Targeting transitioning lung monocytes/macrophages as treatment strategies in lung disease related to environmental exposures.

BACKGROUND: Environmental/occupational exposures cause significant lung diseases. Agricultural organic dust extracts (ODE) and bacterial component lipopolysaccharide (LPS) induce recruited, transitioning murine lung monocytes/macrophages, yet their cellular role remains unclear. METHODS: CCR2 RFP+ mice were intratracheally instilled with high concentration ODE (25%), LPS (10 µg), or gram-positive peptidoglycan (PGN, 100 µg) for monocyte/macrophage cell-trafficking studies. CCR2 knockout (KO) mice and administration of intravenous clodronate liposomes strategies were employed to reduce circulating monocytes available for lung recruitment following LPS exposure. Lung tissues and bronchoalveolar lavage fluid (BALF) were collected. Pro-inflammatory and/or pro-fibrotic cytokines, chemokines, and lung extracellular matrix mediators were quantitated by ELISA. Infiltrating lung cells including monocyte/macrophage subpopulations, neutrophils, and lymphocytes were characterized by flow cytometry. Lung histopathology, collagen content, vimentin, and post-translational protein citrullination and malondialdehyde acetaldehyde (MAA) modification were quantitated. Parametric statistical tests (one-way ANOVA, Tukey'smultiple comparison) and nonparametric statistical (Kruskal-Wallis, Dunn's multiple comparison) tests were used following Shapiro-Wilk testing for normality. RESULTS: Intratracheal instillation of ODE, LPS, or PGN robustly induced the recruitment of inflammatory CCR2+ CD11cintCD11bhi monocytes/macrophages and both CCR2+ and CCR2- CD11c-CD11bhi monocytes at 48 h. There were also increases in CCR2+ CD4+ and CD8+ T cells and NK cells. Despite reductions in LPS-induced lung infiltrating CD11cintCD11bhi cells (54% reduction), CCR2 knockout (KO) mice were not protected against LPS-induced inflammatory and pro-fibrotic consequences. Instead, compensatory increases in lung neutrophils and CCL2 and CCL7 release occurred. In contrast, the depletion of circulating monocytes through the administration of intravenous clodronate (vs. vehicle) liposomes 24 h prior to LPS exposure reduced LPS-induced infiltrating CD11cintCD11bhi monocyte-macrophage subpopulation by 59% without compensatory changes in other cell populations. Clodronate liposome pre-treatment significantly reduced LPS-induced IL-6 (66% reduction), matrix metalloproteinases (MMP)-3 (36%), MMP-8 (57%), tissue inhibitor of metalloproteinases (61%), fibronectin (38%), collagen content (22%), and vimentin (40%). LPS-induced lung protein citrullination and MAA modification, post-translational modifications implicated in lung disease, were reduced (39% and 48%) with clodronate vs. vehicle liposome. CONCLUSION: Highly concentrated environmental/occupational exposures induced the recruitment of CCR2+ and CCR2- transitioning monocyte-macrophage and monocyte subpopulations and targeting peripheral monocytes may reduce the adverse lung consequences resulting from exposures to LPS-enriched inhalants.

What predicts citation counts and translational impact in headache research? A machine learning analysis.

BACKGROUND: We aimed to develop the first machine learning models to predict citation counts and the translational impact, defined as inclusion in guidelines or policy documents, of headache research, and assess which factors are most predictive. METHODS: Bibliometric data and the titles, abstracts, and keywords from 8600 publications in three headache-oriented journals from their inception to 31 December 2017 were used. A series of machine learning models were implemented to predict three classes of 5-year citation count intervals (0-5, 6-14 and, >14 citations); and the translational impact of a publication. Models were evaluated out-of-sample with area under the receiver operating characteristics curve (AUC). RESULTS: The top performing gradient boosting model predicted correct citation count class with an out-of-sample AUC of 0.81. Bibliometric data such as page count, number of references, first and last author citation counts and h-index were among the most important predictors. Prediction of translational impact worked optimally when including both bibliometric data and information from the title, abstract and keywords, reaching an out-of-sample AUC of 0.71 for the top performing random forest model. CONCLUSION: Citation counts are best predicted by bibliometric data, while models incorporating both bibliometric data and publication content identifies the translational impact of headache research.

Lung-delivered IL-10 therapy elicits beneficial effects via immune modulation in organic dust exposure-induced lung inflammation.

