Differential interferon responses to influenza A and B viruses in primary ferret respiratory epithelial cells.

Influenza B viruses (IBV) cocirculate with influenza A viruses (IAV) and cause periodic epidemics of disease, yet antibody and cellular responses following IBV infection are less well understood. Using the ferret model for antisera generation for influenza surveillance purposes, IAV resulted in robust antibody responses following infection, whereas IBV required an additional booster dose, over 85% of the time, to generate equivalent antibody titers. In this study, we utilized primary differentiated ferret nasal epithelial cells (FNECs) which were inoculated with IAV and IBV to study differences in innate immune responses which may result in differences in adaptive immune responses in the host. FNECs were inoculated with IAV (H1N1pdm09 and H3N2 subtypes) or IBV (B/Victoria and B/Yamagata lineages) and assessed for 72 h. Cells were analyzed for gene expression by quantitative real-time PCR, and apical and basolateral supernatants were assessed for virus kinetics and interferon (IFN), respectively. Similar virus kinetics were observed with IAV and IBV in FNECs. A comparison of gene expression and protein secretion profiles demonstrated that IBV-inoculated FNEC expressed delayed type-I/II IFN responses and reduced type-III IFN secretion compared to IAV-inoculated cells. Concurrently, gene expression of Thymic Stromal Lymphopoietin (TSLP), a type-III IFN-induced gene that enhances adaptive immune responses, was significantly downregulated in IBV-inoculated FNECs. Significant differences in other proinflammatory and adaptive genes were suppressed and delayed following IBV inoculation. Following IBV infection, ex vivo cell cultures derived from the ferret upper respiratory tract exhibited reduced and delayed innate responses which may contribute to reduced antibody responses in vivo.IMPORTANCEInfluenza B viruses (IBV) represent nearly one-quarter of all human influenza cases and are responsible for significant clinical and socioeconomic impacts but do not pose the same pandemic risks as influenza A viruses (IAV) and have thus received much less attention. IBV accounts for greater severity and deaths in children, and vaccine efficacy remains low. The ferret can be readily infected with human clinical isolates and demonstrates a similar course of disease and immune responses. IBV, however, generates lower antibodies in ferrets than IAV following the challenge. To determine whether differences in initial innate responses following infection may affect the development of robust adaptive immune responses, ferret respiratory tract cells were isolated, infected with IAV/IBV, and compared. Understanding the differences in the initial innate immune responses to IAV and IBV may be important in the development of more effective vaccines and interventions to generate more robust protective immune responses.

Changes in Influenza and Other Respiratory Virus Activity During the COVID-19 Pandemic - United States, 2020-2021.

The COVID-19 pandemic and subsequent implementation of nonpharmaceutical interventions (e.g., cessation of global travel, mask use, physical distancing, and staying home) reduced transmission of some viral respiratory pathogens (1). In the United States, influenza activity decreased in March 2020, was historically low through the summer of 2020 (2), and remained low during October 2020-May 2021 (<0.4% of respiratory specimens with positive test results for each week of the season). Circulation of other respiratory pathogens, including respiratory syncytial virus (RSV), common human coronaviruses (HCoVs) types OC43, NL63, 229E, and HKU1, and parainfluenza viruses (PIVs) types 1-4 also decreased in early 2020 and did not increase until spring 2021. Human metapneumovirus (HMPV) circulation decreased in March 2020 and remained low through May 2021. Respiratory adenovirus (RAdV) circulated at lower levels throughout 2020 and as of early May 2021. Rhinovirus and enterovirus (RV/EV) circulation decreased in March 2020, remained low until May 2020, and then increased to near prepandemic seasonal levels. Circulation of respiratory viruses could resume at prepandemic levels after COVID-19 mitigation practices become less stringent. Clinicians should be aware of increases in some respiratory virus activity and remain vigilant for off-season increases. In addition to the use of everyday preventive actions, fall influenza vaccination campaigns are an important component of prevention as COVID-19 mitigation measures are relaxed and schools and workplaces resume in-person activities.

