute respiratory infectious disease that is highly infectious and seriously damages human health. Reasonable prediction is of great significance to control the epidemic of influenza.

METHODS

Our Influenza data were extracted from Shanxi Provincial Center for Disease Control and Prevention. Seasonal-trend decomposition using Loess (STL) was adopted to analyze the season characteristics of the influenza in Shanxi Province, China, from the 1st week in 2010 to the 52nd week in 2019. To handle the insufficient prediction performance of the seasonal autoregressive integrated moving average (SARIMA) model in predicting the nonlinear parts and the poor accuracy of directly predicting the original sequence, this study established the SARIMA model, the combination model of SARIMA and Long-Short Term Memory neural network (SARIMA-LSTM) and the combination model of SARIMA-LSTM based on Singular spectrum analysis (SSA-SARIMA-LSTM) to make predictions and identify the best model. Additionally, the Mean Squared Error (MSE), Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) were used to evaluate the performance of the models.

RESULTS

The influenza time series in Shanxi Province from the 1st week in 2010 to the 52nd week in 2019 showed a year-by-year decrease with obvious seasonal characteristics. The peak period of the disease mainly concentrated from the end of the year to the beginning of the next year. The best fitting and prediction performance was the SSA-SARIMA-LSTM model. Compared with the SARIMA model, the MSE, MAE and RMSE of the SSA-SARIMA-LSTM model decreased by 38.12, 17.39 and 21.34%, respectively, in fitting performance; the MSE, MAE and RMSE decreased by 42.41, 18.69 and 24.11%, respectively, in prediction performances. Furthermore, compared with the SARIMA-LSTM model, the MSE, MAE and RMSE of the SSA-SARIMA-LSTM model decreased by 28.26, 14.61 and 15.30%, respectively, in fitting performance; the MSE, MAE and RMSE decreased by 36.99, 7.22 and 20.62%, respectively, in prediction performances.

CONCLUSIONS

The fitting and prediction performances of the SSA-SARIMA-LSTM model were better than those of the SARIMA and the SARIMA-LSTM models. Generally speaking, we can apply the SSA-SARIMA-LSTM model to the prediction of influenza, and offer a leg-up for public policy.

Urine Metabolome Dynamics Discriminate Influenza Vaccination Response

Influenza represents a major and ongoing public health hazard. Current collaborative efforts are aimed toward creating a universal flu vaccine with the goals of both improving responses to vaccination and increasing the breadth of protection against multiple strains and clades from a single vaccine. As an intermediate step toward these goals, the current work is focused on evaluating the systemic host response to vaccination in both normal and high-risk populations, such as the obese and geriatric populations, which have been linked to poor responses to vaccination. We therefore employed a metabolomics approach using a time-course (n = 5 time points) of the response to human vaccination against influenza from the time before vaccination (pre) to 90 days following vaccination. We analyzed the urinary profiles of a cohort of subjects (n = 179) designed to evenly sample across age, sex, BMI, and other demographic factors, stratifying their responses to vaccination as “High”, “Low”, or “None” based on the seroconversion measured by hemagglutination inhibition assay (HAI) from plasma samples at day 28 post-vaccination. Overall, we putatively identified 15,903 distinct, named, small-molecule structures (4473 at 10% FDR) among the 895 samples analyzed, with the aim of identifying metabolite correlates of the vaccine response, as well as prognostic and diagnostic markers from the periods before and after vaccination, respectively. Notably, we found that the metabolic profiles could unbiasedly separate the high-risk High-responders from the high-risk None-responders (obese/geriatric) within 3 days post-vaccination. The purine metabolites Guanine and Hypoxanthine were negatively associated with high seroconversion (p = 0.0032, p < 0.0001, respectively), while Acetyl-Leucine and 5-Aminovaleric acid were positively associated. Further changes in Cystine, Glutamic acid, Kynurenine and other metabolites implicated early oxidative stress (3 days) after vaccination as a hallmark of the High-responders. Ongoing efforts are aimed toward validating these putative markers using a ferret model of influenza infection, as well as an independent cohort of human seasonal vaccination and human challenge studies with live virus.

Defective Interfering Particles of Influenza Virus and Their Characteristics, Impacts, and Use in Vaccines and Antiviral Strategies: A Systematic Review

Defective interfering particles (DIPs) are particles containing defective viral genomes (DVGs) generated during viral replication. DIPs have been found in various RNA viruses, especially in influenza viruses. Evidence indicates that DIPs interfere with the replication and encapsulation of wild-type viruses, namely standard viruses (STVs) that contain full-length viral genomes. DIPs may also activate the innate immune response by stimulating interferon synthesis. In this review, the underlying generation mechanisms and characteristics of influenza virus DIPs are summarized. We also discuss the potential impact of DIPs on the immunogenicity of live attenuated influenza vaccines (LAIVs) and development of influenza vaccines based on NS1 gene-defective DIPs. Finally, we review the antiviral strategies based on influenza virus DIPs that have been used against both influenza virus and SARS-CoV-2. This review provides systematic insights into the theory and application of influenza virus DIPs.

