National Influenza Center

ObjectivesOur previous study in hospitalised patients infected with avian A(H7N9) influenza virus identified CD84 amongst several genes associated with recovery. Yet, the correlation between CD84 and respiratory viral infection outcomes is far from established. We aimed to define CD84 dynamics in patient cohorts of respiratory disease and immune cell populations in influenza virus‐infected mice.MethodsExpression dynamics of CD84 and association with previously identified correlates of severe and fatal respiratory disease outcomes, OLAH and IL18R1, were analysed in A(H7N9) and COVID‐19 patient cohorts across disease severities. Using mouse models of influenza virus infection, CD84 expression on immune cell subsets was analysed over the course of infection.ResultsElevated CD84 levels in recovered A(H7N9) patients were accompanied by increased expression of genes for CD84‐associated adaptor proteins and other SLAM receptor family members. In these patients, high CD84 expression persisted until discharge, while remaining low throughout the disease in patients that succumbed. We found inverse correlations between CD84 with OLAH and IL18R1 levels in our A(H7N9) cohort, and in hospitalised COVID‐19 patients across respiratory disease severities. In influenza virus‐infected mice, CD84 was upregulated on a broad range of immune cell populations, particularly on activated and influenza virus‐specific T‐cell populations and correlated with less disease severity.ConclusionOur findings revealed the link between high CD84 expression in humans and recovery from respiratory viral infections. In mice, CD84 expression increased across a broad range of immune cell populations, with CD84 expression on activated T‐cell populations correlating with less severe disease.

Emerging avian avulaviruses (AVVs) have been identified in Antarctic ecosystems; however, their biological properties and current circulation remain poorly understood. This study utilized historical egg-isolated Antarctic penguin avulavirus strains (AVV17, AVV18, and AVV19) and combined molecular characterization with field surveillance during the 2024-2025 Antarctic season. The historical isolates were molecularly confirmed using RT-qPCR targeting the L gene, confirming their classification as AVV17, AVV18, or AVV19. These isolates were tested for replication indicators in REM 134, MDCK cells and embryonated chicken eggs. Only AVV18 showed evidence of productive replication in REM 134 cells, as indicated by decreasing Ct values and the presence of cytopathic effects.AVV17 and AVV19 were detectable by RT-qPCR but did not exhibit cytopathic changes or replication dynamics. None of the viruses replicated efficiently in MDCK cells. Further propagation of AVV18 in embryonated chicken eggs showed viral amplification in some eggs. Concurrent surveillance at five sites in the South Shetland Islands detected low-level circulation of AVV17-19, exclusively in cloacal swabs, with no viral RNA found in environmental samples. These findings link historical isolates to current circulation, highlighting selective replication among Antarctic AVVs and limited ecological spread in penguin hosts.

Los continuos avances en el uso de las nuevas tecnologías en la vida cotidiana han repercutido en la concepción general de la prueba en el proceso civil. A través del presente artículo se defiende el surgimiento de una nueva fuente de prueba, la prueba digital, que es una prueba con autonomía propia porque su naturaleza y los problemas asociados a la misma son diferentes a los hasta ahora existentes. Intentaremos dar una visión general sobre el panorama al que se enfrentarán los tribunales los próximos años.

The article analyzes the economic and structural transformations in the Russian media industry driven by the implementation of generative artificial intelligence (AI) technologies. The study aims to identify key changes and characterize the new business models emerging from them. The methodology includes case studies of leading market players, content analysis of industry publications, and analysis of expert opinions. It is established that in the current stage (2022–2025), the optimization model of AI use prevails, focusing on cost reduction in production cycles rather than on creating breakthrough products. A key feature of the Russian market is the formation of strong technological ecosystems (Sber, Yandex), which leads to increased market concentration. Simultaneously, the accessibility of AI tools promotes the “democratization” of content production at the grassroots level, creating new market niches. The conclusion is drawn about the dual nature of the transformation: market polarization between large ecosystem players and numerous independent niche producers.

