CD4 Depletion in SIV-Infected Macaques Results in Macrophage and Microglia Infection with Rapid Turnover of Infected Cells

In rhesus macaques (RMs), experimental depletion of CD4+ T-cells prior to SIV infection results in higher viremia and emergence of CD4-independent SIV-envelopes. In this study we used the rhesus recombinant anti-CD4 antibody CD4R1 to deplete RM CD4+ T-cells prior to SIVmac251 infection and investigate the sources of the increased viral burden and the lifespan of productively infected cells. CD4-depleted animals showed (i) set-point viral load two-logs higher than controls; (ii) macrophages constituting 80% of all SIV vRNA+ cells in lymph node and mucosal tissues; (iii) substantial expansion of pro-inflammatory monocytes; (iv) aberrant activation and infection of microglial cells; and (v) lifespan of productively infected cells significantly longer in comparison to controls, but markedly shorter than previously estimated for macrophages. The net effect of CD4+ T-cell depletion is an inability to control SIV replication and a shift in the tropism of infected cells to macrophages, microglia, and, potentially, other CD4-low cells which all appear to have a shortened in vivo lifespan. We believe these findings have important implications for HIV eradication studies

Oral Health in Women During Preconception and Pregnancy: Implications for Birth Outcomes and Infant Oral Health

The mouth is an obvious portal of entry to the body, and oral health reflects and influences general health and well being. Maternal oral health has significant implications for birth outcomes and infant oral health. Maternal periodontal disease, that is, a chronic infection of the gingiva and supporting tooth structures, has been associated with preterm birth, development of preeclampsia, and delivery of a small-for-gestational age infant. Maternal oral flora is transmitted to the newborn infant, and increased cariogenic flora in the mother predisposes the infant to the development of caries. It is intriguing to consider preconception, pregnancy, or intrapartum treatment of oral health conditions as a mechanism to improve women's oral and general health, pregnancy outcomes, and their children's dental health. However, given the relationship between oral health and general health, oral health care should be a goal in its own right for all individuals. Regardless of the potential for improved oral health to improve pregnancy outcomes, public policies that support comprehensive dental services for vulnerable women of childbearing age should be expanded so that their own oral and general health is safeguarded and their children's risk of caries is reduced. Oral health promotion should include education of women and their health care providers ways to prevent oral disease from occurring, and referral for dental services when disease is present

Preterm low birthweight and the role of oral bacteria

Preterm and low birthweight (PTLBW) continues to be a major cause of mortality and morbidity across the world. In recent years, maternal periodontal disease has been implicated as a risk factor for adverse pregnancy outcomes. There is conflicting evidence to support such an outcome as illustrated by descriptive, case control and randomised controlled trials involving pregnant women from across the world, using different measurement tools to determine the level of periodontal disease. Whilst considering the literature, there is evidence for both arguments, based on the effect of periodontal inflammatory by products. Bacteria associated with periodontal disease are not dissimilar to those known to be associated with genito-urinary bacterial infections and adverse pregnancy outcomes. Several groups have demonstrated the apparent translocation of Fusobacterium nucleatum, Prevotella nigrescens, Prevotella intermedia, Porphyromonus gingivalis, Treponema denticola to the foetal placental unit whereby a maternal or foetal response has been detected resulting in premature birth or low birthweight. The normal process of parturition involves a cascade of events including a build-up of inflammatory mediators as linked to inflammation, whereby the maternal environment becomes hostile and threatens the well-being of the infant, and the foetus expelled. The question remains therefore, is there a greater risk of delivering a PTLBW infant when the mother has detectable periodontal disease, or is the release of inflammatory mediators and their translocation via the haematogenous route sufficient to induce a poor pregnancy outcome? The data investigated would suggest that there is a positive outcome when certain oral gram-negative bacteria create a cumulative effect sufficient to trigger early delivery, which represents the final straw to result in preterm or low birthweight delivery. There is equally sufficient epidemiological evidence that does not support this outcome, but it is agreed that maintaining oral health during pregnancy is beneficial to the mother and her infant

