Leadership Lessons: The Campaigns for Vicksburg, 1862-1863

Taking Civil War Leaders to Task Kevin Dougherty’s Leadership Lessons: The Campaigns for Vicksburg, 1862-1863 offers a concise summary of the events that led to the city’s capture in July, 1863, but focuses on the campaign’s utility as a primer for modern leaders in “war, busines...

Hepatocyte expressed chemerin-156 does not protect from experimental non-alcoholic steatohepatitis.

Non-alcoholic steatohepatitis (NASH) is a rapidly growing liver disease. The chemoattractant chemerin is abundant in hepatocytes, and hepatocyte expressed prochemerin protected from NASH. Prochemerin is inactive and different active isoforms have been described. Here, the effect of hepatocyte expressed muChem-156, a highly active murine chemerin isoform, was studied in the methionine-choline deficient dietary model of NASH. Mice overexpressing muChem-156 had higher hepatic chemerin protein. Serum chemerin levels and the capability of serum to activate the chemerin receptors was unchanged showing that the liver did not release active chemerin. Notably, activation of the chemerin receptors by hepatic vein blood did not increase in parallel to total chemerin protein in patients with liver cirrhosis. In experimental NASH, muChem-156 had no effect on liver lipids. Accordingly, overexpression of active chemerin in hepatocytes or treatment of hepatocytes with recombinant chemerin did not affect cellular triglyceride and cholesterol levels. Importantly, overexpression of muChem-156 in the murine liver did not change the hepatic expression of inflammatory and profibrotic genes. The downstream targets of chemerin such as p38 kinase were neither activated in the liver of muChem-156 producing mice nor in HepG2, Huh7 and Hepa1-6 cells overexpressing this isoform. Recombinant chemerin had no effect on global gene expression of primary human hepatocytes and hepatic stellate cells within 24 h of incubation. Phosphorylation of p38 kinase was, however, increased upon short-time incubation of HepG2 cells with chemerin. These findings show that muChem-156 overexpression in hepatocytes does not protect from liver steatosis and inflammation

Polymeric peptide pigments with sequence-encoded properties

Melanins are a family of heterogeneous polymeric pigments that provide ultraviolet (UV) light protection, structural support, coloration, and free radical scavenging. Formed by oxidative oligomerization of catecholic small molecules, the physical properties of melanins are influenced by covalent and noncovalent disorder. We report the use of tyrosine-containing tripeptides as tunable precursors for polymeric pigments. In these structures, phenols are presented in a (supra-)molecular context dictated by the positions of the amino acids in the peptide sequence. Oxidative polymerization can be tuned in a sequence-dependent manner, resulting in peptide sequence–encoded properties such as UV absorbance, morphology, coloration, and electrochemical properties over a considerable range. Short peptides have low barriers to application and can be easily scaled, suggesting near-term applications in cosmetics and biomedicine

Chemerin Overexpression in the Liver Protects against Inflammation in Experimental Non-Alcoholic Steatohepatitis

Non-alcoholic steatohepatitis (NASH) is marked by macrophage infiltration and inflammation. Chemerin is a chemoattractant protein and is abundant in hepatocytes. The aim of this study was to gain insight into the role of hepatocyte-produced prochemerin in NASH. Therefore, mice were infected with adeno-associated virus 8 to direct hepatic overexpression of prochemerin in a methionine–choline deficient dietary model of NASH. At the end of the study, hepatic and serum chemerin were higher in the chemerin-expressing mice. These animals had less hepatic oxidative stress, F4/80 and CC-chemokine ligand 2 (CCL2) protein, and mRNA levels of inflammatory genes than the respective control animals. In order to identify the underlying mechanisms, prochemerin was expressed in hepatocytes and the hepatic stellate cells, LX-2. Here, chemerin had no effect on cell viability, production of inflammatory, or pro-fibrotic factors. Notably, cultivation of human peripheral blood mononuclear cells (PBMCs) in the supernatant of Huh7 cells overexpressing chemerin reduced CCL2, interleukin-6, and osteopontin levels in cell media. CCL2 was also low in RAW264.7 cells exposed to Hepa1–6 cell produced chemerin. In summary, the current study showed that prochemerin overexpression had little effect on hepatocytes and hepatic stellate cells. Of note, hepatocyte-produced chemerin deactivated PBMCs and protected against inflammation in experimental NASH

Differential Affinity and Catalytic Activity of CheZ in E. coli Chemotaxis

Push–pull networks, in which two antagonistic enzymes control the activity of a messenger protein, are ubiquitous in signal transduction pathways. A classical example is the chemotaxis system of the bacterium Escherichia coli, in which the kinase CheA and the phosphatase CheZ regulate the phosphorylation level of the messenger protein CheY. Recent experiments suggest that both the kinase and the phosphatase are localized at the receptor cluster, and Vaknin and Berg recently demonstrated that the spatial distribution of the phosphatase can markedly affect the dose–response curves. We argue, using mathematical modeling, that the canonical model of the chemotaxis network cannot explain the experimental observations of Vaknin and Berg. We present a new model, in which a small fraction of the phosphatase is localized at the receptor cluster, while the remainder freely diffuses in the cytoplasm; moreover, the phosphatase at the cluster has a higher binding affinity for the messenger protein and a higher catalytic activity than the phosphatase in the cytoplasm. This model is consistent with a large body of experimental data and can explain many of the experimental observations of Vaknin and Berg. More generally, the combination of differential affinity and catalytic activity provides a generic mechanism for amplifying signals that could be exploited in other two-component signaling systems. If this model is correct, then a number of recent modeling studies, which aim to explain the chemotactic gain in terms of the activity of the receptor cluster, should be reconsidered