Effect of Priming With Seasonal Influenza A(H3N2) Virus on the Prevalence of Cross-Reactive Hemagglutination-Inhibition Antibodies to Swine-Origin A(H3N2) Variants.

Background: Recent outbreaks of swine-origin influenza A(H3N2) variant (H3N2v) viruses have raised public health concerns. Previous studies indicated that older children and young adults had the highest levels of hemagglutination-inhibition (HI) antibodies to 2010-2011 H3N2v viruses. However, newly emerging 2013 H3N2v have acquired antigenic mutations in the hemagglutinin at amino acid position 145 (N145K/R). We estimated the levels of serologic cross-reactivity among humans primed with seasonal influenza A(H3N2) (sH3N2), using postinfection ferret antisera. We also explored age-related HI antibody responses to 2012-2013 H3N2v viruses. Methods: Human and ferret antisera were tested in HI assays against 1 representative 2012 H3N2v (145N) and 2 2013 H3N2v (145K/R) viruses, together with 9 sH3N2 viruses circulating since 1968. Results: Low levels of cross-reactivity between the H3N2v and sH3N2 viruses from the 1970s-1990s were observed using postinfection ferret antisera. The overall seroprevalence among the sH3N2-primed population against 2012-2013 H3N2v viruses was >50%, and age-related seroprevalence was observed. Seroprevalence was significantly higher to 2013 H3N2v than to 2012 H3N2v viruses among some children likely to have been primed with A/Sydney/5/97-like (145K) or A/Wuhan/359/95-like viruses (145K). Conclusions: A single substitution (N145K/R) was sufficient to affect seropositivity to H3N2v viruses in some individuals. Insight into age-related antibody responses to newly emerging H3N2v viruses is critical for risk assessment and pandemic preparedness.

Ebola Laboratory Response at the Eternal Love Winning Africa Campus, Monrovia, Liberia, 2014-2015.

West Africa experienced the first epidemic of Ebola virus infection, with by far the greatest number of cases in Guinea, Sierra Leone, and Liberia. The unprecedented epidemic triggered an unparalleled response, including the deployment of multiple Ebola treatment units and mobile/field diagnostic laboratories. The National Institute of Allergy and Infectious Diseases and the Centers for Disease Control and Prevention deployed a joint laboratory to Monrovia, Liberia, in August 2014 to support the newly founded Ebola treatment unit at the Eternal Love Winning Africa (ELWA) campus. The laboratory operated initially out of a tent structure but quickly moved into a fixed-wall building owing to severe weather conditions, the need for increased security, and the high sample volume. Until May 2015, when the laboratory closed, the site handled close to 6000 clinical specimens for Ebola virus diagnosis and supported the medical staff in case patient management. Laboratory operation and safety, as well as Ebola virus diagnostic assays, are described and discussed; in addition, lessons learned for future deployments are reviewed.

Plasmodium Parasitemia Associated With Increased Survival in Ebola Virus-Infected Patients.

BACKGROUND: The ongoing Ebola outbreak in West Africa has resulted in 28 646 suspected, probable, and confirmed Ebola virus infections. Nevertheless, malaria remains a large public health burden in the region affected by the outbreak. A joint Centers for Disease Control and Prevention/National Institutes of Health diagnostic laboratory was established in Monrovia, Liberia, in August 2014, to provide laboratory diagnostics for Ebola virus. METHODS: All blood samples from suspected Ebola virus-infected patients admitted to the Médecins Sans Frontières ELWA3 Ebola treatment unit in Monrovia were tested by quantitative real-time polymerase chain reaction for the presence of Ebola virus and Plasmodium species RNA. Clinical outcome in laboratory-confirmed Ebola virus-infected patients was analyzed as a function of age, sex, Ebola viremia, and Plasmodium species parasitemia. RESULTS: The case fatality rate of 1182 patients with laboratory-confirmed Ebola virus infections was 52%. The probability of surviving decreased with increasing age and decreased with increasing Ebola viral load. Ebola virus-infected patients were 20% more likely to survive when Plasmodium species parasitemia was detected, even after controlling for Ebola viral load and age; those with the highest levels of parasitemia had a survival rate of 83%. This effect was independent of treatment with antimalarials, as this was provided to all patients. Moreover, treatment with antimalarials did not affect survival in the Ebola virus mouse model. CONCLUSIONS: Plasmodium species parasitemia is associated with an increase in the probability of surviving Ebola virus infection. More research is needed to understand the molecular mechanism underlying this remarkable phenomenon and translate it into treatment options for Ebola virus infection.

