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In Egypt, efforts to control highly pathogenic H5N1 avian influenza virus in poultry and in humans have failed despite increased biosecurity, quarantine, and vaccination at poultry farms. The ongoing circulation of HP H5N1 avian influenza in Egypt has caused >100 human infections and remains an unresolved threat to veterinary and public health. Here, we describe that the failure of commercially available H5 poultry vaccines in Egypt may be caused in part by the passive transfer of maternal H5N1 antibodies to chicks, inhibiting their immune response to vaccination. We propose that the induction of a protective immune response to H5N1 is suppressed for an extended period in young chickens. This issue, among others, must be resolved and additional steps must be taken before the outbreaks in Egypt can be controlled.

Levels of preexisting antibodies to the hemagglutinin of pandemic influenza A(H1N1) 2009 (hereafter pandemic H1N1) virus positively correlate with age. The impact of contemporary seasonal influenza vaccines on establishing immunity to other pandemic H1N1 proteins is unknown. We measured serum antibodies to the neuraminidase (NA) of pandemic H1N1 in adults prior to and after vaccination with seasonal trivalent inactivated influenza vaccines. Serum antibodies to pandemic H1N1 NA were observed in all age groups; however, vaccination elevated levels of pandemic H1N1 NA antibodies predominately in elderly individuals (age,⩾60 years). Therefore, contemporary seasonal vaccines likely contribute to reduction of pandemic H1N1-associated disease in older individuals.

Biosafety should be a top priority in academic medical centers. Academic medical centers are unique in that they are composed of a diverse population. Students and employees are important populations in terms of safety and compliance. These two groups make up various education levels and job descriptions. Significant differences also exist between the clinical and research arenas in an academic medical center. Clinical personnel may be exposed to a variety of pathogens in blood and body fluids. Where, laboratory personnel deal with very specific pathogens. Therefore, appropriate training geared toward each educational program and employee job duties can be very difficult to develop and the training must be tailored appropriately. The importance of biosafety when handling or being potentially exposed to microorganisms and other infectious materials must be recognized by students and employees. The goal of biosafety is to minimize risk to students and employees. In order to minimize this risk, students and employees must be knowledgeable and aware of biosafety. Individuals must first understand the best practices and procedures for achieving biosafety. This study was conducted at a large academic medical center. The survey population consisted of field professionals. The professions represented were physicians, nurses, researchers, and laboratory technologist. The survey inquiries about biosafety knowledge, practice, and perception. The survey questions were also validated simultaneously by field professionals. The survey results helped to identify some potentially problematic areas in training as well as difference in training among the clinical and laboratory environments. The outcomes will help to develop an improved and tailored approach to training across different disciplines. Accidental exposures to microorganisms and other infectious materials can cause serious illness and harm to students and employees. Good biosafety practices can reduce the number of accidental exposures to biohazardous materials. By increasing biosafety training and stressing the importance of biosafety practices, the potential for accidental exposure to biohazardous materials will ultimately decrease among students and employees.

English language copyediting poses significant barriers to global health authors in academic publishing. Editing is too expensive for most researchers in low-income countries, and large language models (LLMs) like ChatGPT may offer a cost-effective alternative. The technology, however, has been criticized for its biases and inaccuracies. In a preliminary, in-depth case comparison, we compared the number and quality of corrections made by U-M GPT, a secure, University of Michigan-hosted generative AI tool, to those from Grammarly and a human editor to text from two draft papers written by Ugandan sexual and reproductive health researchers. Overall, U-M GPT made about three times as many corrections compared to the human editor and about ten times more than Grammarly. U-M GPT was the least discriminating in terms of quality: only 61% (51/83) of its corrections were judged as improvements. Despite this, U-M GPT has advantages, such as a broad scope of correction types, fast turnaround, and no cost. Its disadvantages, which reflect shortcomings of LLMs more broadly, include the need for prompt engineering skill, careful review of corrections, and high environmental costs due to energy consumption. Additional concerns involve data privacy and content moderation policies that restrict discussions on topics deemed as sensitive; these included words related to sexual and reproductive health. Although LLMs could improve equity, efficiency, and productivity, several important issues should be considered when using the technology. Larger follow-up investigations are needed to confirm our findings. Authors using LLMs should consult journal guidelines and disclose their use.

A poem is presented.

