Oocyte fertilization and successful embryo implantation are key events marking the onset of pregnancy. In sexually reproducing organisms, embryogenesis begins with the fusion of two haploid gametes, each of which has undergone progressive stages of maturation. In the final stages of oocyte maturation, minimal transcriptional activity is present and regulation of gene expression occurs primarily at the post-transcriptional level. MicroRNAs (miRNA) are potent effectors of post-transcriptional gene silencing and recent evidence demonstrates that the miR-34 family of miRNA are involved in both spermatogenesis and early events of embryogenesis. The profile of miR-34 miRNAs has not been characterized in gametes or embryos of Bos taurus. We therefore used quantitative reverse transcription PCR (qRT-PCR) to examine this family of miRNAs: miR-34a, -34b and -34c as well as their precursors in bovine gametes and in vitro produced embryos. Oocytes were aspirated from antral follicles of bovine ovaries, and sperm cells were isolated from semen samples of 10 bulls with unknown fertility status. Immature and in vitro matured oocytes, as well as cleaved embryos, were collected in pools. Gametes, embryos and ovarian and testis tissues were purified for RNA. All members of the miR-34 family are present in bovine spermatozoa, while only miR-34a and -34c are present in oocytes and cleaved (2-cell) embryos. Mir-34c demonstrates variation among different bulls and is consistently expressed throughout oocyte maturation and in the embryo. The primary transcript of the miR-34b/c bicistron is abundant in the testes and present in ovarian tissue but undetectable in oocytes and in mature spermatozoa. The combination of these findings suggest that miR-34 miRNAs may be required in developing bovine gametes of both sexes, as well as in embryos, and that primary miR-34b/c processing takes place before the completion of gametogenesis. Individual variation in sperm miR-34 family abundance may offer potential as a biomarker of male bovine fertility.

Rising COVID-19 cases in Canada in early 2021, coupled with pervasive mis- and disinformation, demonstrate the critical relationship between effective crisis communication, trust, and risk protective measure adherence by the public. Trust in crisis communication is affected by the communication’s characteristics including transparency, timeliness, empathy, and clarity, as well as the source and communication channels used. Crisis communication occurs in a rhetorical arena where various actors, including public health, news media, and the public, are co-producing and responding to messages. Rhetorical arenas must be monitored to assess the acceptance of messaging. The quality and content of Canadian public health and news media crisis communication on Facebook were evaluated to understand the use of key guiding principles of effective crisis communication, the focus of the communication, and subsequent public emotional response to included posts. Four hundred and thirty-eight posts and 26,774 anonymized comments were collected and analyzed. Overall, the guiding principles for effective crisis communication were inconsistently applied and combined. A limited combination of guiding principles, especially those that demonstrate trustworthiness, was likely driving the negative sentiment uncovered in the comments. Public health and news media should use the guiding principles consistently to increase positive sentiment and build trust among followers.

In Northern Canada, climate change has led to many acute and interrelated health and environmental impacts experienced among Inuit populations. Community-based monitoring, in which community members participate in monitoring initiatives using various forms of technology, is a key strategy increasingly used to detect, monitor and respond to climate change impacts. To better understand the landscape of existing environmental and health monitoring programmes mobilising different technologies and operating in the North we conducted a review that used environmental scan methodologies to explore and contextualise these programmes. We consulted with academic researchers with experience in community-led monitoring, conducted systematic searches of grey and peer-reviewed literature, and conducted a secondary search for environment-health mobile-phone applications. Following specific criteria, we identified 18 monitoring programmes using information and communication technologies in the North, and three global monitoring mobile-phone applications, which cumulatively monitored 74 environment and health indicators. Several themes emerged, including the need for: (1) community leadership, (2) indicators of environment and/or human health and (3) innovative technology. This synthesis supports the development of community-led, environment-health monitoring programmes that use innovative technology to monitor and share information related to the health implications of climate change in and around Indigenous communities throughout the Circumpolar North.

The emergence of COVID-19 spurred the formation of myriad teams to tackle every conceivable aspect of the virus and thwart its spread. Enabled by global digital connectedness, collaboration has become a constant theme throughout the pandemic, resulting in the expedition of the scientific process (including vaccine development), rapid consolidation of global outbreak data and statistics, and experimentation with novel partnerships. To document the evolution of these collaborative efforts, the authors collected illustrative examples as the pandemic unfolded, supplemented with publications from the JMIR COVID-19 Special Issue. Over 60 projects rooted in collaboration are categorized into five main themes: knowledge dissemination, data propagation, crowdsourcing, artificial intelligence, and hardware design and development. They highlight the numerous ways that citizens, industry professionals, researchers, and academics have come together worldwide to consolidate information and produce products to combat the COVID-19 pandemic. Initially, researchers and citizen scientists scrambled to access quality data within an overwhelming quantity of information. As global curated data sets emerged, derivative works such as visualizations or models were developed that depended on consistent data and would fail when there were unanticipated changes. Crowdsourcing was used to collect and analyze data, aid in contact tracing, and produce personal protective equipment by sharing open designs for 3D printing. An international consortium of entrepreneurs and researchers created a ventilator based on an open-source design. A coalition of nongovernmental organizations and governmental organizations, led by the White House Office of Science and Technology Policy, created a shared open resource of over 200,000 research publications about COVID-19 and subsequently offered cash prizes for the best solutions to 17 key questions involving artificial intelligence. A thread of collaboration weaved throughout the pandemic response, which will shape future efforts. Novel partnerships will cross boundaries to create better processes, products, and solutions to consequential societal challenges.

One of the essential processes in Mobile Ad hoc Networks (MANETs) is blind flooding to discover routes between source and destination mobile nodes. As the density of nodes in the network increases, the number of broadcast packets increases exponentially. This can lead to broadcast storms, a drain on the device’s battery, and reduced network efficiency. We propose a Cross-layer Adaptive Fuzzy-based Ad hoc On-Demand Distance Vector routing protocol (CLAF-AODV) to minimize the routing broadcast traffic by considering the quality of service (QoS) (e.g. delay, throughput, packet loss), stability, and adaptability of the network. The suggested method employs two-level fuzzy logic and a cross-layer design approach to select the appropriate nodes with a higher probability of participating in broadcasting by considering parameters from the three first layers of the Open Systems Interconnection (OSI) model to achieve a quality of service, stability, and adaptability. It not only investigates the quality of the node and the network density around the node to make a decision but also investigates the path that the broadcast packet traveled to reach this node. Simulation results reveal that our proposed protocol reduces the number of broadcast packets and significantly improves network performance with respect to throughput, packet loss, normalized routing load, collision rate, and average energy consumption compared to the standard AODV and the Fixed Probability AODV (FP-AODV) algorithms.