Gene expression plasticity across hosts of an invasive scale insect species

For plant-eating insects, we still have only a nascent understanding of the genetic basis of host-use promiscuity. Here, to improve that situation, we investigated host-induced gene expression plasticity in the invasive lobate lac scale insect, Paratachardina pseudolobata (Hemiptera: Keriidae). We were particularly interested in the differential expression of detoxification and effector genes, which are thought to be critical for overcoming a plant's chemical defenses. We collected RNA samples from P. pseudolobata on three different host plant species, assembled transcriptomes de novo, and identified transcripts with significant host-induced gene expression changes. Gene expression plasticity was pervasive, but the expression of most detoxification and effector genes was insensitive to the host environment. Nevertheless, some types of detoxification genes were more differentially expressed than expected by chance. Moreover, we found evidence of a trade-off between expression of genes involved in primary and secondary metabolism; hosts that induced lower expression of genes for detoxification induced higher expression of genes for growth. Our findings are largely consonant with those of several recently published studies of other plant-eating insect species. Thus, across plant-eating insect species, there may be a common set of gene expression changes that enable host-use promiscuity

Real-Time Projection to Verify Plan Success During Execution

The Mission Data System provides a framework for modeling complex systems in terms of system behaviors and goals that express intent. Complex activity plans can be represented as goal networks that express the coordination of goals on different state variables of the system. Real-time projection extends the ability of this system to verify plan achievability (all goals can be satisfied over the entire plan) into the execution domain so that the system is able to continuously re-verify a plan as it is executed, and as the states of the system change in response to goals and the environment. Previous versions were able to detect and respond to goal violations when they actually occur during execution. This new capability enables the prediction of future goal failures; specifically, goals that were previously found to be achievable but are no longer achievable due to unanticipated faults or environmental conditions. Early detection of such situations enables operators or an autonomous fault response capability to deal with the problem at a point that maximizes the available options. For example, this system has been applied to the problem of managing battery energy on a lunar rover as it is used to explore the Moon. Astronauts drive the rover to waypoints and conduct science observations according to a plan that is scheduled and verified to be achievable with the energy resources available. As the astronauts execute this plan, the system uses this new capability to continuously re-verify the plan as energy is consumed to ensure that the battery will never be depleted below safe levels across the entire plan

Protocol for ADDITION-PRO: a longitudinal cohort study of the cardiovascular experience of individuals at high risk for diabetes recruited from Danish primary care.

BACKGROUND: Screening programmes for type 2 diabetes inevitably find more individuals at high risk for diabetes than people with undiagnosed prevalent disease. While well established guidelines for the treatment of diabetes exist, less is known about treatment or prevention strategies for individuals found at high risk following screening. In order to make better use of the opportunities for primary prevention of diabetes and its complications among this high risk group, it is important to quantify diabetes progression rates and to examine the development of early markers of cardiovascular disease and microvascular diabetic complications. We also require a better understanding of the mechanisms that underlie and drive early changes in cardiometabolic physiology. The ADDITION-PRO study was designed to address these issues among individuals at different levels of diabetes risk recruited from Danish primary care. METHODS/DESIGN: ADDITION-PRO is a population-based, longitudinal cohort study of individuals at high risk for diabetes. 16,136 eligible individuals were identified at high risk following participation in a stepwise screening programme in Danish general practice between 2001 and 2006. All individuals with impaired glucose regulation at screening, those who developed diabetes following screening, and a random sub-sample of those at lower levels of diabetes risk were invited to attend a follow-up health assessment in 2009-2011 (n=4,188), of whom 2,082 (50%) attended. The health assessment included detailed measurement of anthropometry, body composition, biochemistry, physical activity and cardiovascular risk factors including aortic stiffness and central blood pressure. All ADDITION-PRO participants are being followed for incident cardiovascular disease and death. DISCUSSION: The ADDITION-PRO study is designed to increase understanding of cardiovascular risk and its underlying mechanisms among individuals at high risk of diabetes. Key features of this study include (i) a carefully characterised cohort at different levels of diabetes risk; (ii) detailed measurement of cardiovascular and metabolic risk factors; (iii) objective measurement of physical activity behaviour; and (iv) long-term follow-up of hard clinical outcomes including mortality and cardiovascular disease. Results will inform policy recommendations concerning cardiovascular risk reduction and treatment among individuals at high risk for diabetes. The detailed phenotyping of this cohort will also allow a number of research questions concerning early changes in cardiometabolic physiology to be addressed.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Early laboratory diagnosis of COVID-19 by antigen detection in blood samples of the SARS-COV-2 nucleocapsid protein