The Merits of Malaria Diagnostics during an Ebola Virus Disease Outbreak.

Malaria is a major public health concern in the countries affected by the Ebola virus disease epidemic in West Africa. We determined the feasibility of using molecular malaria diagnostics during an Ebola virus disease outbreak and report the incidence of Plasmodium spp. parasitemia in persons with suspected Ebola virus infection.

Interferon as an immunoadjuvant to enhance antibodies following influenza B infection and vaccination in ferrets.

Despite annual vaccination, influenza B viruses (IBV) continue to cause significant morbidity and mortality in humans. We have found that IBV infection resulted in a weaker innate and adaptive immune response than influenza A viruses (IAV) in ferrets. To understand and overcome the weak immune responses to IBV in ferrets, we administered type-I or type-III interferon (IFN) to ferrets following infection or vaccination and evaluated their effects on the immune response. IFN signaling following viral infection plays an important role in the initial innate immune response and affects subsequent adaptive immune responses. In the respiratory tract, IFN lambda (IFNL) has regulatory effects on adaptive immunity indirectly through thymic stromal lymphopoietin (TSLP), which then acts on immune cells to stimulate the adaptive response. Following IBV infection or vaccination, IFN treatment (IFN-Tx) upregulated gene expression of early inflammatory responses in the upper respiratory tract and robust IFN, TSLP, and inflammatory responses in peripheral blood cells. These responses were sustained following challenge or vaccination in IFN-Tx animals. Serum IFNL and TSLP levels were enhanced in IFN-Tx animals following challenge/rechallenge over mock-Tx; however, this difference was not observed following vaccination. Antibody responses in serum of IFN-Tx animals following IBV infection or vaccination increased more quickly and to higher titers and were sustained longer than mock-Tx animals over 3 months. Following rechallenge of infected animals 3 months post treatment, antibody levels remained higher than mock-Tx. However, IFN-Tx did not have an effect on antibody responses following challenge of vaccinated animals. A strong direct correlation was found between TSLP levels and antibody responses following challenge-rechallenge and vaccination-challenge indicating it as a useful tool for predicting adaptive immune responses following IBV infection or vaccination. The effects of IFN on strengthening both innate and adaptive responses to IBV may aid in development of more effective treatments following infection and improved influenza vaccines.

Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States.

Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here, we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997-2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection ynamics, presumably via heterosubtypic cross-immunity.

