Respiratory tract infections and gut microbiome modifications: A systematic review

Respiratory tract infections (RTIs) are extremely common and can cause gastrointestinal tract symptoms and changes to the gut microbiota, yet these effects are poorly understood. We conducted a systematic review to evaluate the reported evidence of gut microbiome alterations in patients with a RTI compared to healthy controls (PROSPERO: CRD42019138853). We systematically searched Medline, Embase, Web of Science, Cochrane and the Clinical Trial Database for studies published between January 2015 and June 2021. Studies were eligible for inclusion if they were human cohorts describing the gut microbiome in patients with an RTI compared to healthy controls and the infection was caused by a viral or bacterial pathogen. Dual data screening and extraction with narrative synthesis was performed. We identified 1,593 articles and assessed 11 full texts for inclusion. Included studies (some nested) reported gut microbiome changes in the context of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) (n = 5), influenza (H1N1 and H7N9) (n = 2), Tuberculosis (TB) (n = 4), Community-Acquired Pneumonia CAP (n = 2) and recurrent RTIs (rRTI) (n = 1) infections. We found studies of patients with an RTI compared to controls reported a decrease in gut microbiome diversity (Shannon) of 1.45 units (95% CI, 0.15–2.50 [p, <0.0001]) and a lower abundance of taxa (p, 0.0086). Meta-analysis of the Shannon value showed considerable heterogeneity between studies (I(2), 94.42). Unbiased analysis displayed as a funnel plot revealed a depletion of Lachnospiraceae, Ruminococcaceae and Ruminococcus and enrichment of Enterococcus. There was an important absence in the lack of cohort studies reporting gut microbiome changes and high heterogeneity between studies may be explained by variations in microbiome methods and confounder effects. Further human cohort studies are needed to understand RTI-induced gut microbiome changes to better understand interplay between microbes and respiratory health

The Anti-Circumvention Provision of The Digital Millennium Copyright Act

The DMCA\u27s ban on circumvention technology, however, has been the subject of some dispute. In the arms race between encryption and decryption technologies, the anti-circumvention provision seems to have recently won out. The anti-circumvention provision also appears to have altered the contours of copyright law and to have disturbed the balance between protecting the rights of authors and promoting the advancement and flow of information. This Article begins with a brief history of the Digital Millennium Copyright Act and its anti-circumvention provision. It then describes the features of the anti-circumvention provision, its exceptions, and the remedies provided by the Act. Finally, it reviews three recent cases that raise important issues that, when ultimately resolved, may permanently affect copyright law

Subcompartments of the macrophage recycling endosome direct the differential secretion of IL-6 and TNFα

Activated macrophages secrete an array of proinflammatory cytokines, including tumor necrosis factor-α (TNFα) and interleukin 6 (IL-6), that are temporally secreted for sequential roles in inflammation. We have previously characterized aspects of the intracellular trafficking of membrane-bound TNFα and its delivery to the cell surface at the site of phagocytic cups for secretion (Murray, R.Z., J.G. Kay, D.G. Sangermani, and J.L. Stow. 2005. Science. 310:1492–1495). The trafficking pathway and surface delivery of IL-6, a soluble cytokine, were studied here using approaches such as live cell imaging of fluorescently tagged IL-6 and immunoelectron microscopy. Newly synthesized IL-6 accumulates in the Golgi complex and exits in tubulovesicular carriers either as the sole labeled cargo or together with TNFα, utilizing specific soluble NSF attachment protein receptor (SNARE) proteins to fuse with the recycling endosome. Within recycling endosomes, we demonstrate the compartmentalization of cargo proteins, wherein IL-6 is dynamically segregated from TNFα and from surface recycling transferrin. Thereafter, these cytokines are independently secreted, with TNFα delivered to phagocytic cups but not IL-6. Therefore, the recycling endosome has a central role in orchestrating the differential secretion of cytokines during inflammation

A method for the three-dimensional reconstruction of Neurobiotin(TM)-filled neurons and the location of their synaptic inputs

Here, we describe a robust method for mapping the number and type of neuro-chemically distinct synaptic inputs that a single reconstructed neuron receives. We have used individual hypoglossal motor neurons filled with Neurobiotin by semi-loose seal electroporation in thick brainstem slices. These filled motor neurons were then processed for excitatory and inhibitory synaptic inputs, using immunohistochemical-labeling procedures. For excitatory synapses, we used anti-VGLUT2 to locate glutamatergic pre-synaptic terminals and anti-PSD-95 to locate post-synaptic specializations on and within the surface of these filled motor neurons. For inhibitory synapses, we used anti-VGAT to locate GABAergic pre-synaptic terminals and anti-GABA-A receptor subunit a1 to locate the post-synaptic domain. The Neurobiotin-filled and immuno-labeled motor neuron was then processed for optical sectioning using confocal microscopy. The morphology of the motor neuron including its dendritic tree and the distribution of excitatory and inhibitory synapses were then determined by three-dimensional reconstruction using IMARIS software (Bitplane). Using surface rendering, fluorescence thresholding, and masking of unwanted immuno-labeling, tools found in IMARIS, we were able to obtain an accurate 3D structure of an individual neuron including the number and location of its glutamatergic and GABAergic synaptic inputs. The power of this method allows for a rapid morphological confirmation of the post-synaptic responses recorded by patch-clamp prior to Neurobiotin filling. Finally, we show that this method can be adapted to super-resolution microscopy techniques, which will enhance its applicability to the study of neural circuits at the level of synapses