Efficacious therapeutic options capable of resolving inflammatory lung disease associated with environmental and occupational exposures are lacking. This study sought to determine the preclinical therapeutic potential of lung-delivered recombinant interleukin (IL)-10 therapy following acute organic dust exposure in mice. Here, C57BL/6J mice were intratracheally instilled with swine confinement organic dust extract (ODE) (12.5%, 25%, 50% concentrations) with IL-10 (1 µg) treatment or vehicle control intratracheally-administered three times: 5 hr post-exposure and then daily for 2 days. The results showed that IL-10 treatment reduced ODE (25%)-induced weight loss by 66% and 46% at Day 1 and Day 2 post-exposure, respectively. IL-10 treatment reduced ODE (25%, 50%)-induced lung levels of TNFα (-76%, -83% [reduction], respectively), neutrophil chemoattractant CXCL1 (-51%, -60%), and lavage fluid IL-6 (-84%, -89%). IL-10 treatment reduced ODE (25%, 50%)-induced lung neutrophils (-49%, -70%) and recruited CD11cintCD11b+ monocyte-macrophages (-49%, -70%). IL-10 therapy reduced ODE-associated expression of antigen presentation (MHC Class II, CD80, CD86) and inflammatory (Ly6C) markers and increased anti-inflammatory CD206 expression on CD11cintCD11b+ cells. ODE (12.5%, 25%)-induced lung pathology was also reduced with IL-10 therapy. In conclusion, the studies here showed that short-term, lung-delivered IL-10 treatment induced a beneficial response in reducing inflammatory consequences (that were also associated with striking reduction in recruited monocyte-macrophages) following acute complex organic dust exposure.

The minimal computational substrate of fluid intelligence.

The quantification of cognitive powers rests on identifying a behavioural task that depends on them. Such dependence cannot be assured, for the powers a task invokes cannot be experimentally controlled or constrained a priori, resulting in unknown vulnerability to failure of specificity and generalisability. Evaluating a compact version of Raven's Advanced Progressive Matrices (RAPM), a widely used clinical test of fluid intelligence, we show that LaMa, a self-supervised artificial neural network trained solely on the completion of partially masked images of natural environmental scenes, achieves representative human-level test scores a prima vista, without any task-specific inductive bias or training. Compared with cohorts of healthy and focally lesioned participants, LaMa exhibits human-like variation with item difficulty, and produces errors characteristic of right frontal lobe damage under degradation of its ability to integrate global spatial patterns. LaMa's narrow training and limited capacity suggest matrix-style tests may be open to computationally simple solutions that need not necessarily invoke the substrates of reasoning.

Four questions to guide decision-making for data sharing and integration.

Introduction: This paper presents a Four Question Framework to guide data integration partners in building a strong governance and legal foundation to support ethical data use. Objectives: While this framework was developed based on work in the United States that routinely integrates public data, it is meant to be a simple, digestible tool that can be adapted to any context. Methods: The framework was developed through a series of public deliberation workgroups and 15 years of field experience working with a diversity of data integration efforts across the United States. Results: The Four Questions-Is this legal? Is this ethical? Is this a good idea? How do we know (and who decides)?-should be considered within an established data governance framework and alongside core partners to determine whether and how to move forward when building an Integrated Data System (IDS) and also at each stage of a specific data project. We discuss these questions in depth, with a particular focus on the role of governance in establishing legal and ethical data use. In addition, we provide example data governance structures from two IDS sites and hypothetical scenarios that illustrate key considerations for the Four Question Framework. Conclusions: A robust governance process is essential for determining whether data sharing and integration is legal, ethical, and a good idea within the local context. This process is iterative and as relational as it is technical, which means authentic collaboration across partners should be prioritized at each stage of a data use project. The Four Questions serve as a guide for determining whether to undertake data sharing and integration and should be regularly revisited throughout the life of a project. Highlights: Strong data governance has five qualities: it is purpose-, value-, and principle-driven; strategically located; collaborative; iterative; and transparent.Through a series of public deliberation workgroups and 15 years of field experience, we developed a Four Question Framework to determine whether and how to move forward with building an IDS and at each stage of a data sharing and integration project.The Four Questions-Is this legal? Is this ethical? Is this a good idea? How do we know (and who decides)?-should be carefully considered within established data governance processes and among core partners.

Essential requirements for the governance and management of data trusts, data repositories, and other data collaborations.

Introduction: Around the world, many organisations are working on ways to increase the use, sharing, and reuse of person-level data for research, evaluation, planning, and innovation while ensuring that data are secure and privacy is protected. As a contribution to broader efforts to improve data governance and management, in 2020 members of our team published 12 minimum specification essential requirements (min specs) to provide practical guidance for organisations establishing or operating data trusts and other forms of data infrastructure. Approach and Aims: We convened an international team, consisting mostly of participants from Canada and the United States of America, to test and refine the original 12 min specs. Twenty-three (23) data-focused organisations and initiatives recorded the various ways they address the min specs. Sub-teams analysed the results, used the findings to make improvements to the min specs, and identified materials to support organisations/initiatives in addressing the min specs. Results: Analyses and discussion led to an updated set of 15 min specs covering five categories: one min spec for Legal, five for Governance, four for Management, two for Data Users, and three for Stakeholder & Public Engagement. Multiple changes were made to make the min specs language more technically complete and precise. The updated set of 15 min specs has been integrated into a Canadian national standard that, to our knowledge, is the first to include requirements for public engagement and Indigenous Data Sovereignty. Conclusions: The testing and refinement of the min specs led to significant additions and improvements. The min specs helped the 23 organisations/initiatives involved in this project communicate and compare how they achieve responsible and trustworthy data governance and management. By extension, the min specs, and the Canadian national standard based on them, are likely to be useful for other data-focused organisations and initiatives.