Anti-Influenza Effect and Mechanisms of Lentinan in an ICR Mouse Model

Influenza virus is a serious threat to global human health and public health security. There is an urgent need to develop new anti-influenza drugs. Lentinan (LNT) has attracted increasing attention in recent years. As potential protective agent, LNT has been shown to have anti-tumor, anti-inflammatory, and antiviral properties. However, there has been no further research into the anti-influenza action of lentinan in vivo, and the mechanism is still not fully understood. In this study, the anti-influenza effect and mechanism of Lentinan were studied in the Institute of Cancer Research (ICR) mouse model. The results showed that Lentinan had a high degree of protection in mice against infection with influenza A virus, delayed the emergence of clinical manifestations, improved the survival rate of mice, significantly prolonged the middle survival days, attenuated the weight loss, and reduced the lung coefficient of mice. It alleviated the pathological damage of mice infected with the influenza virus and improved blood indices. Lentinan treatment considerably inhibited inflammatory cytokine (TNF-α, IL-1β, IL-4, IL-5, IL-6) levels in the serum and lung and improved IFN-γ cytokine levels, which reduced cytokine storms caused by influenza virus infection. The underlying mechanisms of action involved Lentinan inhibiting the inflammatory response by regulating the TLR4/MyD88 signaling pathway. This study provides a foundation for the clinical application of Lentinan, and provides new insight into the development of novel immunomodulators.

Hemagglutinin Gene Variation Rate of H9N2 Avian Influenza Virus by Vaccine Intervention in China

H9N2 subtype avian influenza virus (AIV) is widespread globally, with China being the main epidemic center. Inactivated virus vaccination was adopted as the main prevention method in China. In this study, 22 hemagglutinin (HA) sequences were obtained from all inactivated vaccine strains of H9N2 subtype AIVs in China since its introduction. A phylogenetic analysis of the vaccine sequences and HA sequences of all published H9N2 subtype AIVs was conducted to investigate the relationship between vaccine use and the virus genetic diversity of the virus. We found that during 2002–2006, when fewer vaccines were used, annual genetic differences between the HA sequences were mainly distributed between 0.025 and 0.075 and were mainly caused by point mutations. From 2009 to 2013, more vaccines were used, and the genetic distance between sequences was about 10 times greater than between 2002 and 2006, especially in 2013. In addition to the accumulation of point mutations, insertion mutations may be the main reason for the large genetic differences between sequences from 2009 to 2013. These findings suggest that the use of inactivated vaccines affected point mutations in the HA sequences and that the contribution of high-frequency replacement vaccine strains to the rate of virus evolution is greater than that of low-frequency replacement vaccine strains. The selection pressure of the vaccine antibody plays a certain role in regulating the variation of HA sequences in H9N2 subtype AIV.

Consequences of Viral Infection and Cytokine Production During Pregnancy on Brain Development in Offspring

Infections during pregnancy can seriously damage fetal neurodevelopment by aberrantly activating the maternal immune system, directly impacting fetal neural cells. Increasing evidence suggests that these adverse impacts involve alterations in neural stem cell biology with long-term consequences for offspring, including neurodevelopmental disorders such as autism spectrum disorder, schizophrenia, and cognitive impairment. Here we review how maternal infection with viruses such as Influenza A, Cytomegalovirus, and Zika during pregnancy can affect the brain development of offspring by promoting the release of maternal pro-inflammatory cytokines, triggering neuroinflammation of the fetal brain, and/or directly infecting fetal neural cells. In addition, we review insights into how these infections impact human brain development from studies with animal models and brain organoids. Finally, we discuss how maternal infection with SARS-CoV-2 may have consequences for neurodevelopment of the offspring.

Clinical Efficacy and Safety of Chinese Patent Medicine Combined with Oseltamivir for the Treatment of Adult Influenza: A Systematic Review and Meta-Analysis

Influenza is a sudden and serious viral breathing and lung-related infectious disease that causes significant deadliness and death worldwide. Now, the international treatment is oseltamivir. Chinese patent medicine (CPM) as a kind of different therapy is used in the treatment of influenza in China. The aim of this study was to interpret the clinical efficacy and safety of CPM combined with oseltamivir in the treatment of adult influenza by reviewing all relevant randomized controlled trials, and to provide new ideas and methods for the treatment of influenza. PubMed, Embase, Cochrane Library, SinoMed, CNKI, and Wanfang Database were searched from the date of beginning until 1 June 2021, for the references on treatment of influenza with CPM. According to standard information extraction tables, two people worked to find and aggregate information independently. Review Manager 5.2 was used to study data carefully and evaluate risk of bias. A total of nine trials of 906 patients were included. Based on the meta-analysis, compared to oseltamivir, CPM combined with oseltamivir had better effect in the time of defervescence [MD = -17.68, 95% CI (-25.93, -9.44), P < 0.0001], the time of symptom improvement [MD = -22.28, 95% CI (-26.77, -17.80), P < 0.00001], and the time of hospitalization [MD = -2.04, 95% CI (-3.45, -0.63), P = 0.005]. Related to safety [RR = 0.69, 95% CI (0.38, 1.23), P = 0.21], the experimental group had fewer adverse reactions than the control group, but there is no statistical significance. The findings show that CPM combined with oseltamivir in adult influenza has a better efficacy in shortening the time of defervescence and symptom improvement, reducing the time of hospitalization. However, publication bias is inevitable due to the low methodological quality check of the clinical research about diagnostic criteria, definition of adult influenza, and small number of articles, and further large sample sizes and multi-center clinical trials are needed to give better proof for its efficacy and safety.