Tobacco Town: Computational Modeling of Policy Options to Reduce Tobacco Retailer Density

To identify the behavioral mechanisms and effects of tobacco control policies designed to reduce tobacco retailer density

Understanding misimplementation in U.S. state health departments: An agent-based model

INTRODUCTION: The research goal of this study is to explore why misimplementation occurs in public health agencies and how it can be reduced. Misimplementation is ending effective activities prematurely or continuing ineffective ones, which contributes to wasted resources and suboptimal health outcomes. METHODS: The study team created an agent-based model that represents how information flow, filtered through organizational structure, capacity, culture, and leadership priorities, shapes continuation decisions. This agent-based model used survey data and interviews with state health department personnel across the U.S. between 2014 and 2020; model design and analyses were conducted with substantial input from stakeholders between 2019 and 2021. The model was used experimentally to identify potential approaches for reducing misimplementation. RESULTS: Simulations showed that increasing either organizational evidence-based decision-making capacity or information sharing could reduce misimplementation. Shifting leadership priorities to emphasize effectiveness resulted in the largest reduction, whereas organizational restructuring did not reduce misimplementation. CONCLUSIONS: The model identifies for the first time a specific set of factors and dynamic pathways most likely driving misimplementation and suggests a number of actionable strategies for reducing it. Priorities for training the public health workforce include evidence-based decision making and effective communication. Organizations will also benefit from an intentional shift in leadership decision-making processes. On the basis of this initial, successful application of agent-based model to misimplementation, this work provides a framework for further analyses

Toward optimal implementation of cancer prevention and control programs in public health: A study protocol on mis-implementation

Abstract Background Much of the cancer burden in the USA is preventable, through application of existing knowledge. State-level funders and public health practitioners are in ideal positions to affect programs and policies related to cancer control. Mis-implementation refers to ending effective programs and policies prematurely or continuing ineffective ones. Greater attention to mis-implementation should lead to use of effective interventions and more efficient expenditure of resources, which in the long term, will lead to more positive cancer outcomes. Methods This is a three-phase study that takes a comprehensive approach, leading to the elucidation of tactics for addressing mis-implementation. Phase 1: We assess the extent to which mis-implementation is occurring among state cancer control programs in public health. This initial phase will involve a survey of 800 practitioners representing all states. The programs represented will span the full continuum of cancer control, from primary prevention to survivorship. Phase 2: Using data from phase 1 to identify organizations in which mis-implementation is particularly high or low, the team will conduct eight comparative case studies to get a richer understanding of mis-implementation and to understand contextual differences. These case studies will highlight lessons learned about mis-implementation and identify hypothesized drivers. Phase 3: Agent-based modeling will be used to identify dynamic interactions between individual capacity, organizational capacity, use of evidence, funding, and external factors driving mis-implementation. The team will then translate and disseminate findings from phases 1 to 3 to practitioners and practice-related stakeholders to support the reduction of mis-implementation. Discussion This study is innovative and significant because it will (1) be the first to refine and further develop reliable and valid measures of mis-implementation of public health programs; (2) bring together a strong, transdisciplinary team with significant expertise in practice-based research; (3) use agent-based modeling to address cancer control implementation; and (4) use a participatory, evidence-based, stakeholder-driven approach that will identify key leverage points for addressing mis-implementation among state public health programs. This research is expected to provide replicable computational simulation models that can identify leverage points and public health system dynamics to reduce mis-implementation in cancer control and may be of interest to other health areas

The Missing Link! A New Skeleton for Evolutionary Multi-agent Systems in Erlang

Evolutionary multi-agent systems (EMAS) play a critical role in many artificial intelligence applications that are in use today. In this paper, we present a new generic skeleton in Erlang for parallel EMAS computations. The skeleton enables us to capture a wide variety of concrete evolutionary computations that can exploit the same underlying parallel implementation. We demonstrate the use of our skeleton on two different evolutionary computing applications: (1) computing the minimum of the Rastrigin function; and (2) solving an urban traffic optimisation problem. We show that we can obtain very good speedups (up to 142.44 ×× the sequential performance) on a variety of different parallel hardware, while requiring very little parallelisation effort.Publisher PDFPeer reviewe

What is evidence required for and who generates that evidence in the Finnish Educational System?

Peer reviewe