Seasonal influenza (flu) viruses cause outbreaks every winter. People infected with influenza typically develop mild respiratory symptoms. But flu infections can cause serious illness in young children, older adults and people with chronic medical conditions. Infected or vaccinated individuals develop some immunity, but the viruses evolve quickly to evade these defenses in a process called antigenic drift. As the viruses change, they can re-infect previously immune people. Scientists update the flu vaccine yearly to keep up with this antigenic drift. The immune system fights flu infections by recognizing two proteins, known as antigens, on the virus's surface, called hemagglutinin (HA) and neuraminidase (NA). However, mutations in the genes encoding these proteins can make them unrecognizable, letting the virus slip past the immune system. Scientists would like to know how these changes affect the size, severity and timing of annual influenza outbreaks. Perofsky et al. show that tracking genetic changes in HA and NA may help improve flu season predictions. The experiments compared the severity of 22 flu seasons caused by the A(H3N2) subtype in the United States with how much HA and NA had evolved since the previous year. The A(H3N2) subtype experiences the fastest rates of antigenic drift and causes more cases and deaths than other seasonal flu viruses. Genetic changes in HA and NA were a better predictor of A(H3N2) outbreak severity than the blood tests for protective antibodies that epidemiologists traditionally use to track flu evolution. However, the prevalence of another subtype of influenza A circulating in the population, called A(H1N1), was an even better predictor of how severe A(H3N2) outbreaks would be. Perofsky et al. are the first to show that genetic changes in NA contribute to the severity of flu seasons. Previous studies suggested a link between genetic changes in HA and flu season severity, and flu vaccines include the HA protein to help the body recognize new influenza strains. The results suggest that adding the NA protein to flu vaccines may improve their effectiveness. In the future, flu forecasters may want to analyze genetic changes in both NA and HA to make their outbreak predictions. Tracking how much of the A(H1N1) subtype is circulating may also be useful for predicting the severity of A(H3N2) outbreaks.

Assembly, activation, and substrate specificity of cyclin D1/Cdk2 complexes.

Previous studies have shown conflicting data regarding cyclin D1/cyclin-dependent kinase 2 (Cdk2) complexes, and considering the widespread overexpression of cyclin D1 in cancer, it is important to fully understand their relevance. While many have shown that cyclin D1 and Cdk2 form active complexes, others have failed to show activity or association. Here, using a novel p21-PCNA fusion protein as well as p21 mutant proteins, we show that p21 is a required scaffolding protein, with cyclin D1 and Cdk2 failing to complex in its absence. These p21/cyclin D1/Cdk2 complexes are active and also bind the trimeric PCNA complex, with each trimer capable of independently binding distinct cyclin/Cdk complexes. We also show that increased p21 levels due to treatment with chemotherapeutic agents result in increased formation and kinase activity of cyclin D1/Cdk2 complexes, and that cyclin D1/Cdk2 complexes are able to phosphorylate a number of substrates in addition to Rb. Nucleophosmin and Cdh1, two proteins important for centrosome replication and implicated in the chromosomal instability of cancer, are shown to be phosphorylated by cyclin D1/Cdk2 complexes. Additionally, polypyrimidine tract binding protein-associated splicing factor (PSF) is identified as a novel Cdk2 substrate, being phosphorylated by Cdk2 complexed with either cyclin E or cyclin D1, and given the many functions of PSF, it could have important implications on cellular activity.

Seasonal H1N1 influenza virus infection induces cross-protective pandemic H1N1 virus immunity through a CD8-independent, B cell-dependent mechanism.

During the 2009 H1N1 influenza virus pandemic (pdmH1N1) outbreak, it was found that most individuals lacked antibodies against the new pdmH1N1 virus, and only the elderly showed anti-hemagglutinin (anti-HA) antibodies that were cross-reactive with the new strains. Different studies have demonstrated that prior contact with the virus can confer protection against strains with some degree of dissimilarity; however, this has not been sufficiently explored within the context of a pdmH1N1 virus infection. In this study, we have found that a first infection with the A/Brisbane/59/2007 virus strain confers heterologous protection in ferrets and mice against a subsequent pdmH1N1 (A/Mexico/4108/2009) virus infection through a cross-reactive but non-neutralizing antibody mechanism. Heterologous immunity is abrogated in B cell-deficient mice but maintained in CD8(-/-) and perforin-1(-/-) mice. We identified cross-reactive antibodies from A/Brisbane/59/2007 sera that recognize non-HA epitopes in pdmH1N1 virus. Passive serum transfer showed that cross-reactive sH1N1-induced antibodies conferred protection in naive recipient mice during pdmH1N1 virus challenge. The presence or absence of anti-HA antibodies, therefore, is not the sole indicator of the effectiveness of protective cross-reactive antibody immunity. Measurement of additional antibody repertoires targeting the non-HA antigens of influenza virus should be taken into consideration in assessing protection and immunization strategies. We propose that preexisting cross-protective non-HA antibody immunity may have had an overall protective effect during the 2009 pdmH1N1 outbreak, thereby reducing disease severity in human infections.

Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States.

Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997-2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection dynamics, presumably via heterosubtypic cross-immunity.

Ferrets as a model for tuberculosis transmission.

Even with the COVID-19 pandemic, tuberculosis remains a leading cause of human death due to a single infectious agent. Until successfully treated, infected individuals may continue to transmit Mycobacterium tuberculosis bacilli to contacts. As with other respiratory pathogens, such as SARS-CoV-2, modeling the process of person-to-person transmission will inform efforts to develop vaccines and therapies that specifically impede disease transmission. The ferret (Mustela furo), a relatively inexpensive, small animal has been successfully employed to model transmissibility, pathogenicity, and tropism of influenza and other respiratory disease agents. Ferrets can become naturally infected with Mycobacterium bovis and are closely related to badgers, well known in Great Britain and elsewhere as a natural transmission vehicle for bovine tuberculosis. Herein, we report results of a study demonstrating that within 7 weeks of intratracheal infection with a high dose (>5 x 103 CFU) of M. tuberculosis bacilli, ferrets develop clinical signs and pathological features similar to acute disease reported in larger animals, and ferrets infected with very-high doses (>5 x 104 CFU) develop severe signs within two to four weeks, with loss of body weight as high as 30%. Natural transmission of this pathogen was also examined. Acutely-infected ferrets transmitted M. tuberculosis bacilli to co-housed naïve sentinels; most of the sentinels tested positive for M. tuberculosis in nasal washes, while several developed variable disease symptomologies similar to those reported for humans exposed to an active tuberculosis patient in a closed setting. Transmission was more efficient when the transmitting animal had a well-established acute infection. The findings support further assessment of this model system for tuberculosis transmission including the testing of prevention measures and vaccine efficacy.

Molecular characterization of in vivo adjuvant activity in ferrets vaccinated against influenza virus.

The 2009 H1N1 influenza pandemic has prompted a significant need for the development of efficient, single-dose, adjuvanted vaccines. Here we investigated the adjuvant potential of CpG oligodeoxynucleotide (ODN) when used with a human seasonal influenza virus vaccine in ferrets. We found that the CpG ODN-adjuvanted vaccine effectively increased antibody production and activated type I interferon (IFN) responses compared to vaccine alone. Based on these findings, pegylated IFN-alpha2b (PEG-IFN) was also evaluated as an adjuvant in comparison to CpG ODN and complete Freund's adjuvant (CFA). Our results showed that all three vaccines with adjuvant added prevented seasonal human A/Brisbane/59/2007 (H1N1) virus replication more effectively than did vaccine alone. Gene expression profiles indicated that, as well as upregulating IFN-stimulated genes (ISGs), CpG ODN enhanced B-cell activation and increased Toll-like receptor 4 (TLR4) and IFN regulatory factor 4 (IRF4) expression, whereas PEG-IFN augmented adaptive immunity by inducing major histocompatibility complex (MHC) transcription and Ras signaling. In contrast, the use of CFA as an adjuvant induced limited ISG expression but increased the transcription of MHC, cell adhesion molecules, and B-cell activation markers. Taken together, our results better characterize the specific molecular pathways leading to adjuvant activity in different adjuvant-mediated influenza virus vaccinations.

Machine learning for the life-time risk prediction of Alzheimer's disease: a systematic review.