Use of different RT-QuIC substrates for detecting CWD prions in the brain of Norwegian cervids

Chronic wasting disease (CWD) is a highly contagious prion disease affecting captive and free-ranging cervid populations. CWD has been detected in United States, Canada, South Korea and, most recently, in Europe (Norway, Finland and Sweden). Animals with CWD release infectious prions in the environment through saliva, urine and feces sustaining disease spreading between cervids but also potentially to other non-cervids ruminants (e.g. sheep, goats and cattle). In the light of these considerations and due to CWD unknown zoonotic potential, it is of utmost importance to follow specific surveillance programs useful to minimize disease spreading and transmission. The European community has already in place specific surveillance measures, but the traditional diagnostic tests performed on nervous or lymphoid tissues lack sensitivity. We have optimized a Real-Time Quaking-Induced Conversion (RT-QuIC) assay for detecting CWD prions with high sensitivity and specificity to try to overcome this problem. In this work, we show that bank vole prion protein (PrP) is an excellent substrate for RT-QuIC reactions, enabling the detection of trace-amounts of CWD prions, regardless of prion strain and cervid species. Beside supporting the traditional diagnostic tests, this technology could be exploited for detecting prions in peripheral tissues from live animals, possibly even at preclinical stages of the disease

Subjecting Elite Athletes to Inspiratory Breathing Load Reveals Behavioral and Neural Signatures of Optimal Performers in Extreme Environments

Background: It is unclear whether and how elite athletes process physiological or psychological challenges differently than healthy comparison subjects. In general, individuals optimize exercise level as it relates to differences between expected and experienced exertion, which can be conceptualized as a body prediction error. The process of computing a body prediction error involves the insular cortex, which is important for interoception, i.e. the sense of the physiological condition of the body. Thus, optimal performance may be related to efficient minimization of the body prediction error. We examined the hypothesis that elite athletes, compared to control subjects, show attenuated insular cortex activation during an aversive interoceptive challenge. Methodology/Principal Findings: Elite adventure racers (n = 10) and healthy volunteers (n = 11) performed a continuous performance task with varying degrees of a non-hypercapnic breathing load while undergoing functional magnetic resonance imaging. The results indicate that (1) non-hypercapnic inspiratory breathing load is an aversive experience associated with a profound activation of a distributed set of brain areas including bilateral insula, dorsolateral prefrontal cortex and anterior cingulated; (2) adventure racers relative to comparison subjects show greater accuracy on the continuous performance task during the aversive interoceptive condition; and (3) adventure racers show an attenuated right insula cortex response during and following the aversive interoceptive condition of non-hypercapnic inspirator

An atlas of genetic scores to predict multi-omic traits

The use of omic modalities to dissect the molecular underpinnings of common diseases and traits is becoming increasingly common. But multi-omic traits can be genetically predicted, which enables highly cost-effective and powerful analyses for studies that do not have multi-omics1. Here we examine a large cohort (the INTERVAL study2; n = 50,000 participants) with extensive multi-omic data for plasma proteomics (SomaScan, n = 3,175; Olink, n = 4,822), plasma metabolomics (Metabolon HD4, n = 8,153), serum metabolomics (Nightingale, n = 37,359) and whole-blood Illumina RNA sequencing (n = 4,136), and use machine learning to train genetic scores for 17,227 molecular traits, including 10,521 that reach Bonferroni-adjusted significance. We evaluate the performance of genetic scores through external validation across cohorts of individuals of European, Asian and African American ancestries. In addition, we show the utility of these multi-omic genetic scores by quantifying the genetic control of biological pathways and by generating a synthetic multi-omic dataset of the UK Biobank3 to identify disease associations using a phenome-wide scan. We highlight a series of biological insights with regard to genetic mechanisms in metabolism and canonical pathway associations with disease; for example, JAK-STAT signalling and coronary atherosclerosis. Finally, we develop a portal ( https://www.omicspred.org/ ) to facilitate public access to all genetic scores and validation results, as well as to serve as a platform for future extensions and enhancements of multi-omic genetic scores

Periodontal disease and some adverse perinatal outcomes in a cohort of low risk pregnant women

Objective: To evaluate the association of periodontal disease (PD) in pregnancy with some adverse perinatal outcomes. Method: This cohort study included 327 pregnant women divided in groups with or without PD. Indexes of plaque and gingival bleeding on probing, probing pocket depth, clinical attachment level and gingival recession were evaluated at one periodontal examination below 32 weeks of gestation. The rates of preterm birth (PTB), low birth weight (LBW), small for gestational age (SGA) neonates and prelabor rupture of membranes (PROM) were evaluated using Risk Ratios (95%CI) and Population Attributable Risk Fractions. Results: PD was associated with a higher risk of PTB (RRadj. 3.47 95% CI 1.62-7.43), LBW (RRadj. 2.93 95% CI 1.36-6.34) and PROM (RRadj. 2.48 95% CI 1.35-4.56), but not with SGA neonates (RR 2.38 95% CI 0.93 - 6.10). Conclusions: PD was a risk factor for PT, LBW and PROM among Brazilian low risk pregnant women

A chemical survey of exoplanets with ARIEL

Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet’s birth, and evolution. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25–7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and well-defined planet sample within its 4-year mission lifetime. Transit, eclipse and phase-curve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10–100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H2O, CO2, CH4 NH3, HCN, H2S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performed – using conservative estimates of mission performance and a full model of all significant noise sources in the measurement – using a list of potential ARIEL targets that incorporates the latest available exoplanet statistics. The conclusion at the end of the Phase A study, is that ARIEL – in line with the stated mission objectives – will be able to observe about 1000 exoplanets depending on the details of the adopted survey strategy, thus confirming the feasibility of the main science objectives.Peer reviewedFinal Published versio

Accurately Measuring Recombination between Closely Related HIV-1 Genomes

Retroviral recombination is thought to play an important role in the generation of immune escape and multiple drug resistance by shuffling pre-existing mutations in the viral population. Current estimates of HIV-1 recombination rates are derived from measurements within reporter gene sequences or genetically divergent HIV sequences. These measurements do not mimic the recombination occurring in vivo, between closely related genomes. Additionally, the methods used to measure recombination make a variety of assumptions about the underlying process, and often fail to account adequately for issues such as co-infection of cells or the possibility of multiple template switches between recombination sites. We have developed a HIV-1 marker system by making a small number of codon modifications in gag which allow recombination to be measured over various lengths between closely related viral genomes. We have developed statistical tools to measure recombination rates that can compensate for the possibility of multiple template switches. Our results show that when multiple template switches are ignored the error is substantial, particularly when recombination rates are high, or the genomic distance is large. We demonstrate that this system is applicable to other studies to accurately measure the recombination rate and show that recombination does not occur randomly within the HIV genome

Unlocking the power of big data in new product development

This study explores how big data can be used to enable customers to express unrecognised needs. By acquiring this information, managers can gain opportunities to develop customer-centred products. Big data can be defined as multimedia-rich and interactive low-cost information resulting from mass communication. It offers customers a better understanding of new products and provides new, simplified modes of large-scale interaction between customers and firms. Although previous studies have pointed out that firms can better understand customers’ preferences and needs by leveraging different types of available data, the situation is evolving, with increasing application of big data analytics for product development, operations and supply chain management. In order to utilise the customer information available from big data to a larger extent, managers need to identify how to establish a customer-involving environment that encourages customers to share their ideas with managers, contribute their know-how, fiddle around with new products, and express their actual preferences. We investigate a new product development project at an electronics company, STE, and describe how big data is used to connect to, interact with and involve customers in new product development in practice. Our findings reveal that big data can offer customer involvement so as to provide valuable input for developing new products. In this paper, we introduce a customer involvement approach as a new means of coming up with customer-centred new product development