Antiviral effects of azithromycin: A narrative review

Viral infections have a great impact on human health. The urgent need to find a cure against different viruses led us to investigations in a vast range of drugs. Azithromycin (AZT), classified as a macrolide, showed various effects on different known viruses such as severe acute respiratory syndrome coronavirus (SARS-CoV), Zika, Ebola, Enterovirus (EVs) and Rhinoviruses (RVs), and Influenza A previously; namely, these viruses, which caused global concerns, are considered as targets for AZT different actions. Due to AZT background in the treatment of known viral infections mentioned above (which is described in this study), in the early stages of COVID-19 (a new zoonotic disease caused by a novel coronavirus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)) development, AZT drew attention to itself due to its antiviral and immunomodulatory effects as a valuable candidate for COVID-19 treatment. AZT usage instructions for treating different viral infections have always been under observation, and COVID-19 is no exception. There are still debates about the use of AZT in COVID-19 treatment. However, eventually, novel researches convinced WHO to announce the discontinuation of AZT use (alone or in combination with hydroxychloroquine) in treating SARS-CoV-2 infection. This research aims to study the structure of all of the viruses mentioned above and the molecular and clinical effects of AZT against the virus.

Construction of Influenza Early Warning Model Based on Combinatorial Judgment Classifier: A Case Study of Seasonal Influenza in Hong Kong

OBJECTIVE

The annual influenza epidemic is a heavy burden on the health care system, and has increasingly become a major public health problem in some areas, such as Hong Kong (China). Therefore, based on a variety of machine learning methods, and considering the seasonal influenza in Hong Kong, the study aims to establish a Combinatorial Judgment Classifier (CJC) model to classify the epidemic trend and improve the accuracy of influenza epidemic early warning.

METHODS

The characteristic variables were selected using the single-factor statistical method to establish the influencing factor system of an influenza outbreak. On this basis, the CJC model was proposed to provide an early warning for an influenza outbreak. The characteristic variables in the final model included atmospheric pressure, absolute maximum temperature, mean temperature, absolute minimum temperature, mean dew point temperature, the number of positive detections of seasonal influenza viruses, the positive percentage among all respiratory specimens, and the admission rates in public hospitals with a principal diagnosis of influenza.

RESULTS

The accuracy of the CJC model for the influenza outbreak trend reached 96.47%, the sensitivity and specificity change rates of this model were lower than those of other models. Hence, the CJC model has a more stable prediction performance. In the present study, the epidemic situation and meteorological data of Hong Kong in recent years were used as the research objects for the construction of the model index system, and a lag correlation was found between the influencing factors and influenza outbreak. However, some potential risk factors, such as geographical nature and human factors, were not incorporated, which ideally affected the prediction performance to some extent.

CONCLUSION

In general, the CJC model exhibits a statistically better performance, when compared to some classical early warning algorithms, such as Support Vector Machine, Discriminant Analysis, and Ensemble Classfiers, which improves the performance of the early warning of seasonal influenza.

Evaluation of a Rapid Antigen Test for the Diagnosis of SARS-CoV-2 during the COVID-19 Pandemic

Objectives: Reverse transcriptase-polymerase chain reaction (RT-PCR), the reference laboratory method of confirmed SARS-CoV-2 diagnosis, though requiring equipment, is time-consuming. There is a crucial demand for rapid techniques such as antigen detection test during the pandemic. This study assessed whether a rapid antigen detection (RAD) test was an effective and essential method for the early diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the COVID-19 pandemic. The probability of public screening at home and the application of RAD during the novel SARS-CoV-2 outbreak were also topics of interest. Methods: A retrospective analysis based on the systemic screening for COVID-19 was conducted at Taipei City Hospital (TCH) from May 28 to June 06, 2021, the first week of outbreak in Taiwan. The results of the RAD and RT-PCR tests were collected from 5 major branches of the TCH. Results: We collected a total number of 6368 cases. We found that the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy ranged from 60.5% to 78.6% (mean 66.0%), 98.2% to 99.9% (mean 99.0%), 74.4% to 97.8% (mean 82.8%), 94.0% to 98.4% (mean 97.5%), and 93.8% to 98.3% (mean 94.2%), respectively. Although the sensitivity score was not high (up to 95% or higher), the other results were satisfactory, with an accuracy of more than 93% in all branches. Furthermore, it had high specificity, PPV, NPV, and accuracy. Conclusion:We concluded that RAD could be a quick and feasible method to identify individuals infected with SARS-CoV-2 from non-contagious individuals during the COVID-19 outbreak. A RAD test was an effective and essential method for the early diagnosis of SARS-CoV-2 during the COVID-19 pandemic.

