Immune Monitoring of Trans-endothelial Transport by Kidney-Resident Macrophages

Small immune complexes cause type III hypersensitivity reactions that frequently result in tissue injury. The responsible mechanisms however remain unclear and differ depending on target organs. Here we identify a kidney-specific anatomical and functional unit, formed by resident macrophages and peritubular capillary endothelial cells, which monitors the transport of proteins and particles ranging from 20 to 700 kDa or 10 to 200 nm into the kidney interstitium. Kidney resident macrophages detect and scavenge circulating immune complexes ‘pumped’ into the interstitium via trans-endothelial transport, and trigger a FcγRIV-dependent inflammatory response and the recruitment of monocytes and neutrophils. In addition, FcγRIV and TLR pathways synergistically ‘super-activate’ kidney macrophages when immune complexes contain a nucleic acid. These data identify a physiological function of tissue resident kidney macrophages and a basic mechanism by which they initiate the inflammatory response to small immune complexes in the kidney

Cyber-Human Systems, Space Technologies, and Threats

CYBER-HUMAN SYSTEMS, SPACE TECHNOLOGIES, AND THREATS is our eighth textbook in a series covering the world of UASs / CUAS/ UUVs / SPACE. Other textbooks in our series are Space Systems Emerging Technologies and Operations; Drone Delivery of CBNRECy – DEW Weapons: Emerging Threats of Mini-Weapons of Mass Destruction and Disruption (WMDD); Disruptive Technologies with applications in Airline, Marine, Defense Industries; Unmanned Vehicle Systems & Operations On Air, Sea, Land; Counter Unmanned Aircraft Systems Technologies and Operations; Unmanned Aircraft Systems in the Cyber Domain: Protecting USA’s Advanced Air Assets, 2nd edition; and Unmanned Aircraft Systems (UAS) in the Cyber Domain Protecting USA’s Advanced Air Assets, 1st edition. Our previous seven titles have received considerable global recognition in the field. (Nichols & Carter, 2022) (Nichols, et al., 2021) (Nichols R. K., et al., 2020) (Nichols R. , et al., 2020) (Nichols R. , et al., 2019) (Nichols R. K., 2018) (Nichols R. K., et al., 2022)https://newprairiepress.org/ebooks/1052/thumbnail.jp

Forecasting Random Walks under Drift Instability

This paper considers forecast averaging when the same model is used but estimation is carried out over different estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or more structural breaks. It is shown that compared to using forecasts based on a single estimation window, averaging over estimation windows leads to a lower bias and to a lower root mean square forecast error for all but the smallest of breaks. Similar results are also obtained when observations are exponentially down-weighted, although in this case the performance of forecasts based on exponential down-weighting critically depends on the choice of the weighting coefficient. The forecasting techniques are applied to monthly inflation series of 21 OECD countries and it is found that average forecasting methods in general perform better than using forecasts based on a single estimation window

The 3′ Untranslated Regions of Influenza Genomic Sequences Are 5′PPP-Independent Ligands for RIG-I

Retinoic acid inducible gene-I (RIG-I) is a key regulator of antiviral immunity. RIG-I is generally thought to be activated by ssRNA species containing a 5′-triphosphate (PPP) group or by unphosphorylated dsRNA up to ∼300 bp in length. However, it is not yet clear how changes in the length, nucleotide sequence, secondary structure, and 5′ end modification affect the abilities of these ligands to bind and activate RIG-I. To further investigate these parameters in the context of naturally occurring ligands, we examined RNA sequences derived from the 5′ and 3′ untranslated regions (UTR) of the influenza virus NS1 gene segment. As expected, RIG-I-dependent interferon-β (IFN-β) induction by sequences from the 5′ UTR of the influenza cRNA or its complement (26 nt in length) required the presence of a 5′PPP group. In contrast, activation of RIG-I by the 3′ UTR cRNA sequence or its complement (172 nt) exhibited only a partial 5′PPP-dependence, as capping the 5′ end or treatment with CIP showed a modest reduction in RIG-I activation. Furthermore, induction of IFN-β by a smaller, U/A-rich region within the 3′ UTR was completely 5′PPP-independent. Our findings demonstrated that RNA sequence, length, and secondary structure all contributed to whether or not the 5′PPP moiety is needed for interferon induction by RIG-I