Abstract Background Uganda is East Africa’s leading producer of pork, yet data on swine respiratory pathogens remains limited, particularly at the wildlife-livestock interfaces of the Albertine Rift region. Here we assessed the seroprevalence, and risk factors of six key pathogens associated with Porcine Respiratory Disease Complex (PRDC) — Porcine Reproductive and Respiratory Syndrome Virus (PRRSV), Swine Influenza Virus (SIV), Porcine Circovirus Type 2 (PCV2), Porcine Adenovirus (ADV), Porcine Parvovirus (PPV), and Mycoplasma hyopneumoniae (MH) —in this high-risk ecosystem. Results Data from 90 pig herds across 11 districts revealed high prevalence rates for SIV (82.2%), PCV2 (70.0%), and PPV (62.7%); moderate for MH (18.9%), low for ADV (1.1%) andan absence of PRRSV. Risk factors linked to high pathogen prevalence included boar sharing, lack of perimeter fencing, and inadequate equipment hygiene. Results also showed that scavenging restrictions were protective against MH. The absence of PRRSV may reflect epidemiological isolation from high-density pig areas in central Uganda, though high within-region contact rates suggest vulnerability to rapid spread if introduced. Conclusion This study establishes critical baseline data for swine respiratory pathogens in western Uganda, highlights the Albertine region as a potential hotspot for pathogen emergence, and emphasizes the need for surveillance, farmer training, and biosecurity interventions to protect pig health and productivity.

ABSTRACT Reliable large-scale testing for respiratory viruses, including influenza viruses, coronaviruses, such as SARS-CoV-2, and respiratory syncytial virus (RSV) is essential for both endemic surveillance and pandemic response. While RT-qPCR remains the current gold standard, the COVID-19 pandemic highlighted the need for alternative, scalable detection platforms. Although alternative approaches like liquid chromatography coupled with mass spectrometry (LC-MS) are well-suited for viral multiplexing, they have yet to undergo clinical validation. Here, we present a quantitative immuno-multiple reaction monitoring (iMRM) assay, called Winterplex, for the simultaneous detection of influenza A, influenza B, RSV, and SARS-CoV-2, each targeted via two proteotypic peptides per virus. The method was validated according to ISO standards for in vitro diagnostics and benchmarked against RT-qPCR. To enhance future pandemic preparedness, urgent investment is needed to translate and expand multiplexed MS-based diagnostic methodologies, which offer the flexibility to incorporate a wide range of targets, making them ideally suited for rapid and adaptable responses to emerging viral threats.

Abstract The continued emergence of new SARS-CoV-2 variants with increased transmissibility and immunoevasive properties highlights the necessity to complement genomic pathogen surveillance with epidemiological data and laboratory-based evaluation of virus variants. Throughout this study, we analyzed over 4,500 SARS-CoV-2 genomes gathered from a nationwide laboratory network from December 1st, 2021, to April 30th, 2023. Lineage assignments revealed ongoing dynamic viral evolution in this advanced phase of the COVID-19 pandemic with subsequent replacements of dominant variants from Delta to Omicron lineages BA.1, BA.2, BA.5.1, and BQ.1, to XBB recombinants. Case-based data analysis showed a higher incidence of BA.2 infections in children compared to other lineages within the same age groups. Furthermore, a multivariable logistic regression model identified male sex and increasing age as significant predictors of hospitalization. Evaluation of representative virus isolates in primary cell cultures suggested an ongoing adaptation to the upper human respiratory tract for Omicron BA.2, BQ.1.1, XBB.1.5, and XBB.1.9.2, as well as increased propagation of XBB.1.9.2 in an alveolar infection model. Collectively, this study underscores the public health importance of implementing strategies to assess the risk of emerging SARS-CoV-2 lineages and demonstrates ongoing intrinsic adaptation of SARS-CoV-2 variants to all compartments of the human respiratory tract.

A significant reduction in influenza incidence during the early days of COVID-19 pandemic was reported worldwide. This study aims to understand the impact of public health and social measures implemented during the COVID- 19 pandemic on influenza circulation in Nepal. We utilized influenza sentinel and non-sentinel surveillance data from Nepal between 2018 and 2022, obtained from the National Influenza Centre (NIC) at National Public Health Laboratory (NPHL), Nepal. Additionally, we used publicly available national COVID-19 case data released by the Ministry of Health and Population of Nepal. The data were analyzed for the trends in influenza cases, positivity rate and the distribution of subtypes/lineages. Furthermore, we compared the trend of influenza with that of COVID-19 and the social and public health measures implemented in the country as part of the COVID-19 response. The average influenza positivity rate dropped significantly from 39% to 14% during the COVID-19 period compared to the pre- COVID-19. Additionally, during the time of COVID 19 there has been a shift in the influenza bimodal seasonal pattern, with only one peak observed. Influenza type A consistently dominated, with variations in its subtype observed from year to year. Notably, one case of Influenza A/H5N1 was reported in 2019. This study shows that the influenza positivity rate decreased substantially after the COVID-19 pandemic began, possibly due to the stringent public health and social measures implemented during the pandemic. Adaptation of the influenza surveillance system during pandemics and integration of other respiratory pathogens into it not only allows continuity of surveillance but also helps to evaluate the public health and social measures implemented to manage future respiratory virus pandemics.