Systematic Evolution of Ligands by Exponential Enrichment Technologies and Aptamer-Based Applications: Recent Progress and Challenges in Precision Medicine of Infectious Diseases

Infectious diseases are considered as a pressing challenge to global public health. Accurate and rapid diagnostics tools for early recognition of the pathogen, as well as individualized precision therapy are essential for controlling the spread of infectious diseases. Aptamers, which were screened by systematic evolution of ligands by exponential enrichment (SELEX), can bind to targets with high affinity and specificity so that have exciting potential in both diagnosis and treatment of infectious diseases. In this review, we provide a comprehensive overview of the latest development of SELEX technology and focus on the applications of aptamer-based technologies in infectious diseases, such as targeted drug-delivery, treatments and biosensors for diagnosing. The challenges and the future development in this field of clinical application will also be discussed.

A Biological Insight into the Susceptibility to Influenza Infection in Junior Rats by Comprehensive Analysis of lncRNA Profiles

Long noncoding RNAs (lncRNAs) have been reported to participate in regulating many biological processes, including immune response to influenza A virus (IAV). However, the association between lncRNA expression profiles and influenza infection susceptibility has not been well elucidated. Here, we analyzed the expression profiles of lncRNAs, miRNAs, and mRNAs among IAV-infected adult rat (IAR), normal adult rat (AR), IAV-infected junior rat (IJR), and normal junior rat (JR) by RNA sequencing. Compared with differently expressed lncRNAs (DElncRNAs) between AR and IAR, 24 specific DElncRNAs were found between IJR and JR. Then, based on the fold changes and P value, the top 5 DElncRNAs, including 3 upregulated and 2 downregulated lncRNAs, were chosen to establish a ceRNA network for further disclosing their regulatory mechanisms. To visualize the differentially expressed genes in the ceRNA network, GO and KEGG pathway analysis was performed to further explore their roles in influenza infection of junior rats. The results showed that the downregulated DElncRNA-target genes were mostly enriched in the IL-17 signaling pathway. It indicated that the downregulated lncRNAs conferred the susceptibility of junior rats to IAV via mediating the IL-17 signaling pathway.

Aptamer Applications in Emerging Viral Diseases

Aptamers are single-stranded DNA or RNA molecules which are submitted to a process denominated SELEX. SELEX uses reiterative screening of a random oligonucleotide library to identify high-affinity binders to a chosen target, which may be a peptide, protein, or entire cells or viral particles. Aptamers can rival antibodies in target recognition, and benefit from their non-proteic nature, ease of modification, increased stability, and pharmacokinetic properties. This turns them into ideal candidates for diagnostic as well as therapeutic applications. Here, we review the recent accomplishments in the development of aptamers targeting emerging viral diseases, with emphasis on recent findings of aptamers binding to coronaviruses. We focus on aptamer development for diagnosis, including biosensors, in addition to aptamer modifications for stabilization in body fluids and tissue penetration. Such aptamers are aimed at in vivo diagnosis and treatment, such as quantification of viral load and blocking host cell invasion, virus assembly, or replication, respectively. Although there are currently no in vivo applications of aptamers in combating viral diseases, such strategies are promising for therapy development in the future.

Performance of Diagnostic Model for Differentiating Between COVID-19 and Influenza: A 2-Center Retrospective Study

Background

COVID-19 and influenza share many similarities, such as mode of transmission and clinical symptoms. Failure to distinguish the 2 diseases may increase the risk of transmission. A fast and convenient differential diagnosis between COVID-19 and influenza has significant clinical value, especially for low- and middle-income countries with a shortage of nucleic acid detection kits. We aimed to establish a diagnostic model to differentiate COVID-19 and influenza based on clinical data.

Material/Methods

A total of 493 patients were enrolled in the study, including 282 with COVID-19 and 211 with influenza. All data were collected and reviewed retrospectively. The clinical and laboratory characteristics of all patients were analyzed and compared. We then randomly divided all patients into development sets and validation sets to establish a diagnostic model using multivariate logistic regression analysis. Finally, we validated the diagnostic model using the validation set.

Results

We preliminarily established a diagnostic model for differentiating COVID-19 from influenza that consisted of 5 variables: age, dry cough, fever, white cell count, and D-dimer. The model showed good performance for differential diagnosis.

Conclusions

This initial model including clinical features and laboratory indices effectively differentiated COVID-19 from influenza. Patients with a high score were at a high risk of having COVID-19, while patients with a low score were at a high risk of having influenza. This model could help clinicians quickly identify and isolate cases in the absence of nucleic acid tests, especially during the cocirculation of COVID-19 and influenza. Owing to the study’s retrospective nature, further prospective study is needed to validate the accuracy of the model.