Nox4 Mediates Renal Cell Carcinoma Cell Invasion through Hypoxia-Induced Interleukin 6- and 8- Production

Inflammatory cytokines are detected in the plasma of patients with renal cell carcinoma (RCC) and are associated with poor prognosis. However, the primary cell type involved in producing inflammatory cytokines and the biological significance in RCC remain unknown. Inflammation is associated with oxidative stress, upregulation of hypoxia inducible factor 1-alpha, and production of pro-inflammatory gene products. Solid tumors are often heterogeneous in oxygen tension together suggesting that hypoxia may play a role in inflammatory processes in RCC. Epithelial cells have been implicated in cytokine release, although the stimuli to release and molecular mechanisms by which they are released remain unclear. AMP-activated protein kinase (AMPK) is a highly conserved sensor of cellular energy status and a role for AMPK in the regulation of cell inflammatory processes has recently been demonstrated.We have identified for the first time that interleukin-6 and interleukin-8 (IL-6 and IL-8) are secreted solely from RCC cells exposed to hypoxia. Furthermore, we demonstrate that the NADPH oxidase isoform, Nox4, play a key role in hypoxia-induced IL-6 and IL-8 production in RCC. Finally, we have characterized that enhanced levels of IL-6 and IL-8 result in RCC cell invasion and that activation of AMPK reduces Nox4 expression, IL-6 and IL-8 production, and RCC cell invasion.Together, our data identify novel mechanisms by which AMPK and Nox4 may be linked to inflammation-induced RCC metastasis and that pharmacological activation of AMPK and/or antioxidants targeting Nox4 may represent a relevant therapeutic intervention to reduce IL-6- and IL-8-induced inflammation and cell invasion in RCC

Predicting September Arctic Sea Ice: A Multi-Model Seasonal Skill Comparison

Abstract This study quantifies the state-of-the-art in the rapidly growing field of seasonal Arctic sea ice prediction. A novel multi-model dataset of retrospective seasonal predictions of September Arctic sea ice is created and analyzed, consisting of community contributions from 17 statistical models and 17 dynamical models. Prediction skill is compared over the period 2001–2020 for predictions of Pan-Arctic sea ice extent (SIE), regional SIE, and local sea ice concentration (SIC) initialized on June 1, July 1, August 1, and September 1. This diverse set of statistical and dynamical models can individually predict linearly detrended Pan-Arctic SIE anomalies with skill, and a multi-model median prediction has correlation coefficients of 0.79, 0.86, 0.92, and 0.99 at these respective initialization times. Regional SIE predictions have similar skill to Pan-Arctic predictions in the Alaskan and Siberian regions, whereas regional skill is lower in the Canadian, Atlantic, and Central Arctic sectors. The skill of dynamical and statistical models is generally comparable for Pan-Arctic SIE, whereas dynamical models outperform their statistical counterparts for regional and local predictions. The prediction systems are found to provide the most value added relative to basic reference forecasts in the extreme SIE years of 1996, 2007, and 2012. SIE prediction errors do not show clear trends over time, suggesting that there has been minimal change in inherent sea ice predictability over the satellite era. Overall, this study demonstrates that there are bright prospects for skillful operational predictions of September sea ice at least three months in advance.</jats:p

An analysis of RSQE forecasts: 1971–1992

The purpose of this paper is to evaluate the accuracy of ex ante econometric model forecasts of four key macroeconomic variables: real GNP growth, the rate of price inflation measured by the GNP deflator, the civilian unemployment rate, and the Treasury Bill rate. Annual forecasts produced by the Research Seminar in Quantitative Economics (RSQE) based on the Michigan Quarterly Econometric Model of the U.S. Economy are compared with quasi ex ante forecasts from a four-variable vector autoregressive (VAR) model. Statistical tests of the equality of forecast error variances as well as univariate and multivariate forecast encompassing-type tests are conducted. The forecast error variance comparisons indicate that for three of the four variables the RSQE forecasts are more accurate than the VAR forecasts and for one of the variables (real GNP growth) only slightly less accurate. The forecast encompassing-type tests indicate that the RSQE forecasts contain information not contained in the VAR forecasts and, conversely, that VAR forecasts contain information not included in the RSQE forecasts. The scope for improving RSQE forecasts by combining them with VAR forecasts is rather limited, however.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43925/1/11293_2006_Article_BF02299030.pd