The purpose of this study was to characterize the diagnostic performance of a newly developed enzyme-linked immunosorbent assay (ELISA) for detection of SARS-CoV-2 nucleocapsid protein (NP) in blood. Blood samples were collected during hospitalization of 165 inpatients with PCR-confirmed SARS-CoV-2 infection and from 505 outpatients predominantly with relevant symptoms of COVID-19 simultaneously with PCR testing. For the 143 inpatients who had their first blood sample collected within 2 weeks after PCR-confirmed infection, the diagnostic sensitivity of the ELISA was 91.6%. The mean NP concentration of the 131 ELISA-positive blood samples was 1,734 pg/ml (range, 10 to 3,840 pg/ml). An exponential decline in NP concentration was observed for 368 blood samples collected over the first 4 weeks after PCR-confirmed SARS-CoV-2 infection, and all blood samples taken later had an NP concentration below the 10-pg/ml diagnostic cutoff. The diagnostic sensitivity of the ELISA was 81.4% for the 43 blood samples collected from outpatients with a simultaneous positive PCR test, and the mean NP concentration of the 35 ELISA-positive samples was 157 pg/ml (range, 10 to 1,377 pg/ml). For the 462 outpatients with a simultaneous negative PCR test, the diagnostic specificity of the ELISA was 99.8%. In conclusion, the SARS-CoV-2 NP ELISA is a suitable laboratory diagnostic test for COVID-19, particularly for hospitals, where blood samples are readily available and screening of serum or plasma by ELISA can facilitate prevention of nosocomial infections and reduce the requirement for laborious swab sampling and subsequent PCR analysis to confirmatory tests only

Bayesian Methods for Exoplanet Science

Exoplanet research is carried out at the limits of the capabilities of current telescopes and instruments. The studied signals are weak, and often embedded in complex systematics from instrumental, telluric, and astrophysical sources. Combining repeated observations of periodic events, simultaneous observations with multiple telescopes, different observation techniques, and existing information from theory and prior research can help to disentangle the systematics from the planetary signals, and offers synergistic advantages over analysing observations separately. Bayesian inference provides a self-consistent statistical framework that addresses both the necessity for complex systematics models, and the need to combine prior information and heterogeneous observations. This chapter offers a brief introduction to Bayesian inference in the context of exoplanet research, with focus on time series analysis, and finishes with an overview of a set of freely available programming libraries.Comment: Invited revie

Breastfeeding and the origins of health: Interdisciplinary perspectives and priorities

Breastfeeding and human milk (HM) are critically important to maternal, infant and population health. This paper summarizes the proceedings of a workshop that convened a multidisciplinary panel of researchers to identify key priorities and anticipated breakthroughs in breastfeeding and HM research, discuss perceived barriers and challenges to achieving these breakthroughs and propose a constructive action plan to maximize the impact of future research in this field. Priority research areas identified were as follows: (1) addressing low breastfeeding rates and inequities using mixed methods, community partnerships and implementation science approaches; (2) improving awareness of evidence-based benefits, challenges and complexities of breastfeeding and HM among health practitioners and the public; (3) identifying differential impacts of alternative modes of HM feeding including expressed/pumped milk, donor milk and shared milk; and (4) developing a mechanistic understanding of the health effects of breastfeeding and the contributors to HM composition and variability. Key barriers and challenges included (1) overcoming methodological limitations of epidemiological breastfeeding research and mechanistic HM research; (2) counteracting ‘breastfeeding denialism’ arising from negative personal breastfeeding experiences; (3) distinguishing and aligning research and advocacy efforts; and (4) managing real and perceived conflicts of interest. To advance research on breastfeeding and HM and maximize the reach and impact of this research, larger investments are needed, interdisciplinary collaboration is essential, and the scientific community must engage families and other stakeholders in research planning and knowledge translation