Influenza Vaccination Quality Improvement as a Model for COVID-19 Prophylaxis

Introduction: Many comparisons have been made on the effect and impact of COVID-19 on influenza pandemics of history. Therefore, it is reasonable to infer that the strategies utilized by healthcare providers to improve influenza vaccination rates can similarly be applied to the administration of a COVID-19 vaccine. The purpose of this study was to determine the rationale of low influenza vaccination rates in an urban allergy clinic and how to improve patient education and knowledge regarding the importance of influenza vaccination. A three-year comparison of interventions is presented as well as its application to future COVID-19 vaccinations.

Methods: This study was performed at an outpatient allergy and clinical immunology practice (MSBI) with hospital affiliation in New York City, New York. A quality improvement medical committee was formed to optimize influenza vaccination rates to greater than 71% and established standardized protocols regarding patient intake workflows, vaccine counseling, and documentation. Patient records from four providers were used for this study to compare pre-and post-intervention rates.

Results: 984 patients met inclusion criteria, with a normal distribution of ages (18-80), race, and sex. Average vaccination rates prior to the intervention were 9.25-13.60%. The average vaccination rate after the intervention was 91.34%.

Discussion: The MSBI quality improvement study identified key areas to address in improving influenza vaccination rates. Vaccine hesitancy, public misinformation, and ambivalence surrounding vaccination with egg allergies or during a subcutaneous immunotherapy injection were all topics addressed during the 2018-2019 intervention year. Additional attention was also put toward provider education and standardization of documentation. Shared decision making and intensive education/outreach efforts are needed by physicians and patients alike to overcome vaccine hesitancy. In comparing this to upcoming COVID-19 vaccine challenges, similar barriers will likely also need to be addressed. Greater research is needed to understand patient motivations regarding hesitancy specific to the COVID-19 vaccine.

Conclusion: As evidenced in the yearly battle with influenza and now the COVID-19 pandemic, it has become essential to identify and implement multi-level strategies to maximize vaccination rates, especially amid a global pandemic. With COVID-19 vaccines reaching emergency approval stages, it is important for healthcare providers to start creating workflows and strategies to address patient inquiries. The influenza vaccination quality improvement project presented here can be used as a guideline for future evaluations of COVID-19 vaccination efforts.

Peripheral blood lymphocyte-to-monocyte ratio as a screening marker for influenza infection

Influenza outbreaks occur annually and account for significant morbidity and mortality. The overall burden of influenza infections, in the USA, for the 2017-2018 season, was an estimated 45 million cases, 810 000 hospitalizations and 61 000 deaths. Literature suggests that leukocyte count and differential, particularly lymphopenia and/or monocytosis, can provide diagnostic value for influenza infection. However, studies regarding these findings are limited in the adult population, particularly in the USA. The objective of this study was to determine if lymphocyte-to-monocyte ratio (L:M)<2 can be used as a screening marker for influenza infection. We performed a retrospective analysis of all patients who presented to University of Florida Health, Jacksonville, a university-affiliated tertiary care center in Jacksonville, Florida, between January 2017 and December 2018, with 'influenza-like' symptoms and who were subsequently admitted to the hospital. Patients were divided into two cohorts, based on whether they had laboratory-confirmed influenza versus another confirmed upper respiratory tract viral infection (influenza-like illness (ILI)). L:M was compared between the two groups and was found to be lower in the influenza group compared with the ILI group (p<0.0001). Results of this study demonstrate that a L:M<2 has significant diagnostic value in the acute phase of influenza and can be used for earlier detection and management of this disease, in order to improve clinical outcomes.

Exploring multiple mechanisms of Qingjie Fanggan prescription for prevention and treatment of influenza based on systems pharmacology

Influenza is a type of acute disease characterized by strong contagiousness and short incubation period, which have posed a large potential threat to public health. Traditional Chinese Medicine (TCM) advocates to the aim of combating complex diseases from a holistic view, which has shown effectiveness in anti-influenza. However, the mechanism of TCM prescription remains puzzling. Here, we applied a system pharmacology approach to reveal the underlying molecular mechanisms of Qingjie Fanggan prescription (QFP) in the prevention and treatment of influenza. In this study, we identified 228 potential active compounds by means of absorption, distribution, metabolism, and excretion (ADME) evaluation system and literature research. Then, the targets of the potential active compounds were predicted by using the WES (Weighted Ensemble Similarity) method, and the influenza-related targets were obtained according to some existing gene databases. Next, an herb-component-target network was constructed to further dissect the multi-directional therapeutic approach for QFP. Meanwhile, we also performed gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation analysis on 344 potential targets. Finally, a target-pathway network was constructed to further dissect the core pathways and targets in treatment of influenza for QFP. And the key components and targets were docked by AutoDock Vina to explore their binding mode. All of these demonstrated that QFP had multi-scale curative activity in regulating influenza-related biological processes, which facilitates the application of traditional medicine in modern medicine.