Salmon is the most commonly consumed finfish in the United States of America (USA), and the mislabeling of salmon is a widespread problem. Washington State is a global supplier of wild-caught Pacific salmon and local salmon mislabeling results in substantial economic, ecological, and cultural impacts. Previous studies in Washington State identified high levels of mislabeled salmon in both markets and restaurants, resulting in local legislation being passed that requires proper labeling of salmon products, including identifying it as wild-caught or farm-raised. To investigate whether recent legislative efforts reduced salmon fraud rates, we acquired and genetically barcoded salmon samples from 67 grocery stores and 52 sushi restaurants in Seattle, Washington. DNA from each salmon sample was isolated and the cytochrome c oxidase gene was sequenced to identify the fish species. Our study, conducted from 2022–2023, revealed 18% of salmon samples from both grocery stores and sushi restaurants were mislabeled. While most samples were acquired during the fall months when wild salmon is in season, we still observed a high salmon mislabeling rate. Unlike grocery stores, Seattle sushi restaurants often sold farmed salmon mislabeled as wild salmon. Specifically, substitutions of vendor-claimed wild salmon with farmed salmon occurred in 32.3% of sushi restaurant samples compared to 0% of grocery store samples. Additionally, occurrences of wild salmon being substituted with another salmon species (wild or farmed) occurred in 38.7% of sushi restaurant samples compared to 11.1% of grocery store samples. All salmon substitutions in sushi restaurants harmed the customer financially as they were given a cheaper market-priced fish. In grocery stores, however, we did not detect significant economic loss to customers due to salmon mislabeling. Taken together, it is important to continue to develop and enforce legislation in Washington State that prevents salmon fraud and promotes ecologically sustainable fishing practices.

Since the reemergence of highly pathogenic H5N1 influenza viruses in humans in 2003, these viruses have spread throughout avian species in Asia, Europe, and Africa. Their sustained circulation has resulted in the evolution of phylogenetically diverse lineages. Viruses from these lineages show considerable antigenic variation, which has confounded vaccine planning efforts. We reconstructed ancestral protein sequences at several nodes of the hemagglutinin (HA) and neuraminidase (NA) gene phylogenies that represent ancestors to diverse H5N1 virus clades. By using the same methods that have been used to generate currently licensed inactivated H5N1 vaccines, we were able to produce a panel of replication competent influenza viruses containing synthesized HA and NA genes representing the reconstructed ancestral proteins. We identified two of these viruses that showed promising in vitro cross-reactivity with clade 1, 2.1, 2.2, 2.3.4, and 4 viruses. To confirm that vaccine antigens derived from these viruses were able to elicit functional antibodies following immunization, we created whole-virus vaccines and compared their protective efficacy versus that of antigens from positive control, naturally occurring, and broadly reactive H5N1 viruses. The ancestral viruses' vaccines provided robust protection against morbidity and mortality in ferrets challenged with H5N1 strains from clades 1, 2.1, and 2.2 in a manner similar to those based on the control strains. These findings provide proof of principle that viable, computationally derived vaccine seed viruses can be constructed within the context of currently licensed vaccine platforms. Such technologies should be explored to enhance the cross reactivity and availability of H5N1 influenza vaccines.

Scientific data analyses often combine several computational tools in automated pipelines, or workflows. Thousands of such workflows have been used in the life sciences, though their composition has remained a cumbersome manual process due to a lack of standards for annotation, assembly, and implementation. Recent technological advances have returned the long-standing vision of automated workflow composition into focus. This article summarizes a recent Lorentz Center workshop dedicated to automated composition of workflows in the life sciences. We survey previous initiatives to automate the composition process, and discuss the current state of the art and future perspectives. We start by drawing the \"big picture\" of the scientific workflow development life cycle, before surveying and discussing current methods, technologies and practices for semantic domain modelling, automation in workflow development, and workflow assessment. Finally, we derive a roadmap of individual and community-based actions to work toward the vision of automated workflow development in the forthcoming years. A central outcome of the workshop is a general description of the workflow life cycle in six stages: 1) scientific question or hypothesis, 2) conceptual workflow, 3) abstract workflow, 4) concrete workflow, 5) production workflow, and 6) scientific results. The transitions between stages are facilitated by diverse tools and methods, usually incorporating domain knowledge in some form. Formal semantic domain modelling is hard and often a bottleneck for the application of semantic technologies. However, life science communities have made considerable progress here in recent years and are continuously improving, renewing interest in the application of semantic technologies for workflow exploration, composition and instantiation. Combined with systematic benchmarking with reference data and large-scale deployment of production-stage workflows, such technologies enable a more systematic process of workflow development than we know today. We believe that this can lead to more robust, reusable, and sustainable workflows in the future.