The Astropy Problem

The Astropy Project (http://astropy.org) is, in its own words, "a community effort to develop a single core package for Astronomy in Python and foster interoperability between Python astronomy packages." For five years this project has been managed, written, and operated as a grassroots, self-organized, almost entirely volunteer effort while the software is used by the majority of the astronomical community. Despite this, the project has always been and remains to this day effectively unfunded. Further, contributors receive little or no formal recognition for creating and supporting what is now critical software. This paper explores the problem in detail, outlines possible solutions to correct this, and presents a few suggestions on how to address the sustainability of general purpose astronomical software

Environment and shipping drive environmental DNA beta-diversity among commercial ports

The spread of nonindigenous species by shipping is a large and growing global problem that harms coastal ecosystems and economies and may blur coastal biogeographical patterns. This study coupled eukaryotic environmental DNA (eDNA) metabarcoding with dissimilarity regression to test the hypothesis that ship-borne species spread homogenizes port communities. We first collected and metabarcoded water samples from ports in Europe, Asia, Australia and the Americas. We then calculated community dissimilarities between port pairs and tested for effects of environmental dissimilarity, biogeographical region and four alternative measures of ship-borne species transport risk. We predicted that higher shipping between ports would decrease community dissimilarity, that the effect of shipping would be small compared to that of environment dissimilarity and shared biogeography, and that more complex shipping risk metrics (which account for ballast water and stepping-stone spread) would perform better. Consistent with our hypotheses, community dissimilarities increased significantly with environmental dissimilarity and, to a lesser extent, decreased with ship-borne species transport risks, particularly if the ports had similar environments and stepping-stone risks were considered. Unexpectedly, we found no clear effect of shared biogeography, and that risk metrics incorporating estimates of ballast discharge did not offer more explanatory power than simpler traffic-based risks. Overall, we found that shipping homogenizes eukaryotic communities between ports in predictable ways, which could inform improvements in invasive species policy and management. We demonstrated the usefulness of eDNA metabarcoding and dissimilarity regression for disentangling the drivers of large-scale biodiversity patterns. We conclude by outlining logistical considerations and recommendations for future studies using this approach.Fil: Andrés, Jose. Cornell University. Department Of Ecology And Evolutionary Biology;Fil: Czechowski, Paul. Cornell University. Department Of Ecology And Evolutionary Biology; . University of Otago; Nueva Zelanda. Helmholtz Institute for Metabolic, Obesity and Vascular Research; AlemaniaFil: Grey, Erin. University of Maine; Estados Unidos. Governors State University; Estados UnidosFil: Saebi, Mandana. University of Notre Dame; Estados UnidosFil: Andres, Kara. Cornell University. Department Of Ecology And Evolutionary Biology;Fil: Brown, Christopher. California State University Maritime Academy; Estados UnidosFil: Chawla, Nitesh. University of Notre Dame; Estados UnidosFil: Corbett, James J.. University of Delaware; Estados UnidosFil: Brys, Rein. Research Institute for Nature and Forest; BélgicaFil: Cassey, Phillip. University of Adelaide; AustraliaFil: Correa, Nancy. Ministerio de Defensa. Armada Argentina. Instituto Universitario Naval de la Ara. Escuela de Ciencias del Mar; Argentina. Ministerio de Defensa. Armada Argentina. Servicio de Hidrografía Naval; ArgentinaFil: Deveney, Marty R.. South Australian Research And Development Institute; AustraliaFil: Egan, Scott P.. Rice University; Estados UnidosFil: Fisher, Joshua P.. United States Fish and Wildlife Service; Estados UnidosFil: vanden Hooff, Rian. Oregon Department of Environmental Quality; Estados UnidosFil: Knapp, Charles R.. Daniel P. Haerther Center for Conservation and Research; Estados UnidosFil: Leong, Sandric Chee Yew. National University of Singapore; SingapurFil: Neilson, Brian J.. State of Hawaii Division of Aquatic Resources; Estados UnidosFil: Paolucci, Esteban Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales "Bernardino Rivadavia"; ArgentinaFil: Pfrender, Michael E.. University of Notre Dame; Estados UnidosFil: Pochardt, Meredith R.. M. Rose Consulting; Estados UnidosFil: Prowse, Thomas A. A.. University of Adelaide; AustraliaFil: Rumrill, Steven S.. Oregon Department of Fish and Wildlife; Estados UnidosFil: Scianni, Chris. Universidad Nacional de Salta. Facultad de Ciencias Naturales. Instituto para el Estudio de la Biodiversidad de Invertebrados; Argentina. Marine Invasive Species Program; Estados UnidosFil: Sylvester, Francisco. Universidad Nacional de Salta. Facultad de Ciencias Naturales. Instituto para el Estudio de la Biodiversidad de Invertebrados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta; ArgentinaFil: Tamburri, Mario N.. University of Maryland; Estados UnidosFil: Therriault, Thomas W.. Pacific Biological Station; CanadáFil: Yeo, Darren C. J.. National University of Singapore; SingapurFil: Lodge, David M.. Cornell University. Department Of Ecology And Evolutionary Biology

Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study

Background: The risk of severe COVID-19 if an individual becomes infected is known to be higher in older individuals and those with underlying health conditions. Understanding the number of individuals at increased risk of severe COVID-19 and how this varies between countries should inform the design of possible strategies to shield or vaccinate those at highest risk. Methods: We estimated the number of individuals at increased risk of severe disease (defined as those with at least one condition listed as “at increased risk of severe COVID-19” in current guidelines) by age (5-year age groups), sex, and country for 188 countries using prevalence data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 and UN population estimates for 2020. The list of underlying conditions relevant to COVID-19 was determined by mapping the conditions listed in GBD 2017 to those listed in guidelines published by WHO and public health agencies in the UK and the USA. We analysed data from two large multimorbidity studies to determine appropriate adjustment factors for clustering and multimorbidity. To help interpretation of the degree of risk among those at increased risk, we also estimated the number of individuals at high risk (defined as those that would require hospital admission if infected) using age-specific infection–hospitalisation ratios for COVID-19 estimated for mainland China and making adjustments to reflect country-specific differences in the prevalence of underlying conditions and frailty. We assumed males were twice at likely as females to be at high risk. We also calculated the number of individuals without an underlying condition that could be considered at increased risk because of their age, using minimum ages from 50 to 70 years. We generated uncertainty intervals (UIs) for our estimates by running low and high scenarios using the lower and upper 95% confidence limits for country population size, disease prevalences, multimorbidity fractions, and infection–hospitalisation ratios, and plausible low and high estimates for the degree of clustering, informed by multimorbidity studies. Findings: We estimated that 1·7 billion (UI 1·0–2·4) people, comprising 22% (UI 15–28) of the global population, have at least one underlying condition that puts them at increased risk of severe COVID-19 if infected (ranging from <5% of those younger than 20 years to >66% of those aged 70 years or older). We estimated that 349 million (186–787) people (4% [3–9] of the global population) are at high risk of severe COVID-19 and would require hospital admission if infected (ranging from <1% of those younger than 20 years to approximately 20% of those aged 70 years or older). We estimated 6% (3–12) of males to be at high risk compared with 3% (2–7) of females. The share of the population at increased risk was highest in countries with older populations, African countries with high HIV/AIDS prevalence, and small island nations with high diabetes prevalence. Estimates of the number of individuals at increased risk were most sensitive to the prevalence of chronic kidney disease, diabetes, cardiovascular disease, and chronic respiratory disease. Interpretation: About one in five individuals worldwide could be at increased risk of severe COVID-19, should they become infected, due to underlying health conditions, but this risk varies considerably by age. Our estimates are uncertain, and focus on underlying conditions rather than other risk factors such as ethnicity, socioeconomic deprivation, and obesity, but provide a starting point for considering the number of individuals that might need to be shielded or vaccinated as the global pandemic unfolds. Funding: UK Department for International Development, Wellcome Trust, Health Data Research UK, Medical Research Council, and National Institute for Health Research

Ontogeny of Toll-Like Receptor Mediated Cytokine Responses of Human Blood Mononuclear Cells

Newborns and young infants suffer increased infectious morbidity and mortality as compared to older children and adults. Morbidity and mortality due to infection are highest during the first weeks of life, decreasing over several years. Furthermore, most vaccines are not administered around birth, but over the first few years of life. A more complete understanding of the ontogeny of the immune system over the first years of life is thus urgently needed. Here, we applied the most comprehensive analysis focused on the innate immune response following TLR stimulation over the first 2 years of life in the largest such longitudinal cohort studied to-date (35 subjects). We found that innate TLR responses (i) known to support Th17 adaptive immune responses (IL-23, IL-6) peaked around birth and declined over the following 2 years only to increase again by adulthood; (ii) potentially supporting antiviral defense (IFN-α) reached adult level function by 1 year of age; (iii) known to support Th1 type immunity (IL-12p70, IFN-γ) slowly rose from a low at birth but remained far below adult responses even at 2 years of age; (iv) inducing IL-10 production steadily declined from a high around birth to adult levels by 1 or 2 years of age, and; (v) leading to production of TNF-α or IL-1β varied by stimuli. Our data contradict the notion of a linear progression from an ‘immature’ neonatal to a ‘mature’ adult pattern, but instead indicate the existence of qualitative and quantitative age-specific changes in innate immune reactivity in response to TLR stimulation