Pediatric SARS, H1N1, MERS, EVALI, and Now Coronavirus Disease (COVID-19) Pneumonia: What Radiologists Need to Know

OBJECTIVE. The purpose of this article is to review new pediatric lung disorders-including disorders that have occurred in recent years years such as severe acute respiratory syndrome (SARS), swine-origin influenza A (H1N1), Middle East respiratory syndrome (MERS), e-cigarette or vaping product use-associated lung injury (EVALI), and coronavirus disease (COVID-19) pneumonia-to enhance understanding of the characteristic imaging findings. CONCLUSION. Although the clinical symptoms of SARS, H1N1, MERS, EVALI, and COVID-19 pneumonia in pediatric patients may be nonspecific, some characteristic imaging findings have emerged or are currently emerging. It is essential for radiologists to have a clear understanding of the characteristic imaging appearances of these lung disorders in pediatric patients to ensure optimal patient care.

Influenza Sentinel Surveillance and Severe Acute Respiratory Infection in a Reference Hospital in Southern Brazil

INTRODUCTION

We report the results of the active surveillance of influenza infections in hospitalized patients and the evaluation of the seasonality and correlation with temperature and rainfall data.

METHODS

During the 2-year study period, 775 patients were tested for 15 respiratory viruses (RVs).

RESULTS

Most of the 57% of (n=444) virus-positive samples were human rhinovirus and respiratory syncytial virus. However, 10.4% (n=46) were influenza virus (80% FluA; 20% FluB). Age and SARI were significantly associated with influenza. FluB circulation was higher is 2013.

CONCLUSIONS

In the post-epidemic period, influenza remains an important cause of hospitalization in SARI patients.

Mortality, morbidity, and hospitalisations due to influenza lower respiratory tract infections, 2017: an analysis for the Global Burden of Disease Study 2017

BACKGROUND

Although the burden of influenza is often discussed in the context of historical pandemics and the threat of future pandemics, every year a substantial burden of lower respiratory tract infections (LRTIs) and other respiratory conditions (like chronic obstructive pulmonary disease) are attributable to seasonal influenza. The Global Burden of Disease Study (GBD) 2017 is a systematic scientific effort to quantify the health loss associated with a comprehensive set of diseases and disabilities. In this Article, we focus on LRTIs that can be attributed to influenza.

METHODS

We modelled the LRTI incidence, hospitalisations, and mortality attributable to influenza for every country and selected subnational locations by age and year from 1990 to 2017 as part of GBD 2017. We used a counterfactual approach that first estimated the LRTI incidence, hospitalisations, and mortality and then attributed a fraction of those outcomes to influenza.

FINDINGS

Influenza LRTI was responsible for an estimated 145 000 (95% uncertainty interval [UI] 99 000-200 000) deaths among all ages in 2017. The influenza LRTI mortality rate was highest among adults older than 70 years (16·4 deaths per 100 000 [95% UI 11·6-21·9]), and the highest rate among all ages was in eastern Europe (5·2 per 100 000 population [95% UI 3·5-7·2]). We estimated that influenza LRTIs accounted for 9 459 000 (95% UI 3 709 000-22 935 000) hospitalisations due to LRTIs and 81 536 000 hospital days (24 330 000-259 851 000). We estimated that 11·5% (95% UI 10·0-12·9) of LRTI episodes were attributable to influenza, corresponding to 54 481 000 (38 465 000-73 864 000) episodes and 8 172 000 severe episodes (5 000 000-13 296 000).

INTERPRETATION

This comprehensive assessment of the burden of influenza LRTIs shows the substantial annual effect of influenza on global health. Although preparedness planning will be important for potential pandemics, health loss due to seasonal influenza LRTIs should not be overlooked, and vaccine use should be considered. Efforts to improve influenza prevention measures are needed.

FUNDING

Bill & Melinda Gates Foundation.

Accurate PCR Detection of Influenza A/B and Respiratory Syncytial Viruses by Use of Cepheid Xpert Flu+RSV Xpress Assay in Point-of-Care Settings: Comparison to Prodesse ProFlu

The Xpert Flu+RSV Xpress Assay is a fast, automated in vitro diagnostic test for qualitative detection and differentiation of influenza A and B viruses and respiratory syncytial virus (RSV) performed on the Cepheid GeneXpert Xpress System. The objective of this study was to establish performance characteristics of the Xpert Flu+RSV Xpress Assay compared to those of the Prodesse ProFlu+ real-time reverse transcription-PCR (RT-PCR) assay (ProFlu+) for the detection of influenza A and B viruses as well as RSV in a Clinical Laboratory Improvement Amendments (CLIA)-waived (CW) setting. Overall, the assay, using fresh and frozen nasopharyngeal (NP) swabs, demonstrated high concordance with results of the ProFlu+ assay in the combined CW and non-CW settings with positive percent agreements (PPA) (100%, 100%, and 97.1%) and negative percent agreements (NPA) (95.2%, 99.5%, and 99.6%) for influenza A and B viruses and RSV, respectively. In conclusion, this multicenter study using the Cepheid Xpert Flu+RSV Xpress Assay demonstrated high sensitivities and specificities for influenza A and B viruses and RSV in ∼60 min for use at the point-of-care in the CW setting.