Alzheimer's disease is a neurodegenerative disorder and the most common form of dementia. Early diagnosis may assist interventions to delay onset and reduce the progression rate of the disease. We systematically reviewed the use of machine learning algorithms for predicting Alzheimer's disease using single nucleotide polymorphisms and instances where these were combined with other types of data. We evaluated the ability of machine learning models to distinguish between controls and cases, while also assessing their implementation and potential biases. Articles published between December 2009 and June 2020 were collected using Scopus, PubMed and Google Scholar. These were systematically screened for inclusion leading to a final set of 12 publications. Eighty-five per cent of the included studies used the Alzheimer's Disease Neuroimaging Initiative dataset. In studies which reported area under the curve, discrimination varied (0.49-0.97). However, more than half of the included manuscripts used other forms of measurement, such as accuracy, sensitivity and specificity. Model calibration statistics were also found to be reported inconsistently across all studies. The most frequent limitation in the assessed studies was sample size, with the total number of participants often numbering less than a thousand, whilst the number of predictors usually ran into the many thousands. In addition, key steps in model implementation and validation were often not performed or unreported, making it difficult to assess the capability of machine learning models.

Effects of a transsphenoidal surgery quality improvement program on patient outcomes and hospital financial performance.

OBJECTIVE: A comprehensive quality improvement (QI) program aimed at all aspects of patient care after pituitary surgery was initiated at a single center. This initiative was guided by standard quality principles to improve patient outcomes and optimize healthcare value. The programmatic goal was to discharge most elective patients within 1 day after surgery, improve patient safety, and limit unplanned readmissions. The program is described, and its effect on patient outcomes and hospital financial performance over a 5-year period are investigated. METHODS: Details of the patient care pathway are presented. Foundational elements of the QI program include evidence-based care pathways (e.g., for hyponatremia and pain), an in-house research program designed to fortify care pathways, patient education, expectation setting, multidisciplinary team care, standard order sets, high-touch postdischarge care, outcomes auditing, and a patient navigator, among other elements. Length of stay (LOS), outcome variability, 30-day unplanned readmissions, and hospital financial performance were identified as surrogate endpoints for healthcare value for the surgical epoch. To assess the effect of these protocols, all patients undergoing elective transsphenoidal surgery for pituitary tumors and Rathke's cleft cysts between January 2015 and December 2019 were reviewed. RESULTS: A total of 609 adult patients who underwent elective surgery by experienced pituitary surgeons were identified. Patient demographics, comorbidities, and payer mix did not change significantly over the study period (p ≥ 0.10). The mean LOS was significantly shorter in 2019 versus 2015 (1.6 ± 1.0 vs 2.9 ± 2.2 midnights, p < 0.001). The percentage of patients discharged after 1 midnight was significantly higher in 2019 versus 2015 (75.4% vs 15.6%, p < 0.001). The 30-day unplanned hospital readmission rate decreased to 2.8% in 2019 from 8.3% in 2015. Per-patient hospital profit increased 71.3% ($10,613 ± $19,321 in 2015; $18,180 ± $21,930 in 2019), and the contribution margin increased 42.3% ($18,925 ± $19,236 in 2015; $26,939 ± $22,057 in 2019), while costs increased by only 3.4% ($18,829 ± $6611 in 2015; $19,469 ± $4291 in 2019). CONCLUSIONS: After implementation of a comprehensive pituitary surgery QI program, patient outcomes significantly improved, outcome variability decreased, and hospital financial performance was enhanced. Future studies designed to evaluate disease remission, patient satisfaction, and how the surgeon learning curve may synergize with other quality efforts may provide additional context.

A novel class of cyclin-dependent kinase inhibitors identified by molecular docking act through a unique mechanism.

