Memory Inflation during Chronic Viral Infection Is Maintained by Continuous Production of Short-Lived, Functional T Cells

SummaryDuring persistent murine cytomegalovirus (MCMV) infection, the T cell response is maintained at extremely high intensity for the life of the host. These cells closely resemble human CMV-specific cells, which compose a major component of the peripheral T cell compartment in most people. Despite a phenotype that suggests extensive antigen-driven differentiation, MCMV-specific T cells remain functional and respond vigorously to viral challenge. We hypothesized that a low rate of antigen-driven proliferation would account for the maintenance of this population. Instead, we found that most of these cells divided only sporadically in chronically infected hosts and had a short half-life in circulation. The overall population was supported, at least in part, by memory T cells primed early in infection, as well as by recruitment of naive T cells at late times. Thus, these data show that memory inflation is maintained by a continuous replacement of short-lived, functional cells during chronic MCMV infection

Phylogeography of six codistributed New Zealand cicadas and their relationship to multiple biogeographical boundaries suggest a re-evaluation of the Taupo Line

Comparative biogeographers question the extent to which codistributed species respond similarly to environmental change. Such responses should create similar, appropriately timed patterns of cladogenesis among codistributed taxa compared to evolutionary independence, which may limit the predictions that can be made for unstudied species. Here, we compare phylogeographical patterns across ecologically divergent, codistributed taxa in the light of New Zealand's palaeohistory. Location: North Island, New Zealand. Methods: Mitochondrial DNA from six codistributed cicada species (Kikihia ochrina, K. cutora, K. laneorum, K. cauta, K. scutellaris and K. dugdalei) was analysed using phylogenetic methods and molecular dating techniques. We analysed phylogeographical distributions using analysis of molecular variance (AMOVA) to determine the significance of hypothesized biogeographical boundaries for clade differentiation and spatial distribution of genetic diversity. Results: Five species (Kikihia ochrina, K. cutora, K. laneorum, K. cauta and K. scutellaris) show various degrees of intraspecific concordance with biogeographical boundaries found in previously studied taxa - the Kauri Line, the Northland Line and the newly identified Cockayne's Line. Clade splits of forest species correlate with the Kauri Line and/or Northland Line, whereas splits of scrub/hill species correlate with Cockayne's Line. Four species (Kikihia ochrina, K. cutora, K. laneorum and K. cauta) diversified before the Last Glacial Maximum (LGM, 20 ka), whereas two species (K. scutellaris and K. dugdalei) show only post-LGM diversification. Main conclusions: Despite species idiosyncrasies, we see the imprint of shared palaeoclimatic/geological events. We distinguish between (1) the importance of biogeographical lines as the demarcation between older genetically diverse and newer genetically depauperate populations, and (2) the importance of lines as biogeographical boundaries between sister clades. We also stress the importance of dating clade splits to ensure consistency with explanations for the biogeographical lines in question. We suggest that the Taupo Line has been overemphasized as a biogeographical boundary, whereas the importance of the mountain axis running north-east to south-west ('Cockayne's Line') has been overlooked

Identification of cancer risk and associated behaviour: implications for social marketing campaigns for cancer prevention

Background Community misconception of what causes cancer is an important consideration when devising communication strategies around cancer prevention, while those initiating social marketing campaigns must decide whether to target the general population or to tailor messages for different audiences. This paper investigates the relationships between demographic characteristics, identification of selected cancer risk factors, and associated protective behaviours, to inform audience segmentation for cancer prevention social marketing. Methods Data for this cross-sectional study (n = 3301) are derived from Cancer Council New South Wales’ 2013 Cancer Prevention Survey. Descriptive statistics and logistic regression models were used to investigate the relationship between respondent demographic characteristics and identification of each of seven cancer risk factors; demographic characteristics and practice of the seven ‘protective’ behaviours associated with the seven cancer risk factors; and identification of cancer risk factors and practising the associated protective behaviours, controlling for demographic characteristics. Results More than 90% of respondents across demographic groups identified sun exposure and smoking cigarettes as moderate or large cancer risk factors. Around 80% identified passive smoking as a moderate/large risk factor, and 40–60% identified being overweight or obese, drinking alcohol, not eating enough vegetables and not eating enough fruit. Women and older respondents were more likely to identify most cancer risk factors as moderate/large, and to practise associated protective behaviours. Education was correlated with identification of smoking as a moderate/large cancer risk factor, and with four of the seven protective behaviours. Location (metropolitan/regional) and country of birth (Australia/other) were weak predictors of identification and of protective behaviours. Identification of a cancer risk factor as moderate/large was a significant predictor for five out of seven associated cancer-protective behaviours, controlling for demographic characteristics. Conclusions These findings suggest a role for both audience segmentation and whole-of-population approaches in cancer-prevention social marketing campaigns. Targeted campaigns can address beliefs of younger people and men about cancer risk factors. Traditional population campaigns can enhance awareness of being overweight, alcohol consumption, and poor vegetable and fruit intake as cancer risk factors

A molecular phylogeny of the cicadas (Hemiptera: Cicadidae) with a review of tribe and subfamily classification:

A molecular phylogeny and a review of family-group classification are presented for 137 species (ca. 125 genera) of the insect family Cicadidae, the true cicadas, plus two species of hairy cicadas (Tettigarctidae) and two outgroup species from Cercopidae. Five genes, two of them mitochondrial, comprise the 4992 base-pair molecular dataset. Maximum-likelihood and Bayesian phylogenetic results are shown, including analyses to address potential base composition bias. Tettigarcta is confirmed as the sister-clade of the Cicadidae and support is found for three subfamilies identified in an earlier morphological cladistic analysis. A set of paraphyletic deep-level clades formed by African genera are together named as Tettigomyiinae n. stat. Taxonomic reassignments of genera and tribes are made where morphological examination confirms incorrect placements suggested by the molecular tree, and 11 new tribes are defined (Arenopsaltriini n. tribe, Durangonini n. tribe, Katoini n. tribe, Lacetasini n. tribe, Macrotristriini n. tribe, Malagasiini n. tribe, Nelcyndanini n. tribe, Pagiphorini n. tribe, Pictilini n. tribe, Psaltodini n. tribe, and Selymbriini n. tribe). Tribe Tacuini n. syn. is synonymized with Cryptotympanini, and Tryellina n. syn. is synonymized with an expanded Tribe Lamotialnini. Tribe Hyantiini n. syn. is synonymized with Fidicinini. Tribe Sinosenini is transferred to Cicadinae from Cicadettinae, Cicadatrini is moved to Cicadettinae from Cicadinae, and Ydiellini and Tettigomyiini are transferred to Tettigomyiinae n. stat from Cicadettinae. While the subfamily Cicadinae, historically defined by the presence of timbal covers, is weakly supported in the molecular tree, high taxonomic rank is not supported for several earlier clades based on unique morphology associated with sound production

Versatile Aggressive Mimicry of Cicadas by an Australian Predatory Katydid

Background: In aggressive mimicry, a predator or parasite imitates a signal of another species in order to exploit the recipient of the signal. Some of the most remarkable examples of aggressive mimicry involve exploitation of a complex signal-response system by an unrelated predator species. Methodology/Principal Findings: We have found that predatory Chlorobalius leucoviridis katydids (Orthoptera: Tettigoniidae) can attract male cicadas (Hemiptera: Cicadidae) by imitating the species-specific wing-flick replies of sexually receptive female cicadas. This aggressive mimicry is accomplished both acoustically, with tegminal clicks, and visually, with synchronized body jerks. Remarkably, the katydids respond effectively to a variety of complex, species-specific Cicadettini songs, including songs of many cicada species that the predator has never encountered. Conclusions/Significance: We propose that the versatility of aggressive mimicry in C. leucoviridis is accomplished by exploiting general design elements common to the songs of many acoustically signaling insects that use duets in pairformation. Consideration of the mechanism of versatile mimicry in C. leucoviridis may illuminate processes driving the evolution of insect acoustic signals, which play a central role in reproductive isolation of populations and the formation of species

All Our Babies Cohort Study: recruitment of a cohort to predict women at risk of preterm birth through the examination of gene expression profiles and the environment

<p>Abstract</p> <p>Background</p> <p>Preterm birth is the leading cause of perinatal morbidity and mortality. Risk factors for preterm birth include a personal or familial history of preterm delivery, ethnicity and low socioeconomic status yet the ability to predict preterm delivery before the onset of preterm labour evades clinical practice. Evidence suggests that genetics may play a role in the multi-factorial pathophysiology of preterm birth. The All Our Babies Study is an on-going community based longitudinal cohort study that was designed to establish a cohort of women to investigate how a women's genetics and environment contribute to the pathophysiology of preterm birth. Specifically this study will examine the predictive potential of maternal leukocytes for predicting preterm birth in non-labouring women through the examination of gene expression profiles and gene-environment interactions.</p> <p>Methods/Design</p> <p>Collaborations have been established between clinical lab services, the provincial health service provider and researchers to create an interdisciplinary study design for the All Our Babies Study. A birth cohort of 2000 women has been established to address this research question. Women provide informed consent for blood sample collection, linkage to medical records and complete questionnaires related to prenatal health, service utilization, social support, emotional and physical health, demographics, and breast and infant feeding. Maternal blood samples are collected in PAXgene™ RNA tubes between 18-22 and 28-32 weeks gestation for transcriptomic analyses.</p> <p>Discussion</p> <p>The All Our Babies Study is an example of how investment in clinical-academic-community partnerships can improve research efficiency and accelerate the recruitment and data collection phases of a study. Establishing these partnerships during the study design phase and maintaining these relationships through the duration of the study provides the unique opportunity to investigate the multi-causal factors of preterm birth. The overall All Our Babies Study results can potentially lead to healthier pregnancies, mothers, infants and children.</p

Anticoagulant selection in relation to the SAMe-TT2R2 score in patients with atrial fibrillation. the GLORIA-AF registry

Aim: The SAMe-TT2R2 score helps identify patients with atrial fibrillation (AF) likely to have poor anticoagulation control during anticoagulation with vitamin K antagonists (VKA) and those with scores &gt;2 might be better managed with a target-specific oral anticoagulant (NOAC). We hypothesized that in clinical practice, VKAs may be prescribed less frequently to patients with AF and SAMe-TT2R2 scores &gt;2 than to patients with lower scores. Methods and results: We analyzed the Phase III dataset of the Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation (GLORIA-AF), a large, global, prospective global registry of patients with newly diagnosed AF and ≥1 stroke risk factor. We compared baseline clinical characteristics and antithrombotic prescriptions to determine the probability of the VKA prescription among anticoagulated patients with the baseline SAMe-TT2R2 score &gt;2 and ≤ 2. Among 17,465 anticoagulated patients with AF, 4,828 (27.6%) patients were prescribed VKA and 12,637 (72.4%) patients an NOAC: 11,884 (68.0%) patients had SAMe-TT2R2 scores 0-2 and 5,581 (32.0%) patients had scores &gt;2. The proportion of patients prescribed VKA was 28.0% among patients with SAMe-TT2R2 scores &gt;2 and 27.5% in those with scores ≤2. Conclusions: The lack of a clear association between the SAMe-TT2R2 score and anticoagulant selection may be attributed to the relative efficacy and safety profiles between NOACs and VKAs as well as to the absence of trial evidence that an SAMe-TT2R2-guided strategy for the selection of the type of anticoagulation in NVAF patients has an impact on clinical outcomes of efficacy and safety. The latter hypothesis is currently being tested in a randomized controlled trial. Clinical trial registration: URL: https://www.clinicaltrials.gov//Unique identifier: NCT01937377, NCT01468701, and NCT01671007

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)