Genotyping and detection of common avian and human origin-influenza viruses using a portable chemiluminescence imaging microarray

Background

Influenza viruses are divided into three types, A, B, and C. Human influenza A and B viruses can cause seasonal epidemics, but influenza C causes only a mild respiratory illness. Influenza A virus can infect various host species. In 2013, human-infectious avian influenza A (H7N9) was first reported in China. By the second week of 2014, there were 210 laboratory-confirmed human cases in the country, and the mortality rate eventually reached 22 %. Rapid and accurate diagnosis of influenza viruses is important for clinical management and epidemiology.

Methods

In this assay, a cost-effective chemiluminescence (CL) detection oligonucleotide microarray was developed to genotype and detect avian influenza A (H7N9), avian influenza A (H5N1), 2009 influenza A (H1N1), seasonal influenza A (H1N1), and seasonal influenza A (H3N2). Influenza A viruses and influenza B viruses were also generally detected using this microarray.

Results

The results of detection of 40 cultivated influenza virus strains showed that the microarray was able to distinguish the subtypes of these influenza viruses very well. The microarray possessed similar or 10 fold higher limit of detection than the real-time RT-PCR method. Sixty-six clinical swab samples were detected using this microarray and verified with real time RT-PCR to evaluate the efficiency of this microarray for clinical testing.

Conclusions

A reliable CL detection oligonucleotide microarray had been developed to genotype and detected these influenza viruses.

Enhanced detection of respiratory pathogens with nanotrap particles

The Influenza virus is a leading cause of respiratory disease in the United States each year. While the virus normally causes mild to moderate disease, hospitalization and death can occur in many cases. There are several methodologies that are used for detection; however problems such as decreased sensitivity and high rates of false-negative results may arise. There is a crucial need for an effective sample preparation technology that concentrates viruses at low abundance while excluding resident analytes that may interfere with detection. Nanotrap particles are hydrogel particles that are coupled to chemical dye affinity baits that bind a broad range of proteins and virions. Within minutes (<30 minutes), Nanotrap particles concentrate low abundant proteins and viruses from clinically complex matrices. Nanotrap particles with reactive red baits concentrated numerous respiratory viruses including various strains and subtypes of Influenza virus, Coronavirus, and Respiratory Syncytial Virus from saliva, nasal fluid swab specimens, and nasal aspirates. Detection was enhanced more than 10-fold when coupled to plaque assays and qRT-PCR. Importantly, Nanotrap particle can efficiently capture and concentrate multiple viral pathogens during a coinfection scenario. These results collectively demonstrate that Nanotrap particles are an important tool that can easily be integrated into various detection methodologies.

Evaluation of a new, rapid, simple test for the detection of influenza virus

BACKGROUND

Influenza virus infections are responsible for significant morbidity and mortality in both pediatric and adult populations worldwide. Rapid and accurate diagnosis of influenza is necessary for appropriate patient management during the influenza season and for optimal utilization of anti-influenza therapy. We prospectively tested the accuracy of a simple and rapid diagnostic method.

METHODS

Ninety-eight samples (nasal and pharyngeal swabs) from patients with upper respiratory tract infection symptoms who presented to primary healthcare centres in Barcelona (Spain) were prospectively analyzed. The samples were collected as part of influenza surveillance program. Samples that had enough volume to make the new test after aliquoting the amount needed to perform routine tests were included. None of the samples were pre-selected as a result of their status in relation to influenza virus. Samples were analyzed by in-house real-time PCR and Alere i Influenza A & B (Alere i), which uses isothermal amplification of nucleic acids for the qualitative detection of influenza A and B in nasal swabs transported in viral transport media. The two techniques were compared by positive percent agreement (PPA) and negative percent agreement (NPA). Statistical analysis was performed with Stata.

RESULTS

Of the 98 samples analysed 90 were concordant; 46 (46.9%) were positive and 44 (44.9%) were negative. Five samples showed invalid results with the Alere i test and could be not re-tested due to insufficient sample volume and were not included in the final statistical analysis. In the 93 remaining samples, the Alere i test showed 97% of accuracy having correctly classified 90 samples. We obtained discordant results in 3 samples (3%). The PPA was 93.8% for influenza A and 94.1% for influenza B, and NPA was 100% for influenza A and influenza B virus. In addition, the Alere i was very rapid (15 minutes or less) and extremely easy to use.

CONCLUSIONS

The Alere i test provided a good correlation compared to the real-time PCR test for the diagnosis of influenza. Since this method can be performed in minutes, it allows immediate, accurate clinical decisions to prescribe appropriate antiviral treatment or isolation of patients.

Fatal clinical course of probable invasive pulmonary aspergillosis with influenza B infection in an immunocompetent patient

Invasive pulmonary aspergillosis (IPA) is rarely reported in patients who have normal immune function. Recently, IPA risk was reported in nonimmunocompromised hosts, such as patients with chronic obstructive pulmonary disease and critically ill patients in intensive care units. Moreover, influenza infection is also believed to be associated with IPA among immunocompetent patients. However, most reports on IPA with influenza A infection, including pandemic influenza H1N1, and IPA associated with influenza B infection were scarcely reported. Here, we report probable IPA with a fatal clinical course in an immunocompetent patient with influenza B infection. We demonstrate IPA as a possible complication in immunocompetent patients with influenza B infection. Early clinical suspicion of IPA and timely antifungal therapy are required for better outcomes in such cases.

Multicenter clinical evaluation of the novel Alere™ i Influenza A&B isothermal nucleic acid amplification test

BACKGROUND

Rapid detection of influenza infection is important for patient management and timely anti-viral therapy. Rapid antigen detection tests for influenza have inferior sensitivity when compared to nucleic acid-based amplification tests. An isothermal nucleic acid amplification test that offers the potential for rapid molecular testing at the clinical point-of-care with simple equipment can improve influenza detection rates.

OBJECTIVES

To evaluate the performance of Alere™ i Influenza A&B isothermal nucleic acid amplification test to detect influenza A and B in comparison to viral cell culture as reference method.

STUDY DESIGN

A prospective, multicenter, clinical study to evaluate the clinical performance of the Alere™ i Influenza A&B assay in a point-of-care setting using prospectively enrolled specimens from both children and adults was conducted in seven sites.

RESULTS

In comparison with viral cell culture, the overall sensitivity and specificity of the Alere™ i Influenza A&B assay was 97.8% and 85.6% for the detection of influenza A, and 91.8% and 96.3% for the detection of influenza B, respectively. Following resolution of discrepant results by real-time RT-PCR the sensitivity and specificity of the Alere™ i Influenza A&B assay improved to 99.3% and 98.1% for influenza A, and 97.6% and 100% for influenza B, respectively.

CONCLUSIONS

The Alere™ i Influenza A&B isothermal nucleic acid amplification test is an ideal point-of-care test for influenza detection in children and adults due to its high sensitivity and specificity and ability to generate results within 15 min from specimen receipt.

An alphavirus-based adjuvant enhances serum and mucosal antibodies, T cells, and protective immunity to influenza virus in neonatal mice

Neonatal immune responses to infection and vaccination are biased toward TH2 at the cost of proinflammatory TH1 responses needed to combat intracellular pathogens. However, upon appropriate stimulation, the neonatal immune system can induce adult-like TH1 responses. Here we report that a new class of vaccine adjuvant is especially well suited to enhance early life immunity. The GVI3000 adjuvant is a safe, nonpropagating, truncated derivative of Venezuelan equine encephalitis virus that targets dendritic cells (DCs) in the draining lymph node (DLN) and produces intracellular viral RNA without propagating to other cells. RNA synthesis strongly activates the innate immune response so that in adult animals, codelivery of soluble protein antigens induces robust humoral, cellular, and mucosal responses. The adjuvant properties of GVI3000 were tested in a neonatal BALB/c mouse model using inactivated influenza virus (iFlu). After a single immunization, mice immunized with iFlu with the GVI3000 adjuvant (GVI3000-adjuvanted iFlu) had significantly higher and sustained influenza virus-specific IgG antibodies, mainly IgG2a (TH1), compared to the mice immunized with antigen only. GVI3000 significantly increased antigen-specific CD4(+) and CD8(+) T cells, primed mucosal immune responses, and enhanced protection from lethal challenge. As seen in adult mice, the GVI3000 adjuvant increased the DC population in the DLNs, caused activation and maturation of DCs, and induced proinflammatory cytokines and chemokines in the DLNs soon after immunization, including gamma interferon (IFN-γ), tumor necrosis factor alpha (TNF-α), granulocyte colony-stimulating factor (G-CSF), and interleukin 6 (IL-6). In summary, the GVI3000 adjuvant induced an adult-like adjuvant effect with an influenza vaccine and has the potential to improve the immunogenicity and protective efficacy of new and existing neonatal vaccines.

IMPORTANCE

The suboptimal immune responses in early life constitute a significant challenge for vaccine design. Here we report that a new class of adjuvant is safe and effective for early life immunization and demonstrate its ability to significantly improve the protective efficacy of an inactivated influenza virus vaccine in a neonatal mouse model. The GVI3000 adjuvant delivers a truncated, self-replicating viral RNA into dendritic cells in the draining lymph node. Intracellular RNA replication activates a strong innate immune response that significantly enhances adaptive antibody and cellular immune responses to codelivered antigens. A significant increase in protection results from a single immunization. Importantly, this adjuvant also primed a mucosal IgA response, which is likely to be critical for protection during many early life infections.

The use of Nanotrap particles for biodefense and emerging infectious disease diagnostics

Detection of early infectious disease may be challenging due to the low copy number of organisms present. To overcome this limitation and rapidly measure low concentrations of the pathogen, we developed a novel technology: Nanotrap particles, which are designed to capture, concentrate, and protect biomarkers from complex biofluids. Nanotrap particles are thermoresponsive hydrogels that are capable of antigen capture through the coupling of affinity baits to the particles. Here, we describe recent findings demonstrating that Nanotrap particles are able to capture live infectious virus, viral RNA, and viral proteins. Capture is possible even in complex mixtures such as serum and allows the concentration and protection of these analytes, providing increased performance of downstream assays. The Nanotrap particles are a versatile sample preparation technology that has far reaching implications for biomarker discovery and diagnostic assays.