Spatial connectivity in mosquito-borne disease models: a systematic review of methods and assumptions

This is the final version. Available from The Royal Society via the DOI in this record.Data extracted from the studies included in this systematic review are available from https://github.com/sophie-a-lee/mbd_connectivity_review and archived in a permanent repository on Zenodo (http://doi.org/10.5281/zenodo.4706866).Spatial connectivity plays an important role in mosquito-borne disease transmission. Connectivity can arise for many reasons, including shared environments, vector ecology and human movement. This systematic review synthesizes the spatial methods used to model mosquito-borne diseases, their spatial connectivity assumptions and the data used to inform spatial model components. We identified 248 papers eligible for inclusion. Most used statistical models (84.2%), although mechanistic are increasingly used. We identified 17 spatial models which used one of four methods (spatial covariates, local regression, random effects/fields and movement matrices). Over 80% of studies assumed that connectivity was distance-based despite this approach ignoring distant connections and potentially oversimplifying the process of transmission. Studies were more likely to assume connectivity was driven by human movement if the disease was transmitted by an Aedes mosquito. Connectivity arising from human movement was more commonly assumed in studies using a mechanistic model, likely influenced by a lack of statistical models able to account for these connections. Although models have been increasing in complexity, it is important to select the most appropriate, parsimonious model available based on the research question, disease transmission process, the spatial scale and availability of data, and the way spatial connectivity is assumed to occur.Engineering and Physical Sciences Research Council (EPSRC)The Royal Societ

Exhaled carbon monoxide in asthmatics: a meta-analysis

<p>Abstract</p> <p>Background</p> <p>The non-invasive assessment of airway inflammation is potentially advantageous in asthma management. Exhaled carbon monoxide (eCO) measurement is cheap and has been proposed to reflect airway inflammation and oxidative stress but current data are conflicting. The purpose of this meta-analysis is to determine whether eCO is elevated in asthmatics, is regulated by steroid treatment and reflects disease severity and control.</p> <p>Methods</p> <p>A systematic search for English language articles published between 1997 and 2009 was performed using Medline, Embase and Cochrane databases. Observational studies comparing eCO in non-smoking asthmatics and healthy subjects or asthmatics before and after steroid treatment were included. Data were independently extracted by two investigators and analyzed to generate weighted mean differences using either a fixed or random effects meta-analysis depending upon the degree of heterogeneity.</p> <p>Results</p> <p>18 studies were included in the meta-analysis. The eCO level was significantly higher in asthmatics as compared to healthy subjects and in intermittent asthma as compared to persistent asthma. However, eCO could not distinguish between steroid-treated asthmatics and steroid-free patients nor separate controlled and partly-controlled asthma from uncontrolled asthma in cross-sectional studies. In contrast, eCO was significantly reduced following a course of corticosteroid treatment.</p> <p>Conclusions</p> <p>eCO is elevated in asthmatics but levels only partially reflect disease severity and control. eCO might be a potentially useful non-invasive biomarker of airway inflammation and oxidative stress in nonsmoking asthmatics.</p

Work done in the margins:A comparative study of mental health literacy in pre-service teacher education in Australia and in Scotland

Ensuring pre-service teachers have strong mental health literacy is vital for progress towards an inclusive, effective education system; yet little is known about how pre-service teachers are prepared for practice with school students who present with poor mental health. The original, internationally comparative small-scale (N = 24) qualitative study reported here compared current mental health literacy provision to pre-service teacher education students in Scotland and Australia. Semi-structured telephone interviews with teacher educators who delivered mental health content divulged highly variable, often ad-hoc mental health literacy provision; a concern, given the prevalence of poor mental health affecting children and young people in schools. Thematic data analysis revealed striking commonalities among issues raised by participants from both countries, highlighting the need for urgent improvement in the provision of mental health literacy to pre-service teachers. Results suggest the possibility of strategically developing a joint Australian-Scottish mental health component suitable for delivery in both countries

Role of protein kinase C and NF-κB in proteolysis-inducing factor-induced proteasome expression in C2C12 myotubes

Proteolysis-inducing factor (PIF) is a sulphated glycoprotein produced by cachexia-inducing tumours, which initiates muscle protein degradation through an increased expression of the ubiquitin–proteasome proteolytic pathway. The role of kinase C (PKC) in PIF-induced proteasome expression has been studied in murine myotubes as a surrogate model of skeletal muscle. Proteasome expression induced by PIF was attenuated by 4alpha-phorbol 12-myristate 13-acetate (100 nM) and by the PKC inhibitors Ro31-8220 (10 muM), staurosporine (300 nM), calphostin C (300 nM) and Gö 6976 (200 muM). Proteolysis-inducing factor-induced activation of PKCalpha, with translocation from the cytosol to the membrane at the same concentration as that inducing proteasome expression, and this effect was attenuated by calphostin C. Myotubes transfected with a constitutively active PKCalpha (pCO2) showed increased expression of proteasome activity, and a longer time course, compared with their wild-type counterparts. In contrast, myotubes transfected with a dominant-negative PKCalpha (pKS1), which showed no activation of PKCalpha in response to PIF, exhibited no increase in proteasome activity at any time point. Proteolysis-inducing factor-induced proteasome expression has been suggested to involve the transcription factor nuclear factor-kappaB (NF-kappaB), which may be activated through PKC. Proteolysis-inducing factor induced a decrease in cytosolic I-kappaBalpha and an increase in nuclear binding of NF-kappaB in pCO2, but not in pKS1, and the effect in wild-type cells was attenuated by calphostin C, confirming that it was mediated through PKC. This suggests that PKC may be involved in the phosphorylation and degradation of I-kappaBalpha, induced by PIF, necessary for the release of NF-kappaB from its inactive cytosolic complex