The cyclin-dependent kinase (Cdk) family is emerging as an important therapeutic target in the treatment of cancer. Cdks 1, 2, 4, and 6 are the key members that regulate the cell cycle, as opposed to Cdks that control processes such as transcription (Cdk7 and Cdk9). For this reason, Cdks 1, 2, 4, and 6 have been the subject of extensive cell cycle-related research, and consequently many inhibitors have been developed to target these proteins. However, the compounds that comprise the current list of Cdk inhibitors are largely ATP-competitive. Here we report the identification of a novel structural site on Cdk2, which is well conserved between the cell cycle Cdks. Small molecules identified by a high throughput in silico screen of this pocket exhibit cytostatic effects and act by reducing the apparent protein levels of cell cycle Cdks. Drug-induced cell cycle arrest is associated with decreased Rb phosphorylation and decreased expression of E2F-dependent genes. Multiple lines of evidence indicate that the primary mechanism of action of these compounds is the direct induction of Cdk1, Cdk2, and Cdk4 protein aggregation.

In vivo ribavirin activity against severe pandemic H1N1 Influenza A/Mexico/4108/2009.

The use of ribavirin in influenza treatment is a matter of debate. Due to adamantine- and oseltamivir-resistant strains of the current pandemic H1N1 (pdmH1N1) influenza viruses, the demand for alternative antiviral treatments has increased. This study demonstrated the potent antiviral effects of ribavirin in a mouse model of pdmH1N1 influenza infection (A/Mexico/4108/2009). It was found that treatment with 40 mg ribavirin kg⁻¹ day⁻¹ partially protected the animals if initiated immediately upon infection. Administration of similar concentrations on subsequent days or immediate therapy with lower doses efficiently delayed disease progression. Correlation studies showed a direct relationship between low viral titres in the lung during the early stages of infection with animal survival in ribavirin-treated animals. Reduced lung pathology in animals treated with ribavirin following infection also indicated the importance of immediate treatment. This study revealed the antiviral properties of ribavirin and these results justify comprehensive clinical studies for the use of ribavirin against influenza virus in future outbreaks.

Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution.

Seasonal influenza virus A/H3N2 is a major cause of death globally. Vaccination remains the most effective preventative. Rapid mutation of hemagglutinin allows viruses to escape adaptive immunity. This antigenic drift necessitates regular vaccine updates. Effective vaccine strains need to represent H3N2 populations circulating one year after strain selection. Experts select strains based on experimental measurements of antigenic drift and predictions made by models from hemagglutinin sequences. We developed a novel influenza forecasting framework that integrates phenotypic measures of antigenic drift and functional constraint with previously published sequence-only fitness estimates. Forecasts informed by phenotypic measures of antigenic drift consistently outperformed previous sequence-only estimates, while sequence-only estimates of functional constraint surpassed more comprehensive experimentally-informed estimates. Importantly, the best models integrated estimates of both functional constraint and either antigenic drift phenotypes or recent population growth.

Vaccination is the best protection against seasonal flu. It teaches the immune system what the flu virus looks like, preparing it to fight off an infection. But the flu virus changes its molecular appearance every year, escaping the immune defences learnt the year before. So, every year, the vaccine needs updating. Since it takes almost a year to design and make a new flu vaccine, researchers need to be able to predict what flu viruses will look like in the future. Currently, this prediction relies on experiments that assess the molecular appearance of flu viruses, a complex and slow approach. One alternative is to examine the virus's genetic code. Mathematical models try to predict which genetic changes might alter the appearance of a flu virus, saving the cost of performing specialised experiments. Recent research has shown that these models can make good predictions, but including experimental measures of the virus' appearance could improve them even further. This could help the model to work out which genetic changes are likely to be beneficial to the virus, and which are not. To find out whether experimental data improves model predictions, Huddleston et al. designed a new forecasting tool which used 25 years of historical data from past flu seasons. Each forecast predicted what the virus population might look like the next year using the previous year's genetic code, experimental data, or both. Huddleston et al. then compared the predictions with the historical data to find the most useful data types. This showed that the best predictions combined changes from the virus's genetic code with experimental measures of its appearance. This new forecasting tool is open source, allowing teams across the world to start using it to improve their predictions straight away. Seasonal flu infects between 5 and 15% of the world's population every year, causing between quarter of a million and half a million deaths. Better predictions could lead to better flu vaccines and fewer illnesses and deaths.