Seasonal changes in patterns of gene expression in avian song control brain regions.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Photoperiod and hormonal cues drive dramatic seasonal changes in structure and function of the avian song control system. Little is known, however, about the patterns of gene expression associated with seasonal changes. Here we address this issue by altering the hormonal and photoperiodic conditions in seasonally-breeding Gambel's white-crowned sparrows and extracting RNA from the telencephalic song control nuclei HVC and RA across multiple time points that capture different stages of growth and regression. We chose HVC and RA because while both nuclei change in volume across seasons, the cellular mechanisms underlying these changes differ. We thus hypothesized that different genes would be expressed between HVC and RA. We tested this by using the extracted RNA to perform a cDNA microarray hybridization developed by the SoNG initiative. We then validated these results using qRT-PCR. We found that 363 genes varied by more than 1.5 fold (>log(2) 0.585) in expression in HVC and/or RA. Supporting our hypothesis, only 59 of these 363 genes were found to vary in both nuclei, while 132 gene expression changes were HVC specific and 172 were RA specific. We then assigned many of these genes to functional categories relevant to the different mechanisms underlying seasonal change in HVC and RA, including neurogenesis, apoptosis, cell growth, dendrite arborization and axonal growth, angiogenesis, endocrinology, growth factors, and electrophysiology. This revealed categorical differences in the kinds of genes regulated in HVC and RA. These results show that different molecular programs underlie seasonal changes in HVC and RA, and that gene expression is time specific across different reproductive conditions. Our results provide insights into the complex molecular pathways that underlie adult neural plasticity

The increasing importance of atmospheric demand for ecosystem water and carbon fluxes

Soil moisture supply and atmospheric demand for water independently limit—and profoundly affect—vegetation productivity and water use during periods of hydrologic stress1, 2, 3, 4. Disentangling the impact of these two drivers on ecosystem carbon and water cycling is difficult because they are often correlated, and experimental tools for manipulating atmospheric demand in the field are lacking. Consequently, the role of atmospheric demand is often not adequately factored into experiments or represented in models5, 6, 7. Here we show that atmospheric demand limits surface conductance and evapotranspiration to a greater extent than soil moisture in many biomes, including mesic forests that are of particular importance to the terrestrial carbon sink8, 9. Further, using projections from ten general circulation models, we show that climate change will increase the importance of atmospheric constraints to carbon and water fluxes in all ecosystems. Consequently, atmospheric demand will become increasingly important for vegetation function, accounting for >70% of growing season limitation to surface conductance in mesic temperate forests. Our results suggest that failure to consider the limiting role of atmospheric demand in experimental designs, simulation models and land management strategies will lead to incorrect projections of ecosystem responses to future climate conditions

Aptamer-based multiplexed proteomic technology for biomarker discovery

Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine

Song Practice Promotes Acute Vocal Variability at a Key Stage of Sensorimotor Learning

BACKGROUND: Trial by trial variability during motor learning is a feature encoded by the basal ganglia of both humans and songbirds, and is important for reinforcement of optimal motor patterns, including those that produce speech and birdsong. Given the many parallels between these behaviors, songbirds provide a useful model to investigate neural mechanisms underlying vocal learning. In juvenile and adult male zebra finches, endogenous levels of FoxP2, a molecule critical for language, decrease two hours after morning song onset within area X, part of the basal ganglia-forebrain pathway dedicated to song. In juveniles, experimental 'knockdown' of area X FoxP2 results in abnormally variable song in adulthood. These findings motivated our hypothesis that low FoxP2 levels increase vocal variability, enabling vocal motor exploration in normal birds. METHODOLOGY/PRINCIPAL FINDINGS: After two hours in either singing or non-singing conditions (previously shown to produce differential area X FoxP2 levels), phonological and sequential features of the subsequent songs were compared across conditions in the same bird. In line with our prediction, analysis of songs sung by 75 day (75d) birds revealed that syllable structure was more variable and sequence stereotypy was reduced following two hours of continuous practice compared to these features following two hours of non-singing. Similar trends in song were observed in these birds at 65d, despite higher overall within-condition variability at this age. CONCLUSIONS/SIGNIFICANCE: Together with previous work, these findings point to the importance of behaviorally-driven acute periods during song learning that allow for both refinement and reinforcement of motor patterns. Future work is aimed at testing the observation that not only does vocal practice influence expression of molecular networks, but that these networks then influence